What if the difference between a seamless tech transfer and a costly setback isn't your process, but how you orchestrate the people and details behind the scenes?
In this episode of the Smart Biotech Scientist Podcast, David Brühlmann shares hard-earned lessons on the complexities of tech transfer and scale-up in the biotech industry.
In Part 1, you learned the six-pillar framework. Now I'm giving you the implementation playbook—starting with the human element that most people completely miss.
Story time. I was leading a tech transfer to a new manufacturing site. Everything was progressing—slowly, but progressing. Except for one guy in QC. Every interaction was difficult. Analysis requests were unpredictable. My team was stressed. His team seemed stressed. Walls were going up.
I was convinced he was the problem. Resistant to change. Maybe territorial about his lab.
Then I did something I should've done weeks earlier. I walked into his lab. No agenda. Just a conversation.
Turns out? He wasn't resistant. He was drowning. His lab was understaffed. His backlog was crushing. And every time we showed up with an "urgent" sample request, it threw his entire week into chaos.
He craved predictability. I was creating chaos.
Once I understood that, everything changed. We built a sampling calendar to give him a longer term view.
The transformation was immediate. Not because the science changed. Because I finally understood what he needed.
Here's the lesson: Understanding stakeholder needs is as critical as understanding the process.
Now, your stakeholder protocol.
1️⃣ First, map early. Identify every stakeholder: QC, QA, manufacturing ops, process development, regulatory, even facilities and IT if your process has special requirements.
2️⃣ Second, understand motivations. What does each stakeholder need? What are their fears? The QC manager might fear analytical backlogs. The QA manager might fear audit findings. The manufacturing supervisor might fear unproven procedures. Write it down.
3️⃣ Third, communication plan. Match frequency and method to stakeholder type. Some people want weekly written updates. Some want face-to-face check-ins every two weeks. Some just want to know you'll call them if there's a problem.
4️⃣ Fourth, use the Power-Interest Grid. Focus your energy on high-power, high-interest stakeholders. They're the ones who can kill your project or accelerate it.
5️⃣ Fifth, build trust face-to-face whenever possible. Especially for the resisters. Email doesn't build trust. Video calls are better than nothing. But nothing beats sitting in someone's space and listening.
Another story. We transferred a process to a new site. Identical equipment specs. Identical SOPs. We'd even sent people for hands-on training.
First batch at the new site? Completely different performance. Lower viability. Lower titer. Different impurity profile.
We spent months troubleshooting. Tested everything. Media? Same lot numbers. Seed train? Same frozen vials. Bioreactor control? Same setpoints. Environmental monitoring? All in spec.
Finally, after exhausting every rational explanation, someone noticed the obvious. Different light exposure.
We ran a controlled study. Light exposure was affecting the culture. Not enough to trigger an out-of-spec environmental reading. Enough to change cell behavior.
The lesson? List ALL differences upfront—and even then, expect surprises. Environmental factors matter. Light. Temperature fluctuations in the room. Vibration from nearby equipment. Document everything, even the "obvious" stuff.
Now, your mass transfer checklist.
Calculate scale-down ratios for key parameters. Mixing time increases with scale—you need to plan for that. Power per volume is typically kept constant. kLa—oxygen transfer—plan for a decrease. Impeller tip speed is a major consideration for shear-sensitive products.
Run scale-down models at the receiving site before you commit to full scale. This isn't optional. You need to prove the physics work in their equipment with their utilities.
And document everything. Not just the process parameters. The room temperature range. The water quality specs. The equipment maintenance history. The things that live in people's heads and never make it into batch records.
Decision framework time.
When to build internal? Platform technology you'll use repeatedly. If you're a monoclonal antibody company planning five programs over three years, in-house manufacturing starts making sense. Core competitive advantage in manufacturing—if your IP is in the process, not just the molecule, you might need to keep it in-house. Commercial volumes that justify capital investment. Or absolute control requirements over IP and process knowledge.
When to outsource? Novel modality with uncertain commercial potential. Need speed to clinic—CDMOs have infrastructure ready today. Limited capital for facility investment. Or strategic redundancy—testing multiple CDMOs so you're not dependent on a single partner.
Matthias Müllner gave us the insight: External CMC expertise bridges gaps early—build internal capability gradually. You don't need to decide everything day one. Start with outsourced. Learn what you actually need. Then selectively insource the pieces that create competitive advantage.
📅 Weeks 1 through 4: Foundation.
Define your Quality Target Product Profile and Critical Quality Attributes with the receiving site. Not at them. With them. Map the stakeholder landscape using the protocol we just covered. Create a detailed tech transfer plan document—this becomes your contract with yourself. And identify which parameters are scale-dependent versus scale-independent.
📅 Weeks 5 through 8: Risk Mitigation.
Conduct a gap assessment. Equipment, methods, training needs. Qualify raw materials at the receiving site—source, vendor approval, comparability. You cannot assume your supplier has the same qualification status at their site. Run scale-down models at the receiving site. Develop a comprehensive sampling plan with statistical power. Train receiving site personnel—and I don't mean train them on SOPs. Train them on the why. Why does this step matter? What happens if it goes wrong? What are the early warning signs?
And here's the critical one: Document tribal knowledge. Capture the undocumented tricks. The environmental nuances. The operator expertise that lives only in people's heads. The way your senior operator knows the culture is stressed before the dissolved oxygen trace shows it. Write that down.
📅 Weeks 9 through 12: Execution Preparation.
Co-author batch records with the receiving site. Not you write, they review. Co-author.
Establish communication protocols—who calls whom when something goes sideways? Define success criteria and go/no-go decision points. Plan for contingencies—if the scale-down model fails, what's plan B?
Go/no-go decision points. You don't proceed to full scale unless:
If any critical gap remains, you stop. You do not proceed to full scale hoping it'll work out. Hope is not a strategy.
Early in my career, I thought I needed to control everything. Write all the protocols. Review all the data. Draft all the reports.
Result? I became the bottleneck. Burned out. And paradoxically, progress slowed.
The turning point came when I got an assistant for admin and protocol and report writing. Suddenly, I had time for the things only I could do. Strategic decisions. Stakeholder relationships. Critical technical judgment calls.
The insight that changed everything: As a leader, focus on the 20% that only you can do. I further honed this as an entrepreneur. You have limited hours and limited attention span. If you spend them on the 80% that someone else could do, you're stealing from the 20% that creates actual value.
Your action item this week: Identify your 80% activities. Then plan to delegate them within 90 days. Not someday. Within 90 days.
You're staring at a tech transfer timeline. Leadership wants aggressive dates. The CDMO is confident but vague. And you're carrying the weight of knowing that if this slips, the entire program slips.
That pressure? It's real. The complexity? Also real.
But here's what's also real. Tech transfer isn't magic. It's not an art. It's building on six essential pillars with discipline and foresight.
You've got the framework now. Technical process understanding—know what's scale-dependent. Analytical comparability—design it upfront. Quality by Design—define your CQAs before the crisis. Stakeholder management—understand what people need. Partner selection—choose the CDMO that challenges you. Strategic build versus buy—focus on competitive advantage.
You've got the 12-week protocol. Foundation, risk mitigation, execution preparation.
And you've got the mindset shift. Master the human element. Understand the physics. Plan systematically. Delegate the 80% that doesn't require your unique expertise.
Your "piece of cake" tech transfer? It can actually be cake. Not because tech transfer got easier. Because you got better at orchestrating complexity.
The timeline's not going to get less aggressive. The stakeholders aren't going to get less demanding. But you now have a system that works regardless.
Go make it happen.
If you liked today’s conversation about scale-up and tech transfer, please tell us by leaving a review. Your review helps scientists like you discover these resources.
For additional bioprocessing tips, visit us at www.smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in the next episode. Until then, let’s continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
If you’re interested in the ideas discussed, here are some of the guests David referenced in this episode.
Episodes 91 - 92: Mass Transfer Secrets: Mastering Bubbles and kLa from Bench to Large-Scale Production with Lars Puiman & Rik Volger
Episodes 79 - 80: Think Before You Build: Holistic Approaches to Biotech Facility Design with Alfredo Martínez Mogarra
Episodes 57 - 58: Crafting a Solid CMC Strategy: Key Factors and Common Pitfalls with Matthias Müllner
Episodes 23 - 24: Strategies for Success: Master CMC Development with Gene Lee
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
Tech transfer in biotech can feel like a high-stakes gamble, balancing regulatory shifts, incomplete data, and mounting stakeholder pressure—all with timelines breathing down your neck.
In this episode of the Smart Biotech Scientist Podcast, David Brühlmann shares hard-earned lessons on the complexities of tech transfer and scale-up in the biotech industry.
Our process development head leaned back in his chair and smiled. "Guys, I have a quick tech transfer to our existing facility. Piece of cake."
Those were his exact words. And I believed him. Why wouldn't I? We had the process nailed. The timeline was tight but doable. The receiving site had done this before.
Except here's what nobody told me: regulatory requirements had evolved. Our process documentation was Swiss cheese. And what I thought was a robust process? It was a house of cards held together by undocumented operator tricks.
Maybe you're staring at a similar situation right now. Timeline pressure mounting. Stakeholders asking for updates you can't confidently give. That nagging feeling that there's something critical you're missing.
You're not wrong to feel that way.
Today, I'm giving you the framework that could've saved our team months of delays and millions in costs. The six-pillar approach that turns tech transfer from a gamble into a managed process.
Here's what we're covering. First, the six essential pillars in every tech transfer—and why missing just one of them puts your project at risk. Second, the technical essentials, specifically why mass transfer physics change everything at scale. Third, the stakeholder strategy that turns resistance into genuine partnership. Fourth, when to build internal capability versus outsource—the decision framework nobody teaches you in grad school. And fifth, real implementation: your 12-week tech transfer preparation protocol.
FDA data shows that over 40% of CMC-related IND issues trace back to manufacturing problems. Not formulation. Not analytics. Manufacturing. And here's the thing—tech transfer is now the number one CDMO differentiation factor. Lonza's data projects that by 2029, 56% of all biologics will be manufactured by CDMOs.
The hidden cost? Poor tech transfer doesn't just delay your program. It questions comparability. It my lead to expensive bridging studies. It hands your competitor the market window you were counting on.
But here's your opportunity. Master this, and you compress timelines while everyone else scrambles to put out fires. You become the person leadership trusts with the critical path.
So let's talk about the six pillars.
Here's the physics challenge you need to tackle. What works brilliantly at 2 liters can fail spectacularly at 2,000 liters. Not because you did something wrong. Because physics changes.
Mass transfer is the big one. Specifically, kLa—oxygen transfer coefficient. Lars Puiman and Rik Volger explained this well on the podcast. Bubble size changes with scale. Residence time changes. Mixing patterns change.
Here's a concrete example. Your 2-liter benchtop bioreactor might have a kLa of 15 to 25 per hour. Your 2000-liter production vessel? You're looking at 8 to 15 per hour. That's roughly a 40 to 60% reduction in oxygen transfer efficiency—and if you're not planning for it, your high-density fed-batch is going to underperform at scale.
Now think about what that means for a high-density fed-batch culture. If your cells are oxygen-limited at production scale but not at bench scale, you're going to see different growth profiles. Different metabolite accumulation. Different product quality.
Your action item here is straightforward but not easy. Map every critical process parameter and ask: is this scale-dependent or scale-independent? Temperature setpoint? Scale-independent. Mixing time? Very scale-dependent. Impeller tip speed? Scale-dependent. pH control strategy? Depends on your system. Can your large-scale bioreactor system supply the oxygen your cell line needs?
Make that list before you commit to a tech transfer timeline.
Here's the blind spot I’ve seen. Teams obsess over the process—feed rates, temperature profiles, aeration strategy. And they completely neglect the sampling plan.
Let me be direct. Analytics isn't separate from tech transfer. It IS tech transfer.
Think about it. How do you prove your process transferred successfully? You measure it. And if your analytical methods aren't validated at the receiving site, or if your sampling plan doesn't have statistical power, you're building conclusions on quicksand.
What you need is side-by-side comparability with real rigor. Full product characterization panel for the final product. And forced degradation studies to demonstrate that your comparability holds up under stress.
This is where most tech transfers actually fail. Not because the process drifted. Because nobody designed a sampling strategy robust enough to detect when it drifted.
Gene Lee said something on the podcast that should be tattooed on every CMC scientist's forehead: "Start CMC planning early—you can't retrofit smart strategy."
Here's the Quality by Design chain: Quality Target Product Profile flows to Critical Quality Attributes, which flow to Critical Process Parameters. If you don't know what quality means for your pr oduct, you literally cannot transfer the process. Because you don't know what to measure and you don't know what to control.
The mistake I see repeatedly? Teams hoping the CDMO will figure it out. They ship over a process description and some batch records and say, "Make it work."
That's not a tech transfer. That's a wish.
Your CDMO will execute your plan. If you don't provide one, they'll improvise. And their improvisation might be scientifically sound and completely wrong for your regulatory strategy.
Define your CQAs before tech transfer. Not during the crisis call after the first batch fails.
I'm going to tell you about the QC guy who taught me the most important tech transfer lesson of my career. And it had absolutely nothing to do with science.
But that's coming in Part 2. Stay tuned for what derails many projects: stakeholder management.
CDMO reality check. Your CDMO partner has deep expertise. They've scaled up hundreds of processes. But they execute YOUR plan.
If you don't have a plan, they will improvise. And that improvisation might be brilliant. It also might be completely misaligned with your regulatory strategy, your competitive timeline, or your quality requirements.
Selection criteria matter more than most people realize. According to Lonza, technology transfer capabilities have become a critical differentiator for successful partnerships and risk mitigation. Technical capability is table stakes. But you also need regulatory track record—have they filed INDs in your modality? And cultural fit—do they ask hard questions, or do they promise "no problem" to everything?
That second one is actually a red flag. The CDMO that promises smooth sailing without probing your process understanding? They're either overconfident or they don't care enough to push back.
You want the partner who challenges your assumptions early. Not the one who surfaces problems after you've committed three months and half a million dollars.
Alfredo Martínez gave us the principle: Think holistically before building—infrastructure is expensive.
And not just expensive in capital. Expensive in time. Expensive in opportunity cost. Expensive in the expertise you need to hire and retain.
I'll give you the full decision framework in Part 2. But here's the preview question: Are you building core competitive advantage or are you building commodity infrastructure?
Because if it's commodity infrastructure, somebody else has already built it better and cheaper.
That's the framework. Six pillars that most people never think about systematically. But knowing the pillars isn't enough. You need the playbook.
Thank you for listening to Part 1. In Part 2, I'm walking you through real implementation: the QC conflict story that changed how I think about stakeholders, the light exposure discovery that taught me to document everything, your 12-week preparation protocol with go/no-go gates, and the build-versus-outsource decision matrix.
If you liked today’s conversation about scale-up and tech transfer, please tell us by leaving a review. Your review helps scientists like you discover these resources.
For additional bioprocessing tips, visit us at www.smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in the next episode. Until then, let’s continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
If you’re interested in the ideas discussed, here are some of the guests David referenced in this episode.
Episodes 91 - 92: Mass Transfer Secrets: Mastering Bubbles and kLa from Bench to Large-Scale Production with Lars Puiman & Rik Volger
Episodes 79 - 80: Think Before You Build: Holistic Approaches to Biotech Facility Design with Alfredo Martínez Mogarra
Episodes 57 - 58: Crafting a Solid CMC Strategy: Key Factors and Common Pitfalls with Matthias Müllner
Episodes 23 - 24: Strategies for Success: Master CMC Development with Gene Lee
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
What if the solution to cell therapy’s biggest cold-chain challenge comes from the biology of Arctic fish?
Cryopreservation is the linchpin of cell and gene therapy logistics—and for years, dimethyl sulfoxide (DMSO) has been the industry’s reluctant standard. DMSO keeps cells alive in the freezer, but at a cost: regulatory headaches, damaged cells, patient side effects, and complicated workflows. So what if an antifreeze-inspired innovation could finally retire DMSO for good?
This conversation features Steve Oh, a leader in advanced bioprocessing, whose career has placed him at the intersection of stem cell biology, process engineering, and clinical translation. Steve Oh joins David Brühlmann to share how a next-generation cryopreservation solution drawing from nature’s antifreeze proteins—lets cells survive, thrive, and simplify manufacturing from the bench to the clinic.
It is really a simple plug-and-play solution. It's been made to GMP grade. It has a Drug Master File. So it's simply just getting a bottle and then using it at the same concentration as you would currently use with DMSO at 5% or 10%. So most cells would just transition from DMSO to the solution without any problem.
David Brühlmann [00:00:23]:
Arctic fish survive in waters that would freeze most life solid. That biological insight, translated into synthetic peptide chemistry, may be exactly what cell therapy manufacturing has been waiting for. In part 1, Steve Oh walked us through the DMSO problem in depth: the toxicity, the cellular damage, the regulatory pressure. Now we get to solutions: from cryopreservation performance data to manufacturing logistics to what a transition actually requires. This is where it gets practical.
Can you give us some examples, Steve, of how this innovative approach helps cells survive better and maintain their viability and function?
Steve Oh [00:02:23]:
We have a presentation on various cell types, both T cells and MSCs. So we have an example where fresh pan-T cells isolated from donor apheresis were stored at 10 million cells per mL, and then they were frozen down for 40 days with the XT5 solution. And post-recovery, they were able to proliferate as well as the fresh product.
Another example was when we preserved T cells from two CDMO partners. The XT-Thrive® frozen product had almost equivalent—about 80%—secretion of IL-2, similar to fresh cells, whereas the DMSO-containing product was around 60%. And in terms of the immunophenotype, they expressed CD4/CD8 markers.
In terms of cytotoxic function, four DMSO-containing competitor products were tested against the XT-TRI solution at effector-to-target ratios of 1:1 and 0.3:1. So XT-Thrive® had the best performance in terms of cell-killing function over the other three DMSO-containing products. In fact, one product had no killing efficacy at all at the lowest effector-to-target ratio.
A third example is when CD4 and CD8 T cells were frozen for 7 days and then thawed, and nucleofection of the CAR-T gene was performed. The efficacy was about 80% for XT-Thrive® versus 60% for the CryoStor CS10 cryopreservation solution. These are the T-cell examples, where we’ve seen much better performance than CS10.
In terms of MSCs, we looked at holding the cells in solution for 24 hours prior to freezing. We found that the viability of the cells held in XT-Thrive® remained at about 90%, but DMSO dropped progressively—within 4 hours to 85%, and then overnight down to 60%.
Then when we froze and thawed them, recovery of viability was about 90% for XT-Thrive® and about 85% for CryoStor CS10, and it continued to drop to about 60% over 8 hours, whereas XT-Thrive® was maintained around 90% in MSC cultures.
All these experiments were done under both serum-containing and serum-free conditions. Many products are moving toward defined serum-free conditions, and cells tend to be more sensitive without the serum background. So we've seen this performance to be consistent irrespective of serum-free or serum-containing conditions.
And finally, when we put these cells back into culture on microcarriers—which is a scalable method for cell production—we saw immediate recovery and growth of the cultures post-thaw with XT-Thrive®. But with DMSO, there was a 4-day lag followed by only marginal growth. So overall, we observed about a 2.5-fold increase in cell yield post-thaw.
David Brühlmann [00:05:20]:
To what extent, Steve, were these stark differences between XT-Thrive® and DMSO due to ice crystal formation and differences, I'd say, in mechanism?
Steve Oh [00:05:32]:
I think that is the key benefit of this approach. We have seen in microscopic studies that ice crystals are relatively large in water, and with both antifreeze proteins and the XT-Thrive® product, the crystal size is reduced to about 10–50% of that seen in water. So most of the damage actually occurs during thawing, when these crystals can cause mechanical damage to the cell membrane if thawing is not rapid enough.
David Brühlmann [00:06:01]:
Let's shift gears here, Steve. So we have seen the stark differences between DMSO and this novel solution. We have also talked about the main challenges linked to DMSO. Now, another question we need to tackle is: we have a new product that seems to work well, but how does this affect established workflows—washing, freezing and thawing, temperature? Can you give us a picture there? What changes for the person doing the work in the lab?
Steve Oh [00:06:33]:
So one of the first things we did was to run a hold-time experiment over 24 hours. We learned in the early days that once you put cells in DMSO, you have to process them quickly—within 4 hours, but ideally between 30 minutes to 2 hours.
That’s fine when you're using small vials of cells that you can aliquot at 1 mL each. But once you're processing, say, 100 mL bags—or even a 1 L batch that you then aliquot into 100 mL bags—that workflow becomes very rushed.
So that's why we did the real-time hold experiment over 24 hours, to ensure that cells could be processed over a full day and to assess whether viability would be affected. And sure enough, we found that viability was maintained over the 24 hours, which makes processing much more convenient.
On the backend, there were also tests where the solution was injected into animals at 100× the concentration used for cryopreservation, and there was no toxicity observed. So there isn’t the same requirement to wash away the DMSO-containing solution—you could inject it as is post-thaw. It behaves almost like water—not exactly, but it is essentially non-toxic.
So you can inject it into the patient without that extra wash step. Again, this reduces the risk of contamination due to manual washing and centrifugation steps, and significantly simplifies the workflow from both a manufacturing and point-of-care delivery perspective.
David Brühlmann [00:08:01]:
How does this simplified workflow without an additional wash step after thawing affect—or facilitate—the distribution of these therapies to remote locations? Because that's one of the challenges we are still facing in cell and gene therapy: how do we bring these therapies from the manufacturing site—whether it's a hospital or a company—to the patient?
Steve Oh [00:08:27]:
So we have tested the solutions at 4°C, −80°C, and −196°C. Across all these temperatures, cell viability and performance are as good as or better than with DMSO. So in autologous therapy, you can hold the cells at 4°C for as long as needed for transportation. In manufacturing, you can create master cell banks and working cell banks at −80°C to −196°C. And for allogeneic therapy, you can handle much larger volumes, enable long-term preservation over years, and then thaw the cells for localized treatment.
One of the benefits of being able to operate at 4°C is that, as I’ll mention later, you can transport certain cell types—like organoids or even organs—for 3 to 5 days at cold temperatures without freezing. So they never form ice crystals. You can transport them across the country, and the organs are still functional after warming. So again, it highlights the versatility of the solution compared to DMSO.
David Brühlmann [00:09:39]:
So am I hearing correctly that this product cannot only be used for single cells, but for organoids and potentially even in tissue engineering or some other areas?
Steve Oh [00:09:50]:
Yeah, that's right. We don't have published data yet, but there is accumulated evidence that heart islets are functioning in XT-Thrive®, and the XT -Novo data for larger human organs will be coming up. So at ISCT, in May 2026 in Dublin, we should have more data on these different cell types, including organoids.
And organoids have their own challenges because they are fairly large structures—up to 5–10 millimeters in size—and they need to be kept cold or produced fresh because there’s traditionally no good way to freeze them down or hold them at cold temperatures. And we think we have some good data to show for that.
David Brühlmann [00:10:31]:
Let's assume that my team and I have developed a T-cell process using DMSO, and now I'm listening to this podcast and I learn about this much better product to freeze and thaw cells. How easily can I switch over to this new product?
Steve Oh [00:10:49]:
I think it is really a simple plug-and-play solution. It's been made to GMP grade. It has Drug Master Files. So it's simply just getting a bottle and then using it at the same concentration as you would currently use with DMSO at 5% or 10%. So most cells would just transition from DMSO to the solution without any problem.
In terms of the manufacturing facilities, there are sites in San Francisco and Vienna, and clients are welcome to visit them to audit the manufacturing process. We are also talking to some major distributors in the US and Japan to extend the global reach.
David Brühlmann [00:11:28]:
Let's zoom out and look at the broader cell and gene therapy picture. There's a lot of innovation happening. Beyond DMSO, what are some impactful areas you're seeing or some promising areas that you think are worthwhile highlighting?
Steve Oh [00:11:48]:
Related to cryopreservation or beyond cryopreservation?
David Brühlmann [00:11:51]:
In general, beyond cryopreservation.
Steve Oh [00:11:54]:
I think the biggest challenge with stem cell–based therapies is the long differentiation time from the starting material to the final product. That's one challenge.
The second is maintaining the consistency and purity of the target population, whether it be neural stem cells for Parkinson’s disease trials or cardiomyocytes for heart disease. So this remains an ongoing challenge.
The third challenge is achieving this at a low cost of goods. Process optimization is key here, just as in biologics manufacturing, because many protocols rely on numerous combinations of growth factors and small molecules to generate the final cell type over many weeks.
So I think the cost of goods, due to the complexity of the process, will determine whether we achieve widespread adoption of these cell therapies.
David Brühlmann [00:12:43]:
What technology innovations have you seen that you think could solve one of these challenges?
Steve Oh [00:12:50]:
I have seen some data from a company called Accelerated Biosciences, using a source of cells called trophoblast stem cells. They had data showing that with a one-day induction, they could produce a cell type that secretes dopamine. And when injected into mouse models of Parkinson’s disease, they were able to recover function.
But that company has been facing challenges raising funds to move into a Phase 1 clinical trial. So if a transformative technology like that can generate a functional cell type—similar to a dopaminergic neuron—in just one day, that would be fantastic in terms of process efficiency, manufacturing, and cost of goods. But it has not yet reached Phase 1 clinical trials.
David Brühlmann [00:13:34]:
Such an innovation would move the needle forward, but it's a pity to see disruptive technology stall because of a lack of funding. I mean, it looks very promising. Even later, perhaps you might run into some technical issues—who knows—but it is at least worthwhile pursuing the development and seeing whether it will work in a commercial setting.
Steve Oh [00:13:58]:
If you had the opportunity, it might be good to get a venture capitalist or someone from the investment side who can talk about what needs to be addressed to unlock funding.
David Brühlmann [00:14:08]:
Yeah, absolutely. And if one of the venture capitalists is listening, this is an opportunity. We are in the money game, yes, but I think we should also have a broader perspective. That's at least my personal view of the industry.
We should pursue technologies that don’t have an immediate return on investment because, at the end of the day, we’re in it to treat patients. So I think this is something that, if I may say, our industry could further develop—the social dimension of innovation—not only the immediate ROI.
Well, this has been great, Steve. Before we wrap up, what burning question haven't I asked that you are eager to share with our biotech community?
Steve Oh [00:14:52]:
I think in terms of disruptive technology, XT-Thrive®, this single cryopreservation solution, will contribute significantly to cell-based therapies because it has zero toxicity. It preserves cells and tissues in a much better state than traditional DMSO across many different cell types. Recovery of cells post-storage is much higher—more viable, functional, and healthier.
It doesn't need a wash step, and it doesn't cause irritation or edema at the site of injection, which makes it easier to administer to patients. So I think this will be one of the key solutions in cell therapies, impacting both current T-cell–based therapies and future stem cell therapies. Thank you for the opportunity to speak about this topic.
David Brühlmann [00:15:38]:
Absolutely. It's a pleasure. And if there is only one thing you want our listeners to walk away with, what would it be?
Steve Oh [00:15:46]:
If you're looking for a cryopreservation solution, just reach out.
David Brühlmann [00:15:59]:
Okay. So this leads me to the final question, Steve. Where can people get ahold of you and this product?
Steve Oh [00:16:05]:
So I'm on LinkedIn, and my email—if you can share it—is skwoh.so@gmail.com.
David Brühlmann [00:16:15]:
There you have it, Smart Biotech Scientists. You will find the link in the show notes. Reach out to Steve and his team. And thank you, Steve, so much for being on the show today and sharing both the challenges and solutions in cryopreservation.
Steve Oh [00:16:30]:
Thank you so much. Thanks, David.
David Brühlmann [00:16:34]:
From Arctic antifreeze proteins to clinical-grade cryopreservation, Steve Oh has shown us that the DMSO era may finally have a credible successor. The performance data is compelling, and the manufacturing implications are significant. If you're navigating these challenges in your own program, I hope this conversation gave you a clearer path forward.
And if it did, please take a moment to leave a review on Apple Podcasts or your favorite platform and share it with a colleague. For additional bioprocessing tips, visit www.smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in our next episode. Until then, let's continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Steve Oh
Steve Oh is a seasoned biotech scientist and advisor with a career defined by innovation and resilience. After more than two decades at A*STAR’s Bioprocessing Technology Institute, where he developed cutting-edge stem cell and bioprocessing technologies, he transitioned into entrepreneurship and advisory roles across the global biotech ecosystem.
Despite early challenges in launching spin-off ventures, he leveraged those experiences to guide companies in areas such as viral vector manufacturing, cultured meat, and advanced cell therapies. He continues to shape the future of biotechnology through research collaborations, advisory work, and mentorship.
Connect with Steve Oh on LinkedIn.
If you’re interested in this topic, check out these episodes, where we explore how Minnesota’s frozen forests inspired a new wave of biotech innovation, transforming how life-saving cells are frozen, stored, and shipped.
Episodes 161 - 162: How to Achieve 85%+ Cell Recovery Without DMSO's Toxic Side Effects with Jeffrey Allen
This is Steve’s second appearance on the podcast. You can also catch his earlier conversation with David, where they explored the challenges and opportunities of cell and gene therapy.
Episodes 11 - 12: From Lab to Patient: Steve Oh’s Guide to Mastering Cell Therapy Process Development.
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
Sixty years after its arrival, one molecule still dominates cell cryopreservation: DMSO. It’s unmatched in its ability to get cells through the freeze–thaw cycle alive, and its clinical track record is extensive. Yet beneath the surface of every viable vial lurk toxicity risks and a legacy of side effects that have regulators and innovators hungry for change.
Why hasn’t DMSO been dethroned—and what’s finally threatening its reign?
Joining David Brühlmann is Steve Oh, whose 22 years at Singapore’s A*STAR produced 43 patents, breakthroughs in stem cell microcarrier technologies, and hard-won expertise on the toughest bottlenecks in bioprocessing. Steve Oh isn’t just theorizing about better cryoprotectants—he’s lived the old problems and is now advising startup trailblazers trying to solve them for good.
DMSO has been the gold standard because of its unique chemical properties and extensive clinical track record, making it difficult to fully replace. But that's a 60-year-old product, and a lot of things have changed since then. So some of the properties are as follows: physicochemical efficiency. It has rapid membrane permeability, and it enters the cells and equilibrates with the intracellular environment faster than other penetrating agents like glycerol. Water displacement: it forms hydrogen bonds with water about 30% stronger than between water molecules themselves, thereby preventing the formation of intracellular ice crystals.
David Brühlmann [00:00:42]:
For 60 years, one molecule has defined cell cryopreservation—effective enough to become the universal standard, yet problematic enough that the FDA attempted to ban it twice. My guest today, Steve Oh, spent 22 years at Singapore's A*STAR, invented stem cell microcarrier technologies, CRISPR activation, and a lot more. He holds 43 patents and has seen this problem from every angle. Steve brings hard-won wisdom to one of bioprocessing’s most persistent challenges. Why has DMSO survived this long, and what finally threatens its reign? Let's find out!
Welcome, Steve. It's good to have you on today.
Steve Oh [00:02:50]:
Thank you, David, for the invitation.
David Brühlmann [00:02:52]:
Steve, share something that you believe about bioprocess development that has made the most impact.
Steve Oh [00:02:59]:
Okay, love to. I think there are 3 that I can think of right now. The development of the AMBR system for small-scale volume optimization that has made a lot of impact in the biologics industry. The development of high-intensity perfusion cultures that has reduced the volume and the footprint of bioreactors for generating high titers of proteins, recombinant antibodies. And I think one that's coming in the future is the use of digital twins to reduce the number of experiments and then focus on the key experiments. I believe you're going to be talking about that in the future, right?
David Brühlmann [00:03:38]:
Yes, absolutely. And we have already covered this topic—digital twins and hybrid modeling—a few times on previous episodes. So if you're interested in that, Smart Biotech Scientists, go back and listen to these episodes. It's a huge pleasure to have you back on, Steve. For those listeners who have not had a chance to listen to our interview we did, I think a couple of years back, take us back to the beginning. What sparked your passion for biotech and cell therapy, and what pivotal moments during your long career shaped your path to becoming a leader in stem cell bioprocessing solutions?
Steve Oh [00:04:17]:
I think back in the '90s, when the production of antibodies was challenging, I had the opportunity to complete my PhD and get into learning about the use of bioreactors for manufacturing cells, which at that time was a big challenge. People were doing bacterial fermentation but not animal cells. So that was the first pivotal moment that gave me the training and the opportunity to get into this field.
And then around 2001, post the discovery of pluripotent embryonic stem cells, again that was a challenge—how to produce stem cells at scale in bioreactors. We built a small team to look at growing these cells, which were very dependent on support cells—feeder cells—and Matrigel, all kind of undefined conditions. And finally, we found a way to switch them to grow on microcarriers in bioreactors. So those were the two big opportunities I had to make an impact in bioprocessing and come up with new solutions to scale.
David Brühlmann [00:05:22]:
And what were some pivotal moments you experienced during your long years at A*STAR that finally led you to also take a leap and pursue entrepreneurial endeavors?
Steve Oh [00:05:32]:
After the discovery of microcarriers for manufacturing stem cells, I did try my hand at forming a spin-off company, but the challenge was raising cash to build a CDMO-type business model and then finding a CEO. So my entrepreneurial skills were not that strong, and we didn't succeed. I'm glad to see that there are companies out there now that are able to make that impact. Still, no products made from bioreactors yet, but people are trying.
David Brühlmann [00:06:03]:
Wow, that's fantastic. You hold a lot of patents—exactly, if I'm not mistaken, 43 patents across microcarrier technologies, serum-free media, and CRISPR activation. So you could have focused on many different areas. What drew you to cryopreservation as one of your key advisory roles? And tell us also what made you believe that this was an area ripe for innovation.
Steve Oh [00:06:31]:
It was in collaboration with a company called X-Therma back in 2015, I believe—or maybe a bit later—where I saw that they had this amazing solution that could transport whole hearts across the country over 3 days. And we had seen there were challenges with DMSO for cryopreservation of pluripotent stem cells and the first challenging differentiated cell type—neural stem cells. So I approached the CEO, Xiaoxi, and looked at potentially testing out that solution for stem cell applications. And I realized that in the final cell therapy, you wouldn't be giving fresh cells—you'd have to freeze them down and use the thawed cells for patient injection.
So we needed something that would be robust and give potent cell properties as close to fresh cells as possible. And really, nobody at that time was looking at the replacement of DMSO, the standard solution. So that's why I felt that there was a blue ocean opportunity to collaborate with them. And then once I left A*STAR about 4 years ago, I sought the opportunity to be a scientific advisor. That's why I'm working with X-Therma on educating the field in alternatives to DMSO.
David Brühlmann [00:07:48]:
Let's start with the fundamentals, Steve, because cryopreservation—or shall I say the preservation of cells—is a big, big topic, not only in cell therapy, but I'd say in various areas of biologics. Help our listeners understand what are the main challenges scientists face when preserving cells, freezing cells, and why has DMSO remained the gold standard despite its limitations for many decades?
Steve Oh [00:08:17]:
So DMSO has been the gold standard because of its unique chemical properties and extensive clinical track record, making it difficult to fully replace. But that's a 60-year-old product, and a lot of things have changed since then. So some of the properties are as follows: physicochemical efficiency. It has rapid membrane permeability, and it enters the cells and equilibrates with the intracellular environment faster than other penetrating agents like glycerol.
Water displacement: it forms hydrogen bonds with water that are about 30% stronger than between water molecules themselves, thereby preventing the formation of intracellular ice crystals. It's versatile. In the pre-cell therapy days, hematopoietic stem cells (HSCs) were mostly the cell type used in cryopreservation—blood products, some immune cells, and mesenchymal stromal cells (MSCs).
And the HSCs have been used in clinical and regulatory environments—so lots of stem cell transplants. Its side effects are documented and manageable within existing medical protocols, such as maximum daily dose limits, typically 1 gram per kilogram of patient weight. There are standardized protocols and workflows built around the 5–10% DMSO formulation. Transitioning to alternatives requires extensive and costly validation to ensure that therapeutic efficacy is not affected.
Then the practical and economic advantages include low cost, high stability, long shelf life at low temperatures, and wide availability in high-purity grades—such as United States Pharmacopeia (USP) grade for clinical use. And it's easy to use in controlled-rate freezers at about −1°C per minute, so fairly simple to implement. So that's the reason why it has been in use for 60 years.
David Brühlmann [00:10:14]:
What I'm hearing here, Steve, is that DMSO has a lot of advantages, and that's the reason why it has been used for so long. Isn't it interesting that the FDA has tried to ban DMSO twice? So what are the specific issues with the toxicity of DMSO, and what are some other aspects that make its use problematic?
Steve Oh [00:10:39]:
One example was back in 1965—there was a ban on human testing because of safety alarms regarding lens (eye) toxicity in animals, and then a sudden death of an Irish woman after topical use. So these early concerns established regulatory wariness that persists today.
Now, for modern cell therapies, there are new issues that we've never had—the challenges of the variety of cell types now being used. This includes cellular dysfunction and loss of potency. For T cells, at concentrations as low as 0.25–1%, DMSO inhibits CD4-positive T cell activation, proliferation, and cytokine production such as IL-2, IL-4, and IL-17A. It downregulates genes in early signaling and T-cell receptor pathways.
Then for NK cells, DMSO is associated with altered expression of natural killer cell markers and diminished effector functions. For stem cells, DMSO is known as a differentiation inducer, so it can downregulate pluripotency factors like OCT4 and NANOG at concentrations as low as 0.125%, potentially biasing their therapeutic identity before they reach the patient.
In terms of physical and structural damage, DMSO induces pore formation in cell membranes and can disrupt the cytoskeleton by dehydrating lipids and interacting with proteins. In terms of mitochondrial and metabolic stress, it can compromise mitochondrial respiration, induce oxidative stress, and trigger apoptosis through caspase-9 and caspase-3 activation.
And then in patients, DMSO toxicity significantly increases dose-dependent cell damage and adverse reactions. Clinical risks include cardiovascular issues, severe nausea, neurological symptoms, and allergic reactions, which necessitate rapid removal or lower concentrations.
David Brühlmann [00:12:42]:
Let me reframe this because you're making an excellent point here, Steve. I have worked in biologics for most of my career, and DMSO is used to freeze cell banks. And pretty much the only parameter many teams were interested in is viability when you thaw your cells.
But now what I'm hearing is that in cell therapy, we are playing a completely different ball game. Because we're not just cultivating cells in a bioreactor—we are using these cells to treat patients. So we have to look much more carefully at what's going on at the genetic level, at the transcriptomics level, and at the metabolic level. So we have a plethora of aspects to watch out for.
Steve Oh [00:13:28]:
Correct. Because the cells are the functional entities, just having viable cells is not sufficient. You have to have the cells be able to perform the function that they were intended for, as they would when fresh.
David Brühlmann [00:13:40]:
Can we look into the cells a bit? What's happening when you're using DMSO and you're freezing and then thawing the cells? What exactly happens at the microscopic level? What are these changes that affect the genetic stability, the transcriptomics, or the metabolism of these cells?
Steve Oh [00:14:01]:
Some of the toxicity issues in cryopreservation are that when cells are exposed to DMSO at temperatures above 4°C during thawing, it can disrupt the cellular membrane, cause mitochondrial damage, and lead to the production of reactive oxygen species. So this is cumulative, and it can start to create all those metabolic damages that I mentioned earlier.
On top of that, exposure to DMSO can lead to undesirable phenotypic changes in stem cells due to alterations in DNA methylation and histone-modifying enzymes that can open up the DNA for priming towards differentiation or close it down such that they can't differentiate.
Then there is the time- and dose-dependent risk. Toxicity is directly related to concentration and exposure time. Typically, DMSO is used in the 5–10% range, but even up to 40% DMSO has been used, and this completely destroys hematopoietic stem cell viability. And then, as I mentioned earlier, when residual DMSO is infused into patients, you can have nausea, vomiting, cardiovascular events like bradycardia and arrhythmia, neurological symptoms like seizures and dizziness, and allergic reactions.
And finally, in terms of manipulating the DMSO itself, because of these toxicity issues, it needs to be washed away to remove residuals and reduce the overall volume to decrease the dose. This can lead to potential opportunities for contamination of the product by having to do this additional step.
David Brühlmann [00:15:38]:
To what extent can these detrimental effects happen even though the viability looks okay?
Steve Oh [00:15:46]:
So even at low concentrations post-wash, the types of disruptions that can happen are as follows: Alterations in DNA methylation: DMSO disrupts the balance between the “writers” and “erasers” of DNA methylation, leading to widespread genomic instability.
The major risk in preserving stem cells and related products is that we don’t fully understand how these methylation changes will affect the long-term behavior of the cell product.
David Brühlmann [00:16:48]:
Given what we've discussed so far, Steve, what are the options we have at our disposal as scientists? Because we could use DMSO, but there are some detrimental effects you just mentioned, and we have to be aware of that. And there are now some alternative products. So what are these products scientists listening can use?
Steve Oh [00:17:10]:
So there are a couple of approaches that have been taken. Companies have looked at trying to reformulate alternatives to DMSO using other small molecules like glycerol and additional cryoprotective agents. These are complex formulations that have to be optimized for each cell type.
Then there are companies like X-Therma, which have come up with antifreeze peptide mimics—essentially single-molecule solutions that aim to do the same thing as DMSO but with processing benefits and without the significant toxicity seen with DMSO. So those are the two approaches: either complex formulations or a completely new entity to replace DMSO.
David Brühlmann [00:17:52]:
And looking at X-Therma, I saw that you took inspiration from antifreeze proteins found in Arctic fish. How did this come about? Explain how these specifically protect the cells from freezing damage.
Steve Oh [00:18:06]:
So these antifreeze proteins improve cryopreservation by binding to ice crystals, inhibiting their growth and recrystallization, and reducing damage to cells at sub-zero temperatures. They were derived from cold-adapted organisms and create a thermal hysteresis gap that lowers the freezing point without affecting the melting point, thereby protecting biological samples and enhancing survival rates.
Essentially, how it works is that they cluster around water molecules and prevent the rapid growth of crystals. Because of these much smaller crystals, they don’t damage the cellular structure either when frozen or during thawing. They can return to the liquid state more smoothly than large crystals would, even without traditional cryoprotectants.
David Brühlmann [00:18:55]:
We've just unpacked why DMSO has persisted for six decades despite its well-documented limitations—and why that persistence has real consequences for your cells, your patients, and your manufacturing process.
In part 2, Steve Oh takes us into the solutions—the science behind next-generation cryoprotectants, the data that's turning heads, and what a DMSO-free workflow actually looks like in practice.
If this episode added value, please leave a review on Apple Podcasts or your preferred platform. This enables more scientists like you to discover the show. Thank you for tuning in today—see you next time.
For additional bioprocessing tips, visit us at www.smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in the next episode. Until then, let’s continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Steve Oh
Steve Oh is a biotechnology leader with over 35 years of international experience spanning academia and industry. He spent 22 years at A*STAR in Singapore as an Institute Professor at the Bioprocessing Technology Institute, where he pioneered innovations in stem cell bioprocessing, including microcarrier systems, serum-free media, and gene activation technologies.
He holds 43 patents, has published over 150 scientific papers, and has led more than $34 million in research funding. Today, Steve serves as a scientific advisor to multiple global biotech companies, supporting advances in gene therapy, cryopreservation, and cell manufacturing.
Connect with Steve Oh on LinkedIn.
If you’re interested in this topic, check out these episodes, where we explore how Minnesota’s frozen forests inspired a new wave of biotech innovation, transforming how life-saving cells are frozen, stored, and shipped.
Episodes 161 - 162: How to Achieve 85%+ Cell Recovery Without DMSO's Toxic Side Effects with Jeffrey Allen
This is Steve’s second appearance on the podcast. You can also catch his earlier conversation with David, where they explored the challenges and opportunities of cell and gene therapy.
Episodes 11 - 12: From Lab to Patient: Steve Oh’s Guide to Mastering Cell Therapy Process Development.
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
For decades, contract development and manufacturing organizations (CDMOs) have grown by building bigger stainless-steel facilities and squeezing ever-tighter margins. But as global overcapacity bites, price wars with Asia intensify, and big pharma pulls production back in-house, the rules of the game are shifting—and standing still might just put you out of business.
This episode, David Brühlmann is joined by Juergen Mairhofer, CEO of enGenes Biotech GmbH, who’s built a career—and a company—around challenging bioprocessing orthodoxy. From developing E. coli strains for single-pot antivenom antibodies to helping major players vertically integrate their supply chains, Juergen Mairhofer’s perspective spans the laboratory, the boardroom, and the demands of a biomanufacturing landscape in flux.
I think the current new Five-Year Plan has been putting bioprocessing at the top next to semiconductors. I think they are going to pull out the same business model as they have been using for the automotive industry, steel industry, and photovoltaics. I think that we will see a replication of that for the bioprocessing industry, and I think the only way out here is to innovate.
And I think also the Chinese industry has understood that they need innovation to become more profitable because currently they are extracting a lot of revenue from Europe and the United States, but they are having a hard time becoming profitable because I think currently they have just been replicating what the industry has been doing over the last 20 years in Europe and the US.
David Brühlmann [00:00:50]:
Welcome back to Part 2 of our conversation with Juergen Mairhofer, who is the CEO of enGenes Biotech. In Part 1, we explored the science behind continuous microbial manufacturing and what makes E. coli such a powerful production platform.
Now we zoom out. In a world of CDMO overcapacity, margin pressure, and shifting geopolitics, does advanced bioprocessing actually become a competitive weapon? And what does it take to build a biotech company from the ground up? Let's find out.
I would come back now to your comments where you said we must innovate. That's a very important point because we live in an industry where we have seen a lot of changes.
And you also said, for instance, synthetic biology — a lot of things have happened since you started. To what extent can the continuous processing you have developed be a competitive advantage, but also a way to lead the way in this evolving industry and finally secure the business and also become an attractive CDMO?
Juergen Mairhofer [00:03:08]:
I think what I can say here is that if you wait for the technology to be completely mature, you will wait for your competitor to pass you. I think this is the point. I see a lot of skepticism when I talk to people. One of the arguments is sometimes: We haven't done that in the past — why should we do that in the future? It's so complicated. And there are all these regulatory aspects that we have to overcome. But at the same time, we also know that the business model in the CDMO space that we are currently seeing cannot go on like it used to.
I think this model is somehow broken, and I think there will be a lot of consolidation in the upcoming months and years. Because in Europe, most of the CDMOs are below €100 million in revenue, so they will have a hard time staying alive at some point. And there is also a lot of pressure from Asia, especially from China. I think the current new Five-Year Plan has been putting bioprocessing at the top next to semiconductors. I think they are going to pull out the same business model they have been using for the automotive industry, steel industry, and photovoltaics.
I think we will see a replication of that model for the bioprocessing industry. And I think the only way out here is to innovate. And I think the Chinese industry has also understood that they need innovation to become more profitable. Because currently they are extracting a lot of revenue from Europe and the United States, but they are having a hard time becoming profitable. I think this is because they have been replicating what the industry has been doing for the last 20 years in Europe and the US.
So they are working with outdated processes, the same outdated processes that US and European CDMOs are still working with. And they have realized that they have to innovate their way out. I think we have to understand that also in Europe and the US the only way forward is innovation, because through innovation we can overcome the cost advantage that countries have where energy and labor are cheaper.
With that understanding, I think the only way forward is to be as innovative as possible, while at the same time trying to overcome the regulatory hurdles as quickly as possible. This will probably not be an easy task, but I think it is a task that is worth working on.
David Brühlmann [00:05:49]:
So what I'm hearing, Juergen, is that the way to stay competitive would be on the technology side, on the bioprocess side, not necessarily on the cost side or the geography, because it's very difficult to compete with that and it's a race to the bottom.
So I'm just trying to wrap my mind around that because we hear about overcapacity in CDMOs, we hear about intense price pressure, and there are a lot of things moving right now. And there are not so many CDMOs that have continuous capacity, for instance. So help us understand how this technological innovation can create a competitive advantage, especially for European or American CDMOs, where the cost of labor is much higher.
Juergen Mairhofer [00:06:36]:
As I said, I think the only solution is to innovate ourselves out of this situation, rather than investing in outdated approaches and trying to extract the last euro or dollar from large-scale stainless steel facilities using outdated technology that doesn't bring any advantage to the customer. Because if you just sell capacity, you are not doing anyone any good. I think this is maybe the major problem we are currently seeing.
By being at the forefront of innovation, you can attract more customers and become more successful. But you have to take some risks. You have to invest in implementing new technologies. You also have to work on a change in mindset, because thinking in terms of a continuous process is not an easy task. I have seen this in my own organization. People have to learn it. But once this learning is accomplished, you unlock many things, because people start to think in a completely different way and become capable of solving problems with less complexity.
That's why I would say: don't be afraid. Push forward into this new landscape and try to adapt before it's too late. Start with a pilot project. Maybe don't start with your most important product, but with a project where you can learn. Find partners like enGenes who master the technology and can enable knowledge transfer, and start now. Because the companies that master continuous processing in the coming years will be the ones that stay competitive. That is what I can say here.
David Brühlmann [00:08:24]:
To what extent, Juergen, will continuous manufacturing become the industry standard in the future?
Juergen Mairhofer [00:08:31]:
I think we will be living in a parallel universe for the next decade, I would assume. I mean, I don't have to tell you what has been built in the past around us. People have been building large-scale stainless steel facilities for CHO, for example, and I think they won't go away. They will stay with us for a long time until they are fully depreciated and the products are probably shifted somewhere else. So they will stay and they will be reutilized.
At the same time, we will see small-footprint continuous manufacturing coming up. So there will be a parallel universe that we have to live and work with. But I think in the long-term future, we will see more and more continuous processes arising on the horizon. Because if we can master the complexity, we unlock so many cost savings and so much increase in productivity that it is worth pursuing that path.
David Brühlmann [00:09:27]:
In this last part of our conversation, Juergen, I would like to talk about your experience and learnings as a company leader. What advice would you give to brilliant scientists who are considering, like yourself, spinning off their technology into a company? What do they need to know about that science alone won't teach them?
Juergen Mairhofer [00:09:49]:
That's a very good question. If you think about it, the honest answer is that your technology doesn't sell itself, no matter how good it is. I think technology excellence is necessary — this is the most important point — but it is not sufficient on its own. The best technology often loses to better-marketed technology. This is something we also had to learn the hard way. There are always people who scream louder, although they don't have superior technology. At the end of the day, they get the financing.
You also have to think from a customer perspective, not just from a scientific one. I think this is a difficult lesson for someone coming from an academic mindset, where you always think: My solution is so brilliant — why don't people care about it? So you really have to try to remove your ego from that perspective.
Another thing I want to mention is that cash is like oxygen. If you run out of cash, it's game over. So this is also something you always have to consider. We have been building the company on revenue, so we always try to onboard new projects. Another point that is relevant: it's not the hard times that are the focus point. You can go through hard times — and you have to — but you have to make the right decisions during the good times. I think this is something people — including me — often forget.
You run through hard times, then you enter good times again, and you think: Okay, let's breathe again. But this is exactly the tipping point where you have to say: Now I have to make the right decisions. And last but not least, I would say the team is everything. I remember writing a quote in my PhD thesis from Joe Strummer, the frontman of The Clash, saying: “Without people, you are nothing.” I think this is one of the most valid quotes for building a company. You can be a brilliant mind as a CEO, but if you don't have a team that is playing the same ball game, you are lost. So focus on the team and treat your people well.
David Brühlmann [00:11:59]:
Yeah, excellent. That's really good advice. Thank you for sharing your experience. Before we wrap up, Juergen, what burning question haven't I asked that you're eager to share with our biotech community?
Juergen Mairhofer [00:12:12]:
I think we could quickly speak about what shifts in the bioprocessing landscape have surprised me most. My answer would be that big pharma is trying to vertically integrate again. When I founded enGenes 12 years ago, the narrative was clear: big pharma outsourced and CDMOs were growing. But I think this is starting to fundamentally reverse. If you think about companies like Pfizer, Eli Lilly and Company, and Novo Nordisk, they are building their own capabilities at massive scale. In-house production is growing again, and the compound annual growth rate is around 10%. Big companies have understood that manufacturing is a strategic asset, not just a cost center. I think this is something they have learned during the last couple of years.
I was just talking to colleagues who came back from a cell and gene therapy conference in the US, and they were saying that big pharma companies have acquired a lot of small innovative companies and are now looking to vertically integrate the supply chain again. When you think about Adeno‑associated virus (AAV) manufacturing, for example, people had been outsourcing the production of raw materials like plasmid DNA. Now they are looking to vertically integrate that again, because these raw materials have been sold at very high prices.
The same is true for Moderna or BioNTech. They also built their own capabilities for producing raw materials for their processes because of the supply-chain issues we saw during COVID‑19 pandemic. I think this is a very big opportunity for enGenes, for example, because we are not directly competing with CDMOs for fermentation capacity. We develop the technology and processes that these companies need, and we can help them vertically integrate and do things on their own again without being dependent on third parties and without incurring very high costs. I think this is a very interesting aspect — that things are going back to where we were 20 years ago.
David Brühlmann [00:14:18]:
We have covered a lot of ground today. What is the most important takeaway from our conversation?
Juergen Mairhofer [00:14:26]:
Don't be afraid, I would say.
David Brühlmann [00:14:29]:
Excellent. Don't be afraid.
Juergen Mairhofer [00:14:31]:
Don't be afraid, and let's innovate our way out. I think all of us in the biotech industry have had a hard time over the last two years or more. The COVID period was tough, and now we see geopolitical shifts, the uncertainties we are confronted with, and all these reshoring initiatives that are ongoing — like the Biosecurity Act, for example. To get back to normal and to stay ahead of the competition, we have to be innovative. Otherwise — as I said before — we will become irrelevant, because the rest of the world is not sleeping. Quite the opposite. Only innovation can help us stay ahead of the competition. That would be my wrap-up of our very nice discussion today.
David Brühlmann [00:15:19]:
Where can a smart biotech scientist who wants to learn more about your E. coli strain and your continuous manufacturing capabilities get in touch with you?
Juergen Mairhofer [00:15:28]:
We have a lot of peer-reviewed publications out there. If you're interested in the technological details, you can dig into those. We currently have an accepted publication in Trends in Biotechnology, together with the Technical University of Denmark, specifically with Andreas Hougaard Laustsen-Kiel’s group. I want to mention that project because it's a very nice one. We have been producing snake antivenom single-domain antibodies in a one-pot bioreactor, significantly reducing the cost using E. coli to produce antivenom therapies for people who are bitten by snakes. Every minute someone somewhere in the world is bitten by a snake, and this approach could help save lives. That’s why we are very proud of this project.
You can also find me at different conferences. For example, I will be in Barcelona at the Bioprocessing Summit, and later in Dublin at the conference of the International Society for Cell & Gene Therapy. If you are close to Vienna, feel free to reach out. I’m always happy to talk with people. I also enjoy helping young entrepreneurs, because I’ve been doing this for 12 years now — growing quite a few gray hairs along the way. I’ve seen many problems, made many mistakes, and I’m happy to share that knowledge if someone needs help.
David Brühlmann [00:16:58]:
There you have it, smart biotech scientists — please take advantage of it. I will also leave the company links in the show notes. And Juergen, thank you very much for sharing your passion and for giving us a wake-up call about innovation. It has been a huge pleasure having this conversation with you today.
Juergen Mairhofer [00:17:18]:
David, thanks a lot for having me. It was a real pleasure discussing with you today. I'm looking forward to feedback from the community about what they think.
David Brühlmann [00:17:28]:
From strain engineering to supply-chain geopolitics to the raw realities of building a biotech company, Juergen Mairhofer brought a perspective you don't hear every day. If this episode made you think differently about where bioprocessing is headed, share it with a colleague and leave a review on Apple Podcasts or wherever you listen. It helps other scientists like you discover the show.
Thank you for tuning in. Until next time — do biotech the smart way. For additional bioprocessing tips, visit www.smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in our next episode. Until then, let's continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Juergen Mairhofer
Juergen Mairhofer is a biotech entrepreneur and scientist with deep expertise in genetic and bioprocess engineering. Before co-founding enGenes Biotech, he conducted research at BOKU University and the Austrian Centre of Industrial Biotechnology, where he worked on engineering microbial systems for efficient protein production.
He earned his PhD in Biotechnology in Vienna and has contributed to the field through numerous publications, as well as advanced training in systems biology and microbial genomics. He is particularly focused on driving innovation in microbial manufacturing and next-generation bioprocesses.
Connect with Juergen Mairhofer on LinkedIn.
If you’re interested in exploring more breakthroughs in continuous bioprocessing and the future of biotech manufacturing, check out these past episodes from the Smart Biotech Scientist Podcast:
Episodes 85 - 86: Bioprocess 4.0: Integrated Continuous Biomanufacturing with Massimo Morbidelli
Episodes 153 - 154: The Future of Bioprocessing: Industry 4.0, Digital Twins, and Continuous Manufacturing Strategies with Tiago Matos
Episode 155: From Process Bottlenecks to Seamless Production: How Continuous Bioprocessing Changes Everything
Episode 156: The Hidden Economics of Continuous Processing That Most Biotech Companies Overlook
Episodes 181 - 182: Innovating Continuous Bioprocessing with Vibrating Membrane Filtration with Jarno Robin
Episodes 209 - 210: From Batch to Continuous: Building Innovation Culture in Conservative Biotech Environments with Irina Ramos
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
What if continuous microbial manufacturing wasn’t a pipe dream, but a reality quietly reshaping the foundations of bioprocessing?
Stuck in the cycle of fed-batch fermentation, the industry has long treated genetic drift and instability as unavoidable limitations—especially with E. coli. But what if the root of these headaches lies not in the hardware or facility layout, but deep within the biology itself?
Today's guest on Smart Biotech Scientist Podcast with David Brühlmann is Juergen Mairhofer, CEO of enGenes Biotech GmbH. Juergen is a scientist with a rare dual fluency in molecular biology and bioprocess engineering.
The solution to the problem is the genetic stability. Because with this high replication rate of microbial cells, you always have this genetic drift. And this is already pronounced in a simple fed-batch process. But when you start to do that in a continuous manner, the process has to be terminated within a few days. Because if you use a classic cell line, the cells will mutate so quickly and there will be no productivity within 4 to 5 days.
David Brühlmann [00:00:31]:
What if the biggest bottleneck in bioprocessing isn't your downstream equipment or your facility design, but the production host itself? Today I'm joined by Juergen Mairhofer, who is the CEO of enGenes Biotech, who has spent over a decade engineering smarter microbial platforms and pioneering continuous manufacturing using microbial cells for recombinant proteins and plasmid DNA. In this conversation, we dig into what it actually takes to move from batch thinking to continuous reality. Let's dive in.
Welcome, Juergen, to the Smart Biotech Scientist. It's good to have you on today.
Juergen Mairhofer [00:02:25]:
Great, David, to be with you today, and I'm really looking forward to this very nice conversation.
David Brühlmann [00:02:30]:
Juergen, share something that you believe about bioprocess development that most people disagree with.
Juergen Mairhofer [00:02:37]:
That most people disagree with. I don't want to be provocative here, but I think that the commodity CDMO model rewards utilization over innovation, and that's why it's becoming unsustainable. So what we know is that CDMOs optimize for utilization of their existing steel tanks and not really for the productivity of the process. I think the problem that we are seeing in the industry and the traditional business model they are driving rewards risk minimization and capital utilization on their end, and they are not really willing to innovate.
When you make money by selling fermentation time, you have zero incentive to make processes faster and more efficient. I think this is the core problem or the root cause of the problem. And when you look into documents like a recent report from Roland Berger, the data in there shows that CDMOs with the right business models, really focused on innovation, can avoid significant price pressure. This is exactly the point.
So the commodity model is under severe pressure, while innovation-focused players thrive. And we at enGenes Biotech deliberately didn't build enGenes as a traditional CDMO.
So our model is based on real process development using proprietary technologies and then out-licensing these technologies. So enGenes makes money when the process gets better, not when it gets longer.
So this is the basic principle, and this aligns our interests with those of our customers. So we are the innovation partner that CDMOs and pharma companies are in need of in these difficult times.
David Brühlmann [00:04:24]:
Before we dive a bit further into your CDMO model and what exactly you're doing in process development, draw us into your story, Juergen. What sparked your interest in biotechnology and what were some pivotal moments leading to your current CEO role?
Juergen Mairhofer [00:04:42]:
So what are the pivotal moments? I think the pivotal moment was when I started my master's thesis here at the University of Natural Resources and Life Sciences, Vienna (BOKU), where I did host cell engineering, so classical molecular biology, and where for the first time in my life I could be creative in a way without other people judging my creativity.
Because if you do painting or something like that, everyone can say, okay, this doesn't look like a dog. But if you pipette small volumes in an Eppendorf tube and you have to wait for four weeks until you get a dataset out, in between nobody can judge whether the creative process is good, bad, or whatever.
So with my supervisor at that time, I learned that creativity is something really amazing. And being raised in a home where everything was macro, because my father is a car mechanic, things were judged immediately because you can just do things right or you can do things wrong. But with molecular biology, you have to try and you have to learn whether things work out.
And this is where the creative process started. Being at that time, I think 24, I think it was the first time in my life I learned what creativity can really bring to the table.
And there was no judgment in academia. So we were able to try things out and see if things worked out. And we were following a lot of weird ideas at that time point because this was the time when synthetic biology was born more or less. So starting around 2002, I think, with the first publications. And I ended up in a very dynamic field and I really appreciated that. So being able to be creative, I think this was the spark.
And then having the opportunity to do a PhD together with a big pharma company - my PhD project was funded by Boehringer Ingelheim at that time -, and getting also an idea of how big industry works.
Then being able to do two more additional postdoc positions, for example with the Austrian Centre of Industrial Biotechnology (ACIB), I also got more and more insights into how the industry works. And at the end of the day, I realized that the big pharma industry is not the place where I want to grow old.
So I come from a sort of DIY perspective. I grew up in the countryside in the 1990s, where nothing was going on, so it was very boring. When we wanted to have fun, we had to build our stuff on our own.
And I think with that mentality, I was able to develop the mindset to start thinking about founding my own company. And I think that's the point where everything started. So being passionate about being creative, building stuff on my own, and then also having the guts and coming from a hard-work mentality to really dig into a topic and make it work. So I think this is what got me into founding my own company.
David Brühlmann [00:07:39]:
Yeah, I love the way you're looking at pharma, looking at creativity where a lot of people see regulatory constraints. It's a pretty good way to look at it. And then on top of that, your entrepreneurial mindset and also hard work. And I think that's definitely a sweet spot. So tell us a bit more about what you're doing now with your company, how you are translating scientific innovation into scalable bioprocesses and more?
Juergen Mairhofer [00:08:09]:
As I started to explain, I was always working at the intersection of molecular biology and bioprocess engineering. So this was quite new in the early 2000s. It was the field of synthetic biology coming up, and at that time people were used to working in silos.
So there were people doing molecular biology, and then there were the bioprocessing people, and within the bioprocessing community there were the upstream people and the downstream people, and none of them were really able to communicate with each other because they had different mindsets and they spoke different technical languages.
And the funny thing was that within my PhD project, it was located directly at that intersection. Meaning we had to engineer a strain, to build a new Escherichia coli (E. coli) strain with a lot of genetic features to be able to perform certain tasks.
And I brought that strain to another working group at the university doing upstream processing. And I think I was one of the first people who was a molecular biologist and then also running fermenters at that time. So that was quite unusual. I had to really work hard so that these people would take me seriously.
But at some point they started to understand that this knowledge has a lot of value because it's like an iterative cycle. This is what I implemented here at the university, saying: Okay, we have to engineer the strain to meet the requirements of a bioprocess, and then we have to look at how the strain behaves in a real bioreactor, not in a shaker flask.
And then once we have learned that, we have to go back and improve the strain, and we have to run this cycle iteratively several times until we have an output that meets our requirements. So this is how I learned to work with the tools I had at that time, and this was fundamental, I think, to founding enGenes Biotech. Because all the work we are doing is based on a proprietary E. coli host strain that I invented together with colleagues.
So what we are capable of doing is that we can decouple protein production from cell growth. At a dedicated time point in the bioprocess, we can stop cell division and at the same time switch on the protein production process, which is using an orthogonal transcription system.
So in that case, T7 RNA polymerase, which then massively overtranscribes the gene of interest. And by having this non-dividing cell population, we can fill the cells with recombinant protein, or we can even secrete the protein to the extracellular space.
At the same time, this also genetically stabilizes the manufacturing system. Because one of the big drawbacks of using bacteria is that they have a very rapid growth rate. So they have a very high turnover. Every 20 minutes you generate progeny, you have an exponential growth function. And due to that fast growth, the genetics of the cells drift, because you always generate variability within your population.
At some point you end up with a cell that no longer has the plasmid where your gene of interest is located, or it has a mutation in some intracellular function. This cell can then overproliferate in your bioreactor and stall your production type. By stopping cell division, you can derail that process. So you're derailing adaptive evolution, and thereby we were able to come up with a very stable and robust manufacturing system that we finally commercialized within enGenes Biotech. And this is where the story started about 12 years ago.
David Brühlmann [00:11:33]:
What kind of products are particularly well suited to produce in your specific strain?
Juergen Mairhofer [00:11:39]:
Everything that you can produce using E. coli, so that is non-glycosylated, we are happy to take over this challenge because we believe that the non-growth-associated production is most of the time beneficial over the growth-associated production.
Because growth-associated production has these drawbacks that I already addressed, namely that the cells try to escape from the burden of producing whatever — let's say recombinant protein, plasmid DNA, or a small metabolite — it doesn't really matter. They want to escape because their objective function is to generate progeny as fast as possible, and they have absolutely no interest in serving the bioprocess engineer.
On the other hand, you have to come up with a smart solution to get the cells to the point where they have to do what you want them to do and to reduce the degrees of freedom that they have. And by playing this trick that we are implementing on the molecular biology level, we block the RNA polymerase of E. coli, so the cell can no longer produce its own messenger RNAs (mRNAs). And therefore it cannot ramp up a stress response, because the stress response is always meant to escape the metabolic burden you exert on the cell by forcing it to overproduce your biomolecule of interest.
David Brühlmann [00:12:57]:
And if I may put it simply, basically your cell line gets you a much higher titer, correct? Because you have more energy available for your protein of interest.
Juergen Mairhofer [00:13:08]:
Absolutely. So all the metabolic resources are channeled into production of the protein of interest, or replication of a plasmid, or production of a bioconjugate. And this allows us to come up with very high-titer processes, and at the same time processes that are very scalable, because we don't have this process variability that can happen through plasmid loss or accumulating mutations.
So also in the scale-up process, the processes we develop are much more robust and stable. And I think this is the big advantage of the technology that we are using.
David Brühlmann [00:13:45]:
And what is now the ratio between traditional fed-batch processes and continuous processes in your programs? Because I know you're big on continuous, but what is the current ratio?
Juergen Mairhofer [00:13:57]:
I mean, the current ratio, to be honest, is that we have been developing microbial continuous processes, and we are the first movers in that field. So I don't know of any other company that has successfully accomplished running an E. coli process fully continuous for the amount of time — days — that we have achieved. So we are currently talking about 40 days. So I think we are the first mover here.
We are currently trying to scale up our process on our own. Right now it's running at the 1-liter scale, already very productive with a small footprint. But at the end of the day, we are looking to scale that up to the 100-liter scale producing bioreagents.
So this is what we are currently looking into, and we are looking for partners who are willing to adapt this process scheme for biopharmaceuticals, for example. So insulin would be an amazing case, because this is something that needs to be produced at massive scale. At the same time, the costs have to be low.
What we are struggling with at the end of the day is what you mentioned earlier — the industry is very risk-averse and conservative. For mammalian cell culture, continuous processing is taking off at the moment. So we see that there is a lot of interest in that. Very few companies are able to master it, but some of them are. But for microbial bioprocessing, I think we are just at the beginning. So this is something we have to push forward now. We see that it is getting traction, but it needs someone who is willing to adopt it and to further develop it together with us.
David Brühlmann [00:15:33]:
What is the reason that E. coli is lagging behind? Because as you said, several companies are mastering continuous processing with CHO, but what is more complex — either on the technical side, or perhaps there are economic factors in E. coli processes that explain that?
Juergen Mairhofer [00:15:48]:
The solution to the problem is, as I have explained before, genetic stability. Because with this high replication rate of microbial cells, you always have this genetic drift. And this is already pronounced in a simple fed-batch process. But when you start to do that in a continuous manner, the process has to be terminated within a few days.
Because if you use a classic cell line, the cells will mutate so quickly that there will be no productivity within 4 to 5 days. That's what we've been seeing by using the classical E. coli BL21 strain, for example, in head-to-head comparison with our technology.
So this effect is really pronounced in continuous mode, and I think the tools haven't been available to tackle that. But now with our technology, we have a genetically stabilized host cell, and we have a proprietary approach to how we do things. Because we do not run the continuous process just in one vessel — a chemostat. We run it in two connected chemostats.
This adds a bit of complexity, but at the same time it solves the problem of genetic stability. In the first vessel we grow our cells, so that is where biomass production is going on. Then we pump our cells into a second vessel where we decouple protein production from cell growth. We stop cell division in the second vessel, thereby genetically stabilizing the system, and then the production goes on in the second vessel. And we are in a fully steady-state condition. So everything that goes in on one side is equal to what goes out on the other side.
And by applying that trick, we end up with a productive process for up to one month. So this is the solution to a complex problem, and I think people have been struggling a lot to solve that. But the solution is now out there. Whenever somebody has an interest in doing that, we can start straight away.
David Brühlmann [00:17:39]:
With now 30 days in continuous mode with E. coli, how do you run the DSP (downstream processing)? Is that continuous, or are there several batches followed by each other?
Juergen Mairhofer [00:17:50]:
The project we have been working on with a larger consortium here in India is a fully end-to-end continuous process. So the upstream is continuous, then the primary recovery. In that case, we have our product — a Protein A ligand — in the supernatant. So we have to separate the biomass from the supernatant. This is done by continuous dynamic filtration.
Then we end up with a clear permeate where our product is located. And this is then captured by a multi-column chromatography approach where we have four columns that are run in series. So every time two columns are loaded, one is eluted, and the fourth column is regenerated. And by assembling all these continuous unit operations, we came up with a very intensified process.
All the learnings we have from changing our mindset in that project to a fully continuous approach can be injected directly into the classical things we are doing in fed-batch mode, because the learnings in process intensification can also be applied to the classical fed-batch principle. So it's about how to do things in the most efficient way.
Because what is very important in continuous production is that you have a robust setup, since you cannot tolerate failure. Everything has to be very robust and very effective, otherwise you cannot master such an endeavor.
David Brühlmann [00:19:11]:
What are the main advantages of a continuous process with E. coli? Many of the listeners are familiar with continuous processes with CHO cells. Are you seeing similar advantages or are they very different?
Juergen Mairhofer [00:19:25]:
I think it's quite similar because what are the main advantages? You want to produce more with less, meaning less facility footprint, less capital expenditure (CAPEX). So you want to invest in a small facility, not build a 10-cubic-meter stainless steel facility. You probably want to build a single-use facility that you can fit into a ballroom concept or something like that.
And you want to have less operational expenditure (OPEX). Meaning if it's fully automated and digitalized, you can also save costs on the level of personnel. I mean, the process that we had up and running required only one person available who was looking at the process from a meta perspective, also being able to send out SMS alerts if things were going wrong or if there was a process deviation.
You can really start to think on a different level. Not having 120 people running around like crazy, but trying to have a process that runs with a small footprint and a low headcount. I think this is what we have to do to innovate and to stay competitive in the race that we are seeing at the moment on a global level. If we are not willing to innovate, we will become irrelevant. I think this is absolutely the problem we are facing.
David Brühlmann [00:20:45]:
Yeah, this is a good point, and I would like to touch upon innovation a bit later. I just want to ask a question about what can go wrong with an E. coli continuous process, because even with CHO, it's no easy endeavor in certain cases to run a process for 30, 45, or even longer days. What are the main reasons or issues you have observed that can go wrong?
Juergen Mairhofer [00:21:10]:
The main issues that can go wrong: genetic stability first and foremost. That is, I think, the major obstacle, as already elaborated.
This is something we had to learn and improve stepwise. Genetic stability on different levels:
Then other issues like sterility can also be a concern. We haven't seen a lot of contamination because we are very good at working aseptically, but if you want to have something running for more than two weeks, it can become a problem at some point.
Especially when you think about single-use equipment, where the systems are most of the time validated only for about 10 days or something like that. So this is still an open question — whether you can reliably run single-use equipment for extended periods.
Another topic is leachables. Is there a leaching issue, especially in microbial processes where you might use ammonia? Is this more pronounced compared to CHO processes? That is a question to be addressed in the future. Then there is also the complexity of connecting multiple unit operations continuously. This can create challenges because if something changes in the upstream, it can have a major impact on the downstream.
We solved that by building models around our process, implementing hybrid or mechanistic models. One of the nice things I can mention here is that we are able to determine the product yield every 15 minutes online. We have an HPLC standing next to our continuous process that measures the titer and then injects that data point into a mechanistic model. This mechanistic model counts, for example, the cycles on the multi-column chromatography, so we know how the columns age.
Based on this knowledge, we can then call the optimal purification method determined by the mechanistic model to purify the protein at the current concentration in the supernatant. These are the feedback loops that you can implement to make your life easier.
And then, as I mentioned earlier, through automation you can solve many problems on the fly. For example, if readings show that the back pressure is increasing on the filtration device, the system can send a warning message to someone near the system to check it and counteract the issue early. That way you avoid something like a burst connection due to rising back pressure.
David Brühlmann [00:24:13]:
This wraps up part one of our conversation. From growth-decoupled production to the real engineering challenges behind continuous microbial manufacturing, Juergen is giving us a masterclass in rethinking how we scale bioprocesses. And we're just getting started.
In Part 2, we shift gears into the business side — CDMOs, geopolitics, and the founder's journey. If you're enjoying this episode, leave a review on Apple Podcasts or your favorite platform. It truly helps other scientist like you discover the show.
For additional bioprocessing tips, visit us at www.smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in our next episode. Until then, let's continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Juergen Mairhofer
Juergen Mairhofer is co-founder of enGenes Biotech and a biotechnology expert specializing in microbial cell design and bioprocess engineering. He previously worked as a Research Associate at BOKU University in Vienna and as a PostDoc at ACIB, focusing on recombinant protein production and strain engineering.
Juergen holds a PhD in Biotechnology and has authored multiple scientific publications and book chapters. His work centers on translating advanced genetic technologies into scalable industrial solutions.
Connect with Juergen Mairhofer on LinkedIn.
If you’re interested in exploring more breakthroughs in continuous bioprocessing and the future of biotech manufacturing, check out these past episodes from the Smart Biotech Scientist Podcast:
Episodes 85 - 86: Bioprocess 4.0: Integrated Continuous Biomanufacturing with Massimo Morbidelli
Episodes 153 - 154: The Future of Bioprocessing: Industry 4.0, Digital Twins, and Continuous Manufacturing Strategies with Tiago Matos
Episode 155: From Process Bottlenecks to Seamless Production: How Continuous Bioprocessing Changes Everything
Episode 156: The Hidden Economics of Continuous Processing That Most Biotech Companies Overlook
Episodes 181 - 182: Innovating Continuous Bioprocessing with Vibrating Membrane Filtration with Jarno Robin
Episodes 209 - 210: From Batch to Continuous: Building Innovation Culture in Conservative Biotech Environments with Irina Ramos
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
For many biotech innovators, high throughput screening platforms promise faster discoveries and streamlined workflows. Yet beneath the glossy veneer, the reality often feels more complicated—requiring hands-on expertise, careful assay design, and a sharp understanding of microbial physiology just to avoid costly missteps.
Smart Biotech Scientist Podcast host David Brühlmann is joined by Sebastian Blum, a microbiologist with more than two decades in the life sciences and now Market Development Manager at Beckman Coulter Life Sciences.
Some believe that high-throughput screening is a kind of black box, where you throw a sample in and it spits out the perfect hits. And automation is often misunderstood as synonymous with simplicity. The reality is, high-throughput screening is highly complex. It requires very careful assay development and validation, a deep understanding of the biology, precise robot programming, and sophisticated data analysis. The system must be calibrated, maintained, and constantly monitored. Misunderstanding this can lead to suboptimal decisions, especially when the team believes it’s “just pushing a button” and underestimates the need for highly specialized personnel.
David Brühlmann [00:00:38]:
Welcome back to Part Two with Sebastian Blum from Beckman Coulter Life Sciences. We’re continuing our conversation on mastering early-stage bioprocess development. Here is Part One of our conversation. We’re talking about practical guidance on choosing between shake flasks, benchtop bioreactors, and high-throughput platforms, and understanding when each approach makes sense for your specific application. We’re also covering the common pitfalls that trip up even experienced teams and how to avoid them. Thanks to Beckman Coulter Life Sciences for making this episode possible. If you want to make smarter screening decisions and save months of troubleshooting, this episode is for you. Let’s dive back in.
What would you tell a startup founder who says, “Well, I’m interested in the BioLector XT Microbioreactor because the system looks great. We can test a lot of things and move quickly,” as many startups want to do. But from your answer, Sebastian, it seems you also need some technical background to use the system correctly. Would you advise for, against, or under what conditions would you say no? This makes sense. You will get the most out of using a BioLector XT Microbioreactor.
Sebastian Blum [00:03:04]:
Normally, when a customer comes to us, or we approach a customer, we talk intensively about their applications. Just as an example, we had one academic customer who wanted to do strictly anaerobic cultivations with a very low OD—starting at 0.x and wanting to induce at 0.x. When we recognized this, we saw that it didn’t match the BioLector XT Microbioreactor specifications, which work from OD 1 up to, let’s say, the sky is the limit because of the scattered light measurement.
We try to understand how important this is for the customer. When he told us it was essential for his process, we said, “Okay, then the BioLector XT Microbioreactor is the choice for him.” So this can happen, but it’s application-dependent.
LUA scripting is not often used in academia. Interestingly, it’s more common in industry, where you might want to combine different feeding modes in one run to mimic larger fermenters, which may switch from exponential to linear or constant feeds. This is possible with LUA scripting, but it does not happen too often. Of course, if customers ask for it, the solution is there. If they cannot handle LUA scripting themselves, we can do it for them. This is normally not a showstopper.
David Brühlmann [00:04:22]:
So what are the scenarios in which it makes the most sense to use the BioLector XT Microbioreactor?
Sebastian Blum [00:04:28]:
I would say anything related to process development, like finding the right parameter combinations—media, pH, induction, induction profiling—and where there’s a need for flexibility across different microorganisms. For example, CDMOs need to be very flexible because they serve multiple clients with different microorganisms and applications.
The BioLector XT Microbioreactor is a very good fit, especially because we can upgrade modules depending on the application. For instance, a customer can start with a simple batch system, then upgrade to a microfluidic system to allow feeding and pH control for up to 32 wells. If the customer requires an anaerobic application, the system can be upgraded with an anaerobic module to perform feeding and pH control under strictly anaerobic conditions.
If offline analytics are needed, the whole system can be integrated with a Beckman Coulter Life Sciences Biomek i5 or i7 workstation to leverage full automation advantages.
So, if a customer needs flexibility, is screening a lot of parameters, and is trying to find the best conditions, that’s where the BioLector XT Microbioreactor excels.
David Brühlmann [00:05:54]:
So that means it’s particularly suited for early-stage screening, correct?
Sebastian Blum [00:05:58]:
Yes, exactly. That accounts for 99% of our systems, placed in upstream development for early R&D screening.
David Brühlmann [00:06:06]:
Speaking of automation and Biomek, where do you see companies typically place the BioLector XT Microbioreactor in their workflow?
Sebastian Blum [00:06:13]:
As I mentioned before, there’s upstream development, downstream development, and finished production. Typically, we see the system used only in upstream development. That’s where you do strain development, identify the best media, and set up initial culture conditions for optimal growth and productivity.
David Brühlmann [00:06:35]:
What are the most common misconceptions you see in scientists who want to acquire a BioLector XT Microbioreactor or already have one? From what we’ve discussed, it’s a powerful tool. You can do a lot of things, but sometimes it's also about managing expectations and helping people use the technology best. What misconceptions do scientists generally have about high-throughput screening systems?
Sebastian Blum [00:07:02]:
Some believe that high-throughput screening is a black box—you put a sample in, and it spits out perfect hits. Automation is often misunderstood as synonymous with simplicity. The reality is, high-throughput screening is highly complex. It requires careful assay development and validation, a deep understanding of the biology, precise robot programming, and sophisticated data analysis.
The system must be calibrated, maintained, and constantly monitored. Misunderstanding this can lead to suboptimal decisions. When teams think it’s “just pushing a button,” they underestimate the need for highly specialized personnel.
As a result, they might underinvest in assay development or bioinformatics expertise, leading to poorly designed assays, unreliable data, high error rates (false positives or negatives), and ultimately a loss of valuable time and resources because results cannot be interpreted or reproduced.
So the “black box” idea is a misconception. It’s not that simple—you can’t just put something in and automatically get the perfect hit.
David Brühlmann [00:08:02]:
This is very well said. I’ve done a lot of deep-well plate experiments in my career, and understanding the process side and analytics is just as important. Thank you for highlighting this, Sebastian.
Looking ahead, with more technology on our end—robotics, automation, and now AI—I’m curious about your perspective. How do you see early-stage bioprocess development evolving in the future?
Sebastian Blum [00:08:34]:
What I see is more automation and miniaturization. There's a clear tendency in this direction. So we are going to see even higher throughput, more sophisticated microbioreactor systems, and a lot more integration of robots for end-to-end automation workflows—from media preparation all the way to sample analyzers. AI is the buzzword, and you see it at every conference at the moment as well.
The huge amounts of data that high-throughput screening generates will increasingly be used with artificial intelligence (AI) and machine learning (ML) for predictive modeling—really fast identification of optimal conditions and a much deeper understanding of the mechanisms at play. It’s going to move beyond just finding what works to understanding why it works. So I see a lot of potential for AI, and that trend is clearly moving in this direction.
What I see as well, especially in larger industries, is more use of digital twins and process simulations. We can expect the development of more robust in silico models, basically digital twins of bioprocesses. That will let scientists simulate thousands of scenarios virtually before they even perform a physical experiment, which will speed up optimization even more. I think that’s still somewhat the future, but I see that customers are already discussing this idea and goal.
I still think some skills will always remain critical—the core bioprocess engineering principles. You still need a fundamental understanding of microbial physiology, cell biology, fluid dynamics, mass transfer, and reaction kinetics. The tools might change, but those underlying biological and engineering principles are constant, in my opinion.
Of course, you also need critical thinking and problem-solving skills—the ability to evaluate data critically, identify the root causes of problems, and design robust experiments. These will always be at the heart of successful development.
David Brühlmann [00:10:24]:
Before we wrap up, Sebastian, what burning question haven’t I asked that you’re eager to share with our biotech community?
Sebastian Blum [00:10:33]:
Honestly, David, your questions have been very good. I’ve also watched your podcast in the past and was impressed by the spectrum you cover. In my opinion, everything relevant was discussed here. I really appreciate your questions and the podcast—thank you for having me.
David Brühlmann [00:10:52]:
Great. Thank you very much for the feedback—it’s always wonderful to hear directly from our guests.
David Brühlmann [00:10:58]:
By the way, if you have feedback about the Smart Biotech Scientist Podcast, please leave a review. This means the world to me. Sebastian, what is the most important takeaway from our conversation?
Sebastian Blum [00:11:13]:
In my opinion, it’s to carefully consider where to implement high-throughput screening tools in your process and evaluate the need and advantages for your specific application. I hope I’ve highlighted the possibilities that customers have by using the BioLector XT Microbioreactor. Above all, I encourage people to stay curious, stay critical, and choose the right tool for the right job.
David Brühlmann [00:11:45]:
Fantastic, Sebastian. Thank you for helping us understand the key success principles for early-stage screening and sharing your insights. Where can people learn more about the BioLector XT Microbioreactor and get in touch with you?
Sebastian Blum [00:12:00]:
The Beckman Coulter Life Sciences website has a lot of information about the BioLector XT Microbioreactor, including publication lists, application notes, and a gallery showing how the system works. There’s also a small training section. If someone is interested in Europe, I’m available as the Market Development Manager to guide them as needed.
David Brühlmann [00:12:29]:
Excellent. I’ll include that info in the show notes. Once again, thank you very much, Sebastian, for being on the show today.
Sebastian Blum [00:12:37]:
David, it was a pleasure. Thank you.
David Brühlmann [00:12:40]:
Thanks for joining us today for this deep dive into bioprocess screening strategy. Remember the right early stage decisions, save months of troubleshooting downstream. If today's conversation gave you actionable insights for your own development work, please leave us a review on Apple Podcasts or whatever platform you're listening on. It truly makes a difference. Thank you so much for your feedback. I love hearing from you. And until next time, keep doing biotech the smart way.
All right, smart scientists, that’s all for today on the Smart Biotech Scientist Podcast. Thank you for tuning in and joining us on your journey to bioprocess mastery. For additional tips, visit www.bruehlmann-consulting.com. Stay tuned for more inspiring biotech insights in the next episode. Until then, let’s continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Sebastian Blum
Sebastian Blum has spent over two decades in the life sciences industry, with a background in biology and microbiology. He is currently Market Development Manager at Beckman Coulter Life Sciences, focusing on high-throughput screening technologies for bioprocess development.
In 2010, he discovered an innovative micro-fermentation system that sparked his interest in transforming early bioprocess workflows. Motivated by strong researcher feedback, he joined m2p-labs in 2011 to help advance the technology. Following the acquisition of m2p-labs by Beckman Coulter Life Sciences, Sebastian embraced the opportunity to continue the journey within a global organization.
Connect with Sebastian Blum on LinkedIn.
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
Why do so many promising biotech ideas stall—long before they reach the clinic or marketplace? For many, the answer lies hidden in the earliest phase of bioprocess development: upstream processing. It’s where strain selection, media optimization, and culture conditions set the stage for everything that follows. Yet, the smallest missteps here can snowball into expensive roadblocks downstream.
Joining Smart Biotech Scientist Podcast host David Brühlmann is Sebastian Blum, a microbiologist with more than two decades of experience in the life sciences and currently Market Development Manager at Beckman Coulter Life Sciences.
There are a lot of bottlenecks in the early bioprocess development in the upstream processing. There is where you do all your strain development, trying to find the best media, setting up those initial culture conditions to get the best growth and productivity, and very often see things get stuck in these early upstream phases. And if you're not doing enough comprehensive screening and optimization right after the beginning, like with your strain selection or media development, you're often setting yourself up for suboptimal titers for product quality and those issues become way harder and more expensive to fix later on when you are further downstream or trying to scale up for example.
David Brühlmann [00:00:40]:
Welcome to The Smart Biotech Scientist. Are you struggling to choose the right screening approach for your early-stage bioprocess development? Wondering if you're creating bottlenecks that will haunt you downstream? Today, we're tackling the critical decisions that separate efficient process development from costly delays. I'm joined by Sebastian Blum, who is a microbiologist with over two decades in life sciences and Market Development Manager at Beckman Coulter Life Sciences. We're diving into high-throughput screening strategies that actually work. And thank you to Beckman Coulter Life Sciences for sponsoring today's episode. Welcome Sebastian. It's good to have you on today.
Sebastian Blum [00:02:36]:
Hey David. Fine now. Happy to hear. Thanks.
David Brühlmann [00:02:39]:
Sebastian, share something that you believe about bioprocess development that most people disagree with.
Sebastian Blum [00:02:46]:
Well, that's an interesting one. So I think maybe the James Bond question, or at least I call it the James Bond question, which often arises in the community. Is it stirred or is it shaken? And in my opinion, in the early screening phase in R&D of microbial cultivations, it's not about how the oxygen is introduced, but how much is introduced. So what is the kLa and what is the oxygen transfer rate? So in my view for this question, at that stage it's irrelevant whether it's stirred or shaken.
David Brühlmann [00:03:12]:
You have quite a long career already in bioprocess development. Take us into your story in the very early days. What drew you into this field and what were some interesting steps along your career path?
Sebastian Blum [00:03:27]:
Actually, I've been in the life science industry for over 25 years now. My background is in biology with a focus on microbiology. Back in, I think it was 2010, there was a small company in my network which really caught my eye and they had invented a micro-fermentation system and they were really focused on using it for bioprocess development across different markets. I was super hooked. So I started talking to potential customers, just asking what they thought about having a tool like that in their lab. And their feedback was quite positive. And that totally convinced me at that time and led me to join the m2p-labs team in 2011, which was then acquired by Beckman Coulter Life Sciences roughly 10 years later. At that point it wasn't an easy decision for me because I just had my first child and honestly I was looking for some stability at that time. But in the 14 years since I have been there, I've never regretted the choice a single day.
David Brühlmann [00:04:16]:
I'm curious Sebastian, because you work with a lot of different companies. Please paint us a picture of how certain biotech companies approach process development differently.
Sebastian Blum [00:04:27]:
Okay, that's maybe really interesting because when I look at biotech companies, they actually tackle process development quite differently and often it depends on who they are. What do I mean by this? For instance, if you've got smaller startups or academic spin-offs, they're usually all about speed and keeping costs down. So they might start with simpler solutions or lower-throughput methods, things like shake flasks, for example, just to quickly prove their concept. And it's all about getting that initial data very fast.
And then on the other end of the spectrum you have the big established pharmaceutical companies and they tend to invest heavily in really robust data-rich early-phase development. For example, they are using advanced automation high-throughput systems like the BioLector XT Microbioreactor right from the start. The main goal is normally to de-risk the process as much as possible, ensure it's scalable afterwards and build this super comprehensive understanding of all the critical process parameters.
Why are they doing this? Because they have got to meet stringent regulatory requirements down the line. And then of course you have the CDMOs, those contract development and manufacturing organizations. They really have to be super flexible, offering a whole spectrum of approaches, simply because they are serving so many different and diverse clients, each with their own unique needs and at different development stages. One common thread that I've seen among all these successful companies, regardless of their size, it's the commitment to generate good data and doing it early and often. Hope that answers your question.
David Brühlmann [00:05:55]:
Just following up on your answer because this is very insightful. What is the main difference between the small and the large companies? Is that mainly cost or is it also expertise or the ultimate strategy? What is your observation?
Sebastian Blum [00:06:10]:
I would say also costs very often, but sometimes you're underestimating the startups where strong investors are, for example, included and they want to push the startups as quickly to the market as possible, and then all of a sudden they also have quite a high budget. But yes, of course startups normally have less budget and fewer resources compared to big pharmaceutical companies, for example.
David Brühlmann [00:06:33]:
Among the projects you are involved in, where are the most common bottlenecks or challenges?
Sebastian Blum [00:06:41]:
I see that there are a lot of bottlenecks in the early bioprocess development. In the upstream processing there is where you do all your strain development, trying to find the best media, setting up those initial culture conditions to get the best growth and productivity, and very often see things get stuck in these early upstream phases. And if you're not doing enough comprehensive screening and optimization right after the beginning, like with your strain selection or media development, you're often setting yourself up for suboptimal titers for product quality and those issues become way harder and more expensive to fix later on when you are further downstream or trying to scale up, for example.
David Brühlmann [00:07:19]:
This is an excellent point. Smart biotech scientists, please listen to this again. I'm going to repeat it. You need to focus on it early on because if you make mistakes early on, these can become very expensive. So thank you very much for saying this, Sebastian, because this is also a message I try to repeat as much as I can. And very important advice. If you look now at early-stage bioprocess development, what are the most common misconceptions you come across working with a diverse group of people?
Sebastian Blum [00:07:49]:
I think most scientists are aware of the particular importance of the early screening phase, so I wouldn't call it a misconception. However, I more often see scientists screening in, for example, batch mode, even though it's already foreseeable that the final process will run in a fed-batch mode, so including pH control. In my experience this can lead to an incorrect ranking, which then only becomes apparent during the scale-up process. This result can lead to a significant loss of time, as you essentially have to start all over again afterwards. I mean, this can be accounted for in project planning, but why not directly screen in the mode in which the final process will ultimately run afterwards?
David Brühlmann [00:08:27]:
Yes, this is important to know what will be the system your process will be running in. Or in other words, start with the end in mind. This is important. And then work everything backwards, right?
Sebastian Blum [00:08:38]:
Yeah, exactly.
David Brühlmann [00:08:39]:
Now, early-stage development can be quite overwhelming if you have never done it before, especially if you're launching your own startup. You have a lot of things to look after. And now, since there are so many different bioreactor systems, how should a founder go about—or even say a more advanced biotech company? Because you have very different systems. So perhaps let's start like this. Sebastian, can you paint us a picture of the various small-scale systems that are available and perhaps just give us the two-minute version of when you should work with one or the other system?
Sebastian Blum [00:09:17]:
I would say when scientists are looking at bioreactor systems today, it's like they are choosing from a pretty clear spectrum. And I would say each option has its own trade-offs. You can start, for example, with the shake flasks. They are super cheap, easy to set up, and good for just rough initial screening and checking viability, for example. But that's the con. The process control is terrible. pH, DO, temperature, they are all over the place. You get limited real-time data. Reproducibility isn't great, not to talk about scalability. Plus, if you have a lot of samples, it's really labor-intensive, not to mention the cleaning and potential cross-contamination. So there are, of course, fields where you can use them, but you need to really check carefully when to use them.
Then, for example, if you look at benchtop bioreactors, 1-liter to 10-liter stirred-tank bioreactors, for example, the advantage is you get excellent process control. They are great for actual scalability studies and they are much more representative of large-scale production compared to, for example, the shake flask. And you can get really rich kinetic data from them. But downsides also exist: they are expensive per experiment and your throughput is normally low. You can only run a few in parallel, which takes a lot of lab space as well. And there is still a lot of manual work involved and they are just slower for extensive optimization. So these are, in my experience, ideal for process characterization and initial scale-up once you have already identified your key parameters.
Then finally, the high-throughput platforms. The advantages—the pros—are this is where you get massive parallelism. We're talking about dozens of experiments all in parallel. And you get advanced process control even at the microscale, with real-time non-invasive measurement for things like optical density, pH, dissolved oxygen, different fluorescent proteins. And they are reproducible and generate tons of rich data for DOE studies, for example, really speeding up early-stage optimization. But also there we have disadvantages. The initial capital investment is higher normally, and you really need good experimental design and data analysis skills to get the most out of them. So these are best for, in my opinion, rapid strain screening, media optimization, and doing really comprehensive process development in those early and mid-development phases.
The big takeaway is I think you've got to pick the system that truly aligns with your development stage, how much data resolution you need, your throughput requirements, and of course your budget. And often companies will use a combination of these systems in a phased approach, for example.
David Brühlmann [00:11:39]:
Basically we have three different main types of bioreactors. Correct? We have the shake flasks or the spin tubes, which are very simple in handling, but you don't have a lot of control over them. We have the bioreactors where obviously the throughput is not very high, but you have a lot of advantages because you can control these bioreactors. And then in the middle we have what we call these high-throughput systems where you can do a lot of screening and you can do, to a certain extent, also some process control definitely.
Sebastian Blum [00:12:13]:
So the BioLector XT Microbioreactor really stands out quite a bit, both for how easy it is to use and the quality of data it gives you, especially compared to traditional methods and even some other automated systems out there. So usability-wise, it uses a microtiter plate format, which is well known and easy for high-throughput work, and setting up an experiment in the BioLector XT Microbioreactor software is intuitive and allows the user to monitor in real time and visualize all your data. Plus, it has this non-invasive optical measurement technology, meaning you don't need to have to put probes into individual wells. That just makes handling so much simpler, reduces contamination risks, and also lets you run it continuously unattended. It's a big advantage. It cuts down on manual labor massively compared to shake flasks or even a lot of benchtop fermenter systems.
Data quality-wise, it gives you real-time online measurement for critical parameters like biomass, which is measured via scattered light, pH, dissolved oxygen, and fluorescence sensors, for instance for GFP expression. And it does this with a time difference of just a few seconds. So unlike systems that just take occasional offline samples, the BioLector XT Microbioreactor captures all those dynamic changes, giving a much richer kinetic profile of how your microbes are behaving under different conditions.
David Brühlmann [00:13:24]:
How does the BioLector XT Microbioreactor differ from, let's say, an ambr® 15 or ambr® 250 plate? I imagine a lot of you listening have worked with either one of the systems. Can you just tell us what are the different volumes, how many conditions you could typically test, and what are some main differences or also some commonalities between the three systems?
Sebastian Blum [00:13:45]:
The BioLector XT Microbioreactor system is using working volumes from 800 microliters up to 2.4 mL in a 48-well format. The 48 wells are batch fermentation. If you want to go for fed-batch fermentation with feeding, it's 32 experiments on one single plate, because we need 16 reservoirs in this plate for carbon source and for adjusting the pH. So compared to ambr® systems, 250 milliliters, there's of course a difference.
We are measuring the pH with so-called optodes, optical sensors in each of the wells individually. By this, we also don't need to take any samples, for example, for biomass measurement, which we also try to avoid, of course, because the volume is not that high and that can also be a disadvantage. If, for example, a higher volume is needed, then I would say the ambr® system with 250 mL offers much more possibilities than an 800- or 1,500-microliter reaction volume.
I would say some of our customers are using, for example, the BioLector XT Microbioreactor also to reduce or de-risk their ambr® 250 runs. That means they are using both systems in combination just to get a better-selected choice into the maybe more expensive ambr® runs and to de-risk their experiments.
David Brühlmann [00:14:56]:
Can you run perfusion at all in the BioLector XT Microbioreactor?
Sebastian Blum [00:15:02]:
No, that is not possible. We cannot run a perfusion in the BioLector XT Microbioreactor.
David Brühlmann [00:15:06]:
Okay, understood. And what are the cell types that are best suited for the BioLector XT Microbioreactor?
Sebastian Blum [00:15:11]:
BioLector XT Microbioreactor is developed for microbial applications, so everything that needs high oxygen transfer or changes the pH quickly is made for BioLector XT Microbioreactor. Definitely do not use mammalian cells in the BioLector XT Microbioreactor. We tried this in the past because we were curious, but the results were quite poor. So we said, okay, that's not our target market here.
But the possible microorganisms that can be used range from strictly anaerobic applications to phototrophic organisms, fungi or filamentous fungi, even bacteria, yeast, E. coli, Pichia, Saccharomyces, Bacillus, you name it. So it's very flexible in terms of microorganism cultivation.
David Brühlmann [00:15:49]:
Can you give us some specific projects or cell types you have worked on recently?
Sebastian Blum [00:15:55]:
We are working with Pichia pastoris and methanol induction, which is very common in the industry as well and gives a big advantage. But also Lactobacillus, for example, in the food industry is often used with BioLector XT Microbioreactor and low-pH sensors that we are offering because of the low pH at which Lactobacillus is cultivated. So I would say these are some strong organisms that we are working with together with customers at the moment.
David Brühlmann [00:16:18]:
I'm just curious, because what I am hearing, Sebastian, is that the BioLector XT Microbioreactor excels at screening experiments because you have 48 wells you can use for media screening, for different culture conditions, and now giving different approaches, especially modeling approaches and so on. I mean, there are smarter ways to define your experiments and there are not-so-smart ways to define your experiments, let's say it like that in a very simple way. So I'm just curious, how do you guide companies also to make the best use of the BioLector XT Microbioreactor? Can you give us some examples what companies typically need, or are they very experienced and they know exactly what they need to do?
Sebastian Blum [00:17:00]:
Typically when they get in touch with BioLector XT Microbioreactor, we normally also do demonstrations of the system, and at that point in time we understand what customers need and the customer understands what the system can offer to them. So that helps a lot in the process of seeing whether the system gives an advantage to the customer at all.
But of course, there is intensive training because not everyone is very familiar with high-throughput screening systems or with the BioLector XT Microbioreactor specifically. And also the software is, of course, new. So there is normally a training of two to three days with application specialists involved, where we go through what customers want to see and also what kind of complexity there is.
Our system allows scripting, which means you are able to do more complex protocols. These complex protocols are done in LUA. There you need to have somebody on board who is able to script in LUA. Of course, that is not always the case, and we have also developed a user interface that helps you do that.
But very often we face, especially in the industry—less in academic areas—customers who are not able to do LUA scripting on their side. And therefore m2p-labs / Beckman Coulter Life Sciences is also offering this to be done by us, so we can get in touch with customers and talk about what they need to be able to program this LUA script especially for them. I would say from the biological part they are very experienced normally, but of course there needs to be training on how they can use their knowledge on the BioLector XT Microbioreactor most effectively.
David Brühlmann [00:18:24]:
That's it for part one. We've covered critical ground on process development strategies and early-stage decision-making. In part two, we'll continue exploring screening technologies and practical advice for maximizing your data quality. If you're finding value in these insights, please leave us a review on Apple Podcasts or your favorite platform. It helps other scientists discover practical advice like this. Thank you so much for tuning in, and I'll see you in part two.
All right, smart scientists, that's all for today on The Smart Biotech Scientist Podcast. Thank you for tuning in and joining us on your journey to bioprocess mastery. If you enjoyed this episode, please leave a review on Apple Podcasts or your favorite podcast platform. By doing so, we can empower more scientists like you. For additional bioprocessing tips, visit us at www.bruehlmann-consulting.com. Stay tuned for more inspiring biotech insights in our next episode. Until then, let's continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Sebastian Blum
Sebastian Blum is Market Development Manager at Beckman Coulter Life Sciences, specializing in high-throughput bioprocess development. He has more than 25 years of experience in the life sciences industry and supports international R&D teams in addressing microbial process challenges efficiently.
Sebastian holds a degree in Biology with a focus on Microbiology from Heinrich Heine University Düsseldorf. Before joining Beckman Coulter Life Sciences, he gained hands-on experience in laboratory automation and bioprocess technologies at Hamilton Robotics GmbH and m2p-labs GmbH.
His work bridges scientific depth with practical, scalable bioprocess solutions.
Connect with Sebastian Blum on LinkedIn.
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
Do you wish to simplify your biologics drug development project? Contact Us
Bioprocess development has always been slowed down by legacy assumptions: big stainless-steel bioreactors, endless timelines, and the belief that complex therapeutics can only be produced in closed systems. But what if you could grow life-saving antibodies in a greenhouse instead?
In this episode of Smart Biotech Scientist Podcast, host David Brühlmann sits down with Professor Waranyoo Phoolcharoen, co-founder of Baiya Phytopharm, to explore how she’s transforming cutting-edge academic research into life-saving biopharmaceuticals made from plants.
During the COVID-19 pandemic, we conducted Phase 1 and Phase 2 clinical trials for COVID-19 vaccines produced using our technology. We received many questions from regulators. With scientific questions, we used scientific knowledge to explain and answer them. That is why we were approved for both Phase 1 and Phase 2 clinical trials.
David Brühlmann [00:00:26]:
Welcome back to our conversation about molecular farming. In Part 1, Waranyoo Phoolcharoen explained how plants become biofactories and why Southeast Asia’s biotech landscape shaped Baiya Phytopharm’s strategy.
Now we tackle deployment. How does their platform address everything from oncology to infectious diseases? What enabled Asia’s first plant-derived COVID-19 vaccine to reach clinical trials and achieve a production capacity of 5 million doses per month in Bangkok? And where is this technology heading next? Let’s find out.
Let’s look at the technology itself. Your platform is very interesting—a unique and different way to produce life-saving drugs and medicines in a more affordable way.
However, scientifically speaking, you are competing with legacy systems—microbial systems, yeast expression systems, and mammalian cell systems like CHO cells.
How does your platform compare to these, and what makes it a strong choice for certain molecules?
Waranyoo Phoolcharoen [00:02:44]:
In the pharmaceutical industry today, we all know that CHO cells (Chinese Hamster Ovary cells) are the standard platform. CHO cells and microbial systems are incredibly powerful and have enabled modern biologics manufacturing. However, they were built for environments with significant capital investment and stable infrastructure.
That is not always the reality in low- and middle-income countries.
The biggest limitations are cost and complexity. CHO cell manufacturing requires expensive facilities, complex equipment, and tightly controlled conditions. This makes it difficult to build and operate in settings where capital, supply chains, and utilities may be limited.
Another issue is scalability. CHO cell systems scale by building larger bioreactors, which increases cost very quickly. That model works well for high-margin products, but it is harder to apply for affordable vaccines or monoclonal antibodies.
If you consider microbial systems, they are fast and relatively inexpensive. However, they cannot produce complex biologics like monoclonal antibodies due to the lack of proper post-translational modifications.
Molecular farming takes a different approach. Plants are naturally scalable—you grow more biomass instead of building larger reactors. The infrastructure is simpler, the system is more robust, and the cost structure is better aligned with the needs of low- and middle-income countries.
Molecular farming is not replacing CHO or microbial systems. But for products where speed, cost, and access truly matter, it is often a better structural fit.
David Brühlmann [00:04:41]:
One additional advantage I see is that you have much more flexibility with your system in terms of demand. When scaling up a biologics process, you typically need to build a larger facility or install larger bioreactors. But if I understand correctly, Waranyoo, in your case—if demand changes quickly—you could simply plant more plants in a short time. Is that correct?
Waranyoo Phoolcharoen [00:05:06]:
Yes. Because we use plants, we can grow them continuously. The plants we grow do not need to be committed to a specific product immediately—we can decide later which product to produce.
To scale up, we simply grow more plants. This is very different from scaling up CHO cell manufacturing, where obtaining additional bioreactor capacity is a major investment. For us, increasing production for each product is relatively straightforward—grow more plants. That makes scaling easier.
At the beginning of our conversation, you mentioned the importance of accelerating process development. How does your platform speed up process development?
Waranyoo Phoolcharoen [00:05:45]:
When we talk about molecular farming—using plants to produce proteins—at our company, we do not create transgenic plants. Instead, we use what is called transient expression.
This means we do not need to generate stable cell lines. Once we have the gene sequence, we introduce it into the plant and begin producing the protein almost immediately. The plant acts as a living bioreactor, translating the genetic information very quickly.
Within three to four days, we can express the target protein. From gene sequence to harvest typically takes about one week—not months.
This is why our platform enables rapid product changes and accelerated development. The key advantages are speed and flexibility.
David Brühlmann [00:06:41]:
What is the regulatory perspective on this technology? Since it is quite a different production approach, have you received buy-in from regulators?
Waranyoo Phoolcharoen [00:06:52]:
The technology itself is not new. Most regulators, including the U.S. Food and Drug Administration (FDA), have been familiar with plant-based expression systems for more than 20 years. There may be additional questions because there are still relatively few products on the market using this platform. However, regulators understand the scientific principles.
Regardless of whether a product is produced in CHO cells, bacterial systems, or plant cells, regulators ultimately evaluate the product itself. You must demonstrate purity, safety, and efficacy. The standards are similar, even if the production platform differs.
We have evidence of regulatory acceptance through our COVID-19 vaccine program. During the COVID-19 pandemic, we conducted Phase 1 and Phase 2 clinical trials for vaccines produced using our technology.
We received many questions from regulators. But scientific questions can be addressed with scientific data. By providing strong evidence and explanations, we were approved to proceed with both Phase 1 and Phase 2 clinical trials.
David Brühlmann [00:07:59]:
Beyond the COVID-19 vaccine and other vaccines, what additional molecules are in your pipeline, and how advanced are these programs?
Waranyoo Phoolcharoen [00:08:08]:
Right now, we have several products in our R&D pipeline. We are focusing more on monoclonal antibodies. We use our platform to engineer molecules and try to develop “biobetters.”
For example, we are working on cancer antibodies. We have animal data showing that our plant-produced monoclonal antibodies can be used for cancer immunotherapy.
We are also engineering different glycan structures to study whether glycosylation patterns affect antibody half-life. That is one of our key research areas.
Beyond oncology, we are also working on infectious diseases. We are developing antibodies against RSV (Respiratory Syncytial Virus), using RSV antibodies as a model to improve half-life extension strategies.
Another important focus is rabies monoclonal antibodies. Rabies remains a significant problem in Thailand and Southeast Asia. In our region, equine-derived polyclonal antibodies are still commonly used.
What we are trying to demonstrate is that plant-produced monoclonal antibodies can perform effectively as an alternative. That program is currently in progress.
David Brühlmann [00:09:31]:
As you work on these programs—especially monoclonal antibodies and your oncology pipeline—what manufacturing, development, or regulatory challenges do you anticipate before reaching market approval?
Waranyoo Phoolcharoen [00:09:51]:
After we stopped the clinical trials for our COVID-19 vaccine, we restructured the company. We have subsidiary company. We still want to focus on developing drug and new product. But I would say we need to think about revenue. We need to think about how to sell the product. Then we structured the company that I would say now maybe our goal is not develop one drug from the beginning and we aim for marketing that product. Then with Baiya Phytopharm, we still focus on developing new drugs, but we focus on what we are good at. Let's say we're thinking about developing things like if we can have molecules, antibody that have longer half-life, then we might spin off this and try to do Phase 1 clinical trial if we can. And license that product to our partner or someone else. But we have two more subsidiary companies.
One subsidiary focuses on molecular farming services. Because we have a GMP facility, we realized that many groups are interested in producing proteins using plant-based systems but lack the infrastructure or technology. By offering our platform as a service, we can support external partners, test our system across different proteins, and generate revenue while strengthening our expertise.
Another subsidiary is BGF Pantry. BGF Pantry focuses on growth factors and other proteins that can be sold as raw materials for cosmetic applications. These products face lower regulatory barriers and can reach the market more quickly. They use the same plant-based platform but provide faster commercialization pathways.
This part of the business generates cash flow and helps maintain our team and manufacturing capabilities while our therapeutic programs continue to advance.
The key point is that we must develop multiple parts of the company simultaneously to push the platform forward. We still aim to develop high-value therapeutic antibodies, but the journey to market approval is long. That is why we need multiple business engines to move the company forward. Balancing these efforts allows us to continue advancing plant-based medicines.
David Brühlmann [00:12:30]:
I’d like to go back to the GMP facility. You built it with the goal of producing a COVID-19 vaccine there—if I’m correct, with a capacity of up to 5 million doses per month. Can you tell us what the biggest technological and regulatory challenges were, especially as you were preparing during a pandemic?
Waranyoo Phoolcharoen [00:12:50]:
When I think back to that time, during the COVID-19 vaccine development, many people asked how difficult the regulatory process was. Surprisingly, it was not as difficult as many expected.
We worked closely with the Thai Food and Drug Administration. They were knowledgeable and maintained strict quality standards and protocols. Most of their questions were scientific, and scientific questions can be answered with scientific data.
Looking back, I did not see major bottlenecks from a laboratory or regulatory perspective.
The more serious challenge was actually the supply chain. Many critical pieces of equipment, reagents, and consumables required for biomanufacturing—such as filters, chromatography resins, and single-use components—were not produced locally in Thailand. We had to import everything.
During the pandemic, when every country was trying to produce vaccines at the same time, these supply chains became a major constraint. Lead times increased significantly, shipments were delayed, and that became a major bottleneck for GMP production.
That experience taught us an important lesson: pandemic preparedness is not just about having the technology or a GMP facility. It requires building the entire ecosystem.
David Brühlmann [00:14:26]:
Yes, it’s often much more global and holistic than we think, right?
Waranyoo Phoolcharoen [00:14:31]:
Exactly. In normal situations, you never think about those aspects.
David Brühlmann [00:14:35]:
As we wrap up, what are some interesting technological innovations in molecular farming that you see emerging in the future?
Waranyoo Phoolcharoen [00:14:47]:
At this point, when people ask me about our next plan, I’m not always sure which specific product we will sell. In biotech, product direction can change quickly.
But for me, the most important goal is to prove that plants can be recognized as a mainstream production platform. I don’t want plant-based systems to be viewed merely as an alternative option.
When we think about producing a protein, we typically consider mammalian cells, insect cells, E. coli, and other microbial systems. I want plants to be part of that standard list of platform choices.
Our goal is to demonstrate that plants are a reliable and scalable platform for producing medicines.
David Brühlmann [00:15:35]:
This has been great, Waranyoo. With everything we covered today, what is the one key takeaway you want listeners to remember?
Waranyoo Phoolcharoen [00:15:44]:
My key takeaway is that manufacturing platform choice truly matters.
If you are in biotech and struggling with long development timelines or scale-up challenges, it may not always be the molecule—it may be the system you are using.
Molecular farming offers a different set of trade-offs: faster development and flexible scaling. It will not replace traditional microbial or mammalian systems, but it provides scientists with another practical option.
So don’t default to only one platform. Step back and consider alternatives. And if you would like to explore this approach, feel free to reach out to me.
David Brühlmann [00:16:31]:
That’s a very good point.
Waranyoo Phoolcharoen [00:16:32]:
We are very happy to collaborate and test your molecules on our platform.
David Brühlmann [00:16:39]:
Where can people reach you?
Waranyoo Phoolcharoen [00:16:42]:
You can visit our website at www.baiyaphytopharm.com. We are also active on LinkedIn.
David Brühlmann [00:16:51]:
There you have it, smart biotech scientists. I will put the link in the show notes. Please reach out to Waranyoo.
Waranyoo Phoolcharoen [00:16:56]:
Yes, we are very open to new collaborations and excited to explore new molecules using our platform.
David Brühlmann [00:17:06]:
Well, there's your offer. Please take advantage of it and reach out to Waranyoo and her team. And Waranyoo, thank you so much for sharing your new technology, what you're doing in Thailand. It has been a wonderful conversation. Thank you so much.
Waranyoo Phoolcharoen [00:17:21]:
Thank you.
David Brühlmann [00:17:23]:
Waranyoo’s journey—from molecular farming researcher to building pandemic-ready biomanufacturing capacity in Bangkok—reveals a powerful truth: plants can help democratize medicine production.
Weeks instead of months. Regional resilience instead of dependency. Accessible biologics instead of supply chain bottlenecks.
As her oncology pipeline advances, the next chapter of molecular farming is unfolding.
If this conversation changed how you think about biomanufacturing’s future, please leave us a review on Apple Podcasts or your preferred platform.
Thank you for tuning in today, and I’ll see you next time.
All right, smart scientists—that’s all for today on the Smart Biotech Scientist Podcast. Thank you for joining us on your journey to bioprocess mastery. Stay tuned for more inspiring biotech insights in our next episode. Until then, let’s continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Waranyoo Phoolcharoen
Waranyoo Phoolcharoen is a pioneer in molecular pharming and co-founder of Baiya Phytopharm, a biotechnology company developing plant-based platforms for rapid and scalable biopharmaceutical production.
As Chief Technology Officer and a professor at Chulalongkorn University’s Faculty of Pharmaceutical Sciences, she bridges academic research and real-world impact—using plant biotechnology to develop medicines for infectious diseases. Her work focuses on making biologics faster, more accessible, and more affordable while fostering a collaborative scientific culture and strengthening Thailand’s biotechnology ecosystem.
Connect with Waranyoo Phoolcharoen on LinkedIn.
You may also enjoy exploring these additional conversations from the podcast, featuring ideas, insights, and perspectives across biotechnology and innovation.
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Episodes 163 - 164: How Moss Enables Production of Unproducible Protein Therapeutics with Andreas Schaaf
Episodes 229 - 230: Cyanobacteria Biomanufacturing: Achieving Carbon-Neutral Production at Lower Cost Than Fermentation with Tim Corcoran
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
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Do you wish to simplify your biologics drug development project? Contact Us
Bioprocess development has always been slowed down by legacy assumptions: big stainless-steel bioreactors, endless timelines, and the belief that complex therapeutics can only be produced in closed systems.
But what if you could grow life-saving antibodies in a greenhouse instead?
Today's guest on Smart Biotech Scientist Podcast with David Brühlmann is Waranyoo Phoolcharoen, co-founder of Baiya Phytopharm in Thailand, a pioneer in molecular farming—turning plants into agile biofactories for recombinant proteins, vaccines, and antibody therapeutics.
I came across a scientific paper on molecular farming, which is the idea of using plant to produce pharmaceutical proteins. Then I think at that time, I just realized from the paper that, oh, plants is not just sources of food or raw material, but we can use it as efficient biological system to produce so many things. They grow using sunlight, water, and time. They naturally produce complex molecules. So I began to question why are we relying on expensive control industrial system, big fermenter to make medicine if this plant can produce those kind of things as well?
David Brühlmann [00:00:35]:
What if you could grow life-saving antibodies in a greenhouse instead of stainless steel bioreactors? Professor Waranyoo Phoolcharoen spent years pioneering molecular farming, which means turning plants into biofactories for rabies treatment and COVID vaccines, before co-founding Baiya Phytopharm in Thailand. Today she reveals how her platform produces biopharmaceuticals in weeks instead of months and why Southeast Asia's biotech landscape offers unique advantages, and what pivotal moment pushed her from publishing research to building a clinical-stage company that's redefining pandemic preparedness. Welcome, Waranyoo Phoolcharoen, to the podcast. It's great to have you on today.
Waranyoo Phoolcharoen [00:02:36]:
Hello. Thank you very much.
David Brühlmann [00:02:38]:
Waranyoo, share something that you believe about bioprocess development that most people disagree with?
Waranyoo Phoolcharoen [00:02:46]:
If we think about bioprocess development, one thing that people disagree on is that bioprocess development does not have to take a long time. I think timing is quite important, which is something people often consider, especially for pharmaceutical bioprocess development. This idea likely stems from traditional technology. From my experience with molecular farming and bioprocess development, if you start thinking about the process early—considering manufacturer scalability and downstream constraints from day one—then that should shorten the timeline. I believe the real challenge is not that bioprocess development is inherently slow, but rather that we often treat it as though it must be slow.
David Brühlmann [00:03:37]:
I'm looking forward to this discussion today because you're making a very good point, and we need to find ways to accelerate process development. So take us back to the beginning; what sparked your passion for plant biotechnology, and what were some pivotal moments along your journey?
Waranyoo Phoolcharoen [00:03:57]:
That's a very interesting question. I did not plan to work in plant biotechnology at all. I completed my undergraduate and master's degrees in Thailand. I was interested in science in general; like other students, I just enjoyed learning, but I did not have a clear passion or long-term vision for my career. The real turning point came later during my PhD when I received a scholarship from the Thai government to pursue my PhD in plant biotechnology at Arizona State University. It was not necessarily because this was my dream; rather, it was a requirement of the scholarship.
At the same time, I knew that upon returning to Thailand, I would have to teach at the Faculty of Pharmaceutical Sciences due to this scholarship. I began asking myself the ethical question: what should I focus on to connect plant biotechnology with pharmaceutical science and medicine? With this question in mind, I began to read and search for more research publications. And I came across a scientific paper on molecular farming, which is the idea of using plant to produce pharmaceutical proteins. Then I think at that time, I just realized from the paper that, oh, plants is not just sources of food or raw material, but we can use it as efficient biological system to produce so many things. They grow using sunlight, water, and time. They naturally produce complex molecules.
So I began to question why are we relying on expensive control industrial system, big fermenter to make medicine if this plant can produce those kind of things as well? And at first it's just the field that I had to study, but over time I became more interested in when I saw the result. I saw that we can really make medicine more affordable and easy to bring it to people who don't have access. I mean, this part did not start with big dream, but during my PhD, then I used plant to produce antibody and vaccines for Ebola. And I saw that it really worked in animal model. And later I can see that people use this work to test in human. And I think that experience changed what I believe. It changed how I think because I feel like this is not just publication. It's not just in theory, but we can use it, the plant, to produce something to save people's lives. And I think that is the moment that I saw that this technology have potential in the real world.
David Brühlmann [00:06:31]:
Very exciting. And what I love about your story is that it’s driven by both curiosity and a sense of purpose—making therapies more accessible to more people. I think that's a very important topic, especially in your region. I'm eager to dive into that a bit further later in our conversation. At this point, I'm curious about your journey as you finished your PhD and postdoc. At one point, you had the idea or opportunity to co-found a company. Can you share what sparked this idea and what ultimately made you decide to take that step? Founding a company is quite a leap.
Waranyoo Phoolcharoen [00:07:12]:
Actually, I observed how biotech companies operate while I was in Arizona. I had the chance to work at a biotech company in San Diego, and it was my first exposure to that environment since we don’t have such companies in Thailand. However, I knew I had a scholarship that required me to return to be a professor at a university. After coming back to work at the university in Thailand, I followed what I believed was the right academic path. I worked as a professor, taught students, conducted research, and published papers. On paper, everything looked successful. I secured research funding, and many students contributed to scientific knowledge.
However, over time, I began to feel uncomfortable with this situation. It seemed like all my research ended the same way—with publications. We utilized a lot of research funding, which is public money, and given that Thailand is a low and middle-income country, we don't have abundant resources. This led me to question what tangible benefits our country derives from just publications. I couldn't find a satisfactory answer. Yes, I trained students, and I take pride in that—they went on to secure good jobs, but most of them, let's say none of them, continued in research. It was a simple reality: researchers in our country do not get paid well, and many students end up selling products online, earning more than they would in a laboratory. Accepting this was a hard reality.
At some point, I realized that I needed to do something differently. Publishing papers alone wasn’t sufficient. If this technology truly works, I thought, then I need to take action. Starting the company was an idea we had—it stemmed from wanting to do something different, not out of sheer confidence. When we co-founded Baiya Phytopharm in 2018, our initial idea was simply to commercialize something from our research. We didn't have a clear business plan or roadmap; we were looking to try something new. That decision led us to where we are today.
David Brühlmann [00:09:40]:
When I looked at your website, what stood out was the phrase, "We grow the plant of life." What does this actually mean? Also, can you share with our listeners what kind of plants you're using and how you utilize them to produce medicine?
Waranyoo Phoolcharoen [00:09:56]:
Because the plant of life is not just a metaphor for us, but it's the real way to describe what we do. At Baiya Phytopharm, we use plants as a living system to make medicines. Instead of producing drugs in stainless steel tanks, we can grow them, produce the medicine in the plant cells. And you can think of a plant as a natural factory. Plants already know how to grow quickly. They know how to make complex molecules. And what we do is just give the plant clear instructions, telling the plant how to make specific medical proteins, such as vaccines, monoclonal antibodies. And then for a short period of time, the plant can follow this instruction and produce medicine inside the leaf. And the plant can stay healthy and continue to grow. But during that time, it becomes a biofactory.
And the real advantages of this approach are speed and flexibility. We can go from a gene sequence to producing useful protein in a week, not years. And we don't have to build new factories or redesign the whole system for each new product. The same platform can quickly adapt to medicines for new diseases or new variants. Then we can design the whole process as one system, from how plants grow to how we harvest them, how we purify these medicines. This allows us to meet pharmaceutical quality standards while keeping the benefits of plants, like lower cost and easy scalability.
So when we say that we grow the plant of life, we mean exactly that. We are growing plants to make real medicines—medicines that can be produced faster, more affordably, and closer to the people who need them. The plant is not just a tool, but the foundation of a new way of making medicines.
David Brühlmann [00:11:58]:
When you say plants, this means that you are literally growing the whole plant, not as many people do plant cell cultures, just individual cells in a bioreactor?
Waranyoo Phoolcharoen [00:12:08]:
No, we grow the whole plant.
David Brühlmann [00:12:11]:
And what kind of plants do you usually use?
Waranyoo Phoolcharoen [00:12:14]:
The plant we use is one type of tobacco plant. The scientific name is Nicotiana benthamiana, and it is a species of tobacco that contains a lower amount of nicotine. It is a plant that most plant biologists use in the lab. They use it to study phenotypes and genotypes because it is quite susceptible to Agrobacterium transformation.
David Brühlmann [00:12:38]:
Now, before we dive a bit more into the technology and the science itself, as you were transitioning from a more academic role into an entrepreneurial role, what were some key mindset shifts you had to take in order to succeed in that role?
Waranyoo Phoolcharoen [00:12:55]:
I did not plan to change from scientist to entrepreneur at the beginning. I think I changed over time. And I think the biggest mindset shift is that we moved from just asking simple research questions—we didn’t want our work to end with publication. As professors, we know the pathway: getting grants, doing research, publishing, training students, and so on.
But as an entrepreneur, we have to ask different questions. It’s not just, “Oh, this is interesting and we want to do it.” The mindset comes from asking different questions: Who is going to pay for this? Does it make commercial sense? These are questions I never thought about when I was only a scientist.
I think the biggest shift comes from the questions we ask, because when you have the right question, it leads to the right answer.
David Brühlmann [00:13:56]:
Thinking about whether it makes commercial sense, the question I want to ask is: as you were thinking about this, what were the products that came into your mind?
Waranyoo Phoolcharoen [00:14:09]:
When we started the company, yes, we wanted to make medicines—we wanted to make drugs and vaccines. That’s the goal, because we believe it’s very important. And as a professor in the Faculty of Pharmaceutical Sciences, that’s what we want to do.
But when we started the company, we began with products that could reach the market quickly with lower regulatory barriers. For example, we started producing different types of growth factors that could be sold as raw materials for cosmetic products. The regulation is different compared to vaccines or drugs.
Actually, I learned this from our CEO, who has more experience from a business perspective than I do. What we do together is that I support the technology—what we can do scientifically—while she works on the market size, which products we can realistically bring to market and generate revenue from. The technology and the business side have to work together, and from that, we determine which products we are going to make.
David Brühlmann [00:15:19]:
Translating an innovation or technology can be quite a struggle. I’ve talked to a lot of scientists, and I’ve also been part of technology innovation initiatives. I’d say it’s not only in academia—even in larger corporations, scientists sometimes struggle with this. I would love to hear your perspective.
Based on your journey, what advice would you give to researchers who want to create impact-driven biotech companies, especially in a context like yours, where resources may be limited?
Waranyoo Phoolcharoen [00:15:50]:
I think the first thing I would say is that there are many ways to create impact from research. Building your own company is just one of them. Not every scientist needs to become an entrepreneur.
There are many pathways. You can file patents and license them to other companies, or you can transfer or sell your intellectual property. There are different ways to create impact.
But if you want to build your own company, I think the most important step is to be very honest with yourself. You need to understand what role you can perform well.
In my case, when I started the company, I didn’t have many choices because there was no one else who could take this research to commercialization. That’s why I felt I needed to do it myself. But I also needed to understand what I could do and what I could not do.
For example, I knew I could not be both CTO and CEO. Some scientists can manage both roles, but for me, management, finance, and marketing involve many skills that would take time to learn. That’s why I found a partner—someone who is strong in the areas where I am not. I think that is very important.
Another important lesson is timing. If you wait until you feel completely ready, you will probably never start. You have to begin when you feel unready. In a resource-constrained environment, perfect conditions never exist.
You will make mistakes. You will fail. But speed matters. Move fast, fail fast, and fail forward. Each failure gives you information and lessons learned. You cannot get that from planning alone.
Before I started the company, someone gave me very simple advice. He said, “Be brave.” At that time, it sounded simple, and I didn’t fully understand it. But along the journey, I realized how true it is. You will face many things you are afraid of—regulatory uncertainty, funding gaps, technical challenges, and many other issues.
Courage doesn’t mean you are not afraid. It means you move forward anyway. For me, one of the most important things was simply to start and learn from doing. Learning itself is already a form of impact.
Different countries and regions are different. You need to start, act, and learn from your own environment.
David Brühlmann [00:18:39]:
Yes, I love that. What I’m hearing are three things:
I would love to hear your perspective and also for you to tell our listeners more specifically about the landscape where you are building your company—in Thailand. You studied in the United States, and many of our listeners are from Europe and the U.S. They may not be very familiar with the scientific and technological landscape in Southeast Asia.
Could you paint a picture for us of what research looks like in Thailand, and how the pharmaceutical industry operates there and more broadly across Southeast Asia?
Waranyoo Phoolcharoen [00:19:27]:
I think Southeast Asia has an interesting and often misunderstood biotech landscape. It is not yet a global biotech hub like Boston or California, but it is certainly not an empty space.
What we see today is a region with strong scientific talent and growing infrastructure, but still relatively immature in terms of the translation ecosystem. In countries like Thailand, Singapore, Malaysia, and Indonesia, there are many excellent academic researchers, strong clinical talent, and increasing government investment in the life sciences.
However, the systems that connect discovery to commercialization—such as venture capital, experienced biotech operators, contract development and manufacturing organizations (CDMOs) at scale, and advanced laboratory know-how—are still developing. This gap creates both challenges and opportunities.
From the opportunity perspective, Southeast Asia has real unmet medical needs, especially for infectious diseases and biologics that are either too expensive or not prioritized by Western markets. This creates a strong case for locally developed, cost-effective biologics. We are also close to diverse patient populations and regional clinical sites, which is valuable for translational and clinical research.
Another advantage is the cost structure. Biotech is never cheap, but building R&D and manufacturing capacity here in Southeast Asia can be significantly more cost-efficient than in the U.S. or Europe. If you design the process carefully, this is especially important for technologies like molecular farming, where scalability and cost of goods sold matter from the beginning.
At the same time, the challenges are real. Capital is more limited here. Investors tend to be more risk-averse when it comes to deep-tech biotech. We also have fewer people with experience in taking biologics from the lab through clinical development and into regulatory approval.
As a founder, you are not just building a company—you are also helping to build the ecosystem around it. You need to develop talent, partnerships, regulatory pathways, and even public trust. Education is part of the work as well.
These are both challenges and opportunities.
David Brühlmann [00:22:20]:
Yes. And if I may add to that—something you said, Waranyoo, about cost-effectiveness being very interesting in Southeast Asia—I can confirm that. Recently, I’ve done a lot of research in the region regarding CDMO capabilities, and there are increasingly more excellent CDMOs in Singapore, Thailand, Malaysia, and even Vietnam.
There is a lot happening in Southeast Asia. I agree with what you’re saying—it is often misunderstood. It’s important to raise awareness that the region has a strong competitive advantage and is evolving very quickly.
Waranyoo Phoolcharoen [00:23:02]:
Yes, and I think now more people are starting to realize that. I see more companies from other regions looking toward Southeast Asia.
David Brühlmann [00:23:14]:
This wraps up Part 1 of our conversation about molecular farming. We’ve explored how Waranyoo transformed academic breakthroughs into Baiya Phytopharm’s commercial endeavor, how molecular farming addresses structural limitations of closed production systems, and what building biotech in Thailand reveals about emerging markets.
In Part 2, we’ll examine the platform’s plug-and-play capabilities, how they achieved Asia’s first plant-derived COVID-19 vaccine to enter clinical trials, and the development of a GMP manufacturing facility for pandemic response.
If this resonated with you, please leave a review on Apple Podcasts or your favorite platform and share it with a colleague. Thank you so much for tuning in today, and I’ll see you next time.
All right, smart scientists—that’s all for today on the Smart Biotech Scientist Podcast. Thank you for joining us on your journey to bioprocess mastery. If you enjoyed this episode, please leave a review on Apple Podcasts or your preferred podcast platform. By doing so, we can empower more scientists like you.
For additional bioprocessing tips, visit smartbiotechscientist.com. Stay tuned for more inspiring biotech insights in our next episode. Until then, let’s continue to smarten up biotech.
Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.
Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call
About Waranyoo Phoolcharoen
Waranyoo Phoolcharoen is a plant biotechnology scientist, entrepreneur, and professor at Chulalongkorn University. She co-founded Baiya Phytopharm in 2018 to translate molecular pharming research into scalable biopharmaceutical solutions, using plants as biofactories to produce medicines for infectious diseases such as rabies and COVID-19.
Dr. Phoolcharoen holds a B.Sc. in Biochemistry from Chulalongkorn University, an M.Sc. in Molecular Genetics and Genetic Engineering from Mahidol University, and a Ph.D. in Plant Biology from Arizona State University. Alongside her academic work, she leads innovation at Baiya, advancing plant-based pharmaceutical manufacturing while mentoring the next generation of scientists in Thailand.
Connect with Waranyoo Phoolcharoen on LinkedIn.
You may also enjoy exploring these additional conversations from the podcast, featuring ideas, insights, and perspectives across biotechnology and innovation.
Episodes 141 - 142: How Microalgae Cuts Antibody Costs by 70% and Redefines Biomanufacturing with Muriel Bardor
Episodes 163 - 164: How Moss Enables Production of Unproducible Protein Therapeutics with Andreas Schaaf
Episodes 229 - 230: Cyanobacteria Biomanufacturing: Achieving Carbon-Neutral Production at Lower Cost Than Fermentation with Tim Corcoran
David Brühlmann is a strategic advisor who helps C-level biotech leaders reduce development and manufacturing costs to make life-saving therapies accessible to more patients worldwide.
He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.
Hear It From The Horse’s Mouth
Want to listen to the full interview? Go to Smart Biotech Scientist Podcast.
Want to hear more? Do visit the podcast page and check out other episodes.
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