Carbon neutrality pledges echo across the biopharma industry, but the question lingers: how do you actually measure and shrink your true environmental impact, when most data is missing and every facility operates on a different baseline?

In this episode from the Smart Biotech Scientist Podcast, David Brühlmann welcomes Niklas Jungnelius, a veteran in process modeling and sustainability at Cytiva, who’s spent years uncovering what really drives emissions—and how small process changes can have outsized effects.

Key Topics Discussed

• Challenges biotech companies face in accurately measuring and defining their carbon footprint, and how this shapes sustainability strategies.
• Adapting bioprocessing approaches based on local resource availability, such as balancing water use and energy demands.
• Understanding why emissions from production processes may outweigh recycling efforts and exploring strategies to mitigate them.
• Using modeling tools during development to optimize both economic performance and environmental outcomes.
• Evaluating the pros and cons of relying on historical data versus simulation-based insights for emerging manufacturing approaches like AI-driven or continuous processing.
• Identifying less obvious but potentially more significant environmental drivers in biomanufacturing sustainability.
• Assessing the influence of upstream and vendor-related emissions on achieving carbon neutrality goals.
• Leveraging process modeling to choose fit-for-purpose technologies and anticipating disruptive innovations such as intensified or cell-free processes.

Episode Highlights

• Understanding life cycle assessment and the key damage categories in environmental sustainability—including carbon emissions, water usage, and resource depletion. [00:00]
• The challenge of defining carbon emissions baselines and why it’s harder—and often more expensive—to achieve deep reductions if your operations already use clean energy sources. [03:06]
• The impact of production scale, consumables, and obscure chemicals on the overall environmental impact—and how these surprises can shift sustainability strategies. [05:54]
• How to start monitoring and modeling environmental impact in process development and manufacturing. [08:00]
• The importance of involving manufacturing perspectives early in process development, and choosing the right level of detail and ambition for process modeling. [08:18]
• There’s no one-size-fits-all in manufacturing technology—whether fed-batch, continuous, or hybrid—and decisions must fit each organization’s needs, resources, and ambitions. [10:13]
• Industry trends that could transform the field, from intensified fed-batch production to future technologies like cell-free expression systems. [11:22]
• Why understanding individual circumstances is crucial for making smart choices in sustainable and economic bioprocessing. [12:22]
• Where to connect with Niklas for further questions or collaboration. [14:03]

In Their Words

Episode Transcript: Process Economics Decoded: How to Model Biomanufacturing Costs From Clinical to Commercial Scale - Part 2

David Brühlmann [00:00:45]:
Welcome back. In part one, Niklas Jungnelius opened our eyes to the hidden economics of bioprocessing. Now, in part two, we’re shifting gears to tackle the elephant in the room—sustainability.

How do you actually quantify environmental impact? What’s stopping biotech from hitting those ambitious carbon-neutral targets? And with AI and continuous manufacturing changing the game, how do you model technologies that barely have historical data? Niklas brings his process modeling expertise to answer these burning questions. Ready to future-proof your bioprocessing strategy? Let’s go.

I’d also like to focus on another part. Obviously, process economics is important. The other key area is the environment. Many leading biopharma companies have set ambitious sustainability goals—being carbon-neutral by 2030 or 2040, depending on the context. What are the biggest technical and economic hurdles preventing biotech companies from reaching these goals?

Niklas Jungnelius [00:03:06]:
That’s an interesting question. I think if we focus on the relative targets that many companies have set—such as an 80% to 90% reduction in CO₂ emissions compared to a given baseline year—it really depends on what your baseline is.

And that’s not as easy to determine as it sounds, because there’s still a lot of missing data. When trying to assess your true carbon emissions, we often have to make assumptions, and over time we’re getting more and more accurate data. So things may shift slightly—it’s somewhat of a moving target.
But the baseline largely determines what your viable reduction options are. For example, if your baseline situation involved heavy use of fossil energy in your operations, that will have a very high impact on your carbon footprint. In that case, the most obvious way to reduce emissions would be to switch to renewable energy sources, which can make a huge difference in your CO₂ footprint and substantially cut emissions.

On the other hand, if your manufacturing facility was already using renewable energy in the baseline year—say, in Switzerland, for example, where I know, David, that a large portion of the electricity grid is renewable—you already have a cleaner baseline profile. But that also means it’s much harder to achieve those 80–90% reductions.

So you’ll need to focus more on other factors—typically consumable-related emissions. Those are your Scope 3 emissions—the emissions you’re not directly responsible for, but that come from your supply chain and vendors.

As a supplier to the biopharma industry, Cytiva has to work extensively not only to introduce new, more sustainable products with lower carbon footprints, but also to reduce the emissions of existing products. Our customers can’t simply replace every product in their process to make it more environmentally friendly.

So if we, on our end, can reduce emissions from existing products—by, for example, switching to renewable energy, working closely with our suppliers, or identifying alternative raw materials—we can significantly help our customers reach their sustainability targets.

David Brühlmann [00:05:33]:
If we look at the consumables or raw materials we’re using, what comes to mind is obviously single-use plastics—that’s where a lot of the CO₂ footprint lies. But biopharma also uses a lot of water. Are these really the main drivers, or not? I’m curious—what are the real drivers?

Niklas Jungnelius [00:05:54]:
I think it depends on which damage category you’re looking at, because when you perform a life cycle assessment (LCA), you evaluate several different impact categories.

There are many aspects of environmental sustainability — perhaps the most important one at this point in time being carbon emissions. But if you’re producing your product in a region facing water scarcity, then water conservation becomes a key focus area, since our industry is highly water-intensive.

Whereas if you have plenty of water available, you might focus less on that. Then you also have factors like resource depletion — how many resources are you consuming in your process?
If we stay with carbon footprint for a moment, I think that’s a great point — it’s top of mind for most people. It’s very obvious, with all the single-use plastics generated in our processes, that consumables are a major focus area.

However, I would argue that based on the data we have today, our main focus shouldn’t necessarily be on recycling. Even though it’s tempting — and very visual — to focus on those piles of plastics, the relative benefit from recycling, compared to emissions generated during production, is actually quite small.

Also, because biopharma is a relatively small global industry, we face logistical challenges — such as transport emissions — in the recycling chain for these materials.

In contrast, during the production phase, we have large waste streams, and manufacturing in cleanrooms is highly energy-intensive. I think that’s where we’ll find our true hotspots.

And one thing I should add about environmental sustainability is that it often surprises people when they conduct an LCA and discover what the real impact drivers are. Sometimes it turns out to be a single, obscure chemical you’d never expect — yet it has a disproportionate environmental impact. If we can eliminate or replace that chemical, it can make a huge difference to the overall sustainability of a product.

David Brühlmann [00:08:00]:
Let’s get tactical here — some of our listeners working in process development or manufacturing might be thinking, “That’s great, I want to monitor this, but where do I start?” Can you give some advice on how to begin and how to measure these key parameters?

Niklas Jungnelius [00:08:18]:
I think there’s a lot of potential to work more with process modeling. We’re seeing many large biopharma companies now integrating process modeling early in development — to design smarter, more efficient processes.

One key principle is to think manufacturing from the start. In process development, the time horizon is often limited — especially if you’re a startup without the resources or expertise to fully map your future manufacturing process. But starting with the end in mind — including commercial-scale production — leads to better decisions along the way.

You also need to define the scope and ambition level of your modeling. What benefits do you want to achieve? How much effort is it worth investing at different stages?

Should you model individual unit operations or entire processes? That may depend on whether you already have a platform process.

The level of detail in your models determines how you structure your organization. If you want broad adoption — for example, having people in every PD or MSAT lab trained on process modeling — then the models need to be relatively simple.

But if you want high accuracy and detailed parameter tracking, you’ll likely need dedicated experts who work with process modeling daily. It’s difficult for someone to stay up-to-date with all inputs and assumptions if it’s just an add-on to another role. So for higher precision and more robust results, it’s worth having a few specialists focus on process modeling full time.

David Brühlmann [00:10:05]:
Niklas, what burning question haven’t I asked that you’re eager to share with our biotech community?

Niklas Jungnelius [00:10:13]:
I’d say that there’s no single manufacturing technology that’s superior in every situation. It really depends on your inputs and assumptions.

For example, if you compare fed-batch with continuous manufacturing, the outcome changes drastically depending on the starting titer. If you double the titer, that could make or break the business case entirely.

So asking, “What’s the best manufacturing technology?” is a bit like asking, “What’s the best way to get to work?” The answer is always — it depends. It depends on your traffic, how far you live, what transportation options are available, and how much you’re willing to spend on commuting.

Similarly, in manufacturing, understanding the implications of each option helps you make the best decision for your specific needs. Process economic modeling can guide you toward the manufacturing strategy that best aligns with your individual objectives.

David Brühlmann [00:11:12]:
And if we look ahead, Niklas, is there any emerging trend in bioprocessing that could completely change our models or assumptions?

Niklas Jungnelius [00:11:22]:
I think what’s shifting now is how we work with technologies like intensified fed-batch, where productivity in batch bioreactors increases by front-loading the cell expansion phase.

As I mentioned, titer is a key parameter here — and these improvements can actually shift the balance back toward batch manufacturing in certain cases. We’re also seeing hybrid processes — for example, perfusion bioreactors combined with batch downstream processing.

Looking further ahead, we might see new manufacturing technologies such as cell-free expression systems. If we’re talking about transformational change, that’s where it could happen — but those technologies are still quite uncertain and varied, each requiring significant optimization for specific manufacturing contexts.

David Brühlmann [00:12:13]:
We’ve covered a lot of ground today. From everything we’ve discussed, what’s the most important takeaway you’d like listeners to remember?

Niklas Jungnelius [00:12:22]:
From my perspective, it’s about understanding that depending on your focus areas, prerequisites, and ambitions, different solutions will suit your manufacturing process differently. And perhaps, David, I’ll turn the question back to you — have you learned anything today that you think could be useful in your work as a strategic advisor to the biopharma industry?

David Brühlmann [00:12:48]:
Absolutely — that’s a great question, and I like it. One thing I’ve learned is that there’s really no one-size-fits-all solution. It depends on your scale and on the phase you’re in — whether you’re still in the clinical stage or moving closer to commercial manufacturing. The choices you make will differ greatly depending on that context — for instance, whether you opt for single-use systems versus stainless steel, or for smaller versus larger-scale operations.

Another important factor is your modality — ultimately, the volume required and the process productivity determine what’s most suitable. As you said, Niklas, it’s critical to consider these parameters right from the start. Ideally, you aim for as high productivity as possible in your process, because that’s where you can gain a lot — in both time and cost savings.

Niklas Jungnelius [00:13:40]:
Thanks a lot, David. That’s a very good answer — I’m very happy with that.

David Brühlmann [00:13:46]:
That’s great — I passed the test!

Niklas Jungnelius [00:13:48]:
Yes, you did!

David Brühlmann [00:13:51]:
This has been fantastic, Niklas. Thank you for your insights — and for that thought-provoking question at the end. I loved it. Where can people reach you if they’d like to connect or learn more?

Niklas Jungnelius [00:14:03]:
The easiest way is to connect with me on LinkedIn. Perhaps you can include the link in the podcast notes.

David Brühlmann [00:14:09]:
Sure — we’ll do that. Just check out the Smart Biotech Scientist show notes for this episode. You’ll find Niklas’s contact information there. And please, take the opportunity to reach out to Niklas with your process modeling or bioprocess optimization questions. And once again Niklas, thank you so much for being on the show today.

Niklas Jungnelius [00:14:26]:
Thank you so much, David. It's been a pleasure and happy to connect with anyone who wants to discuss more about this very interesting topic.

David Brühlmann [00:14:34]:
This wraps up our conversation with Niklas Jungnelius from Cytiva. From quantifying environmental footprints to navigating emerging technologies, Niklas has given us a true masterclass in thinking beyond just cost of goods. Remember — every process decision you make today shapes both your economics and your environmental impact tomorrow.

If this episode sparked new ideas, do us a favor and leave a review on Apple Podcasts or your favorite podcast platform. Your feedback helps us serve you better — and thank you for tuning in! 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 joining us on your journey toward bioprocess mastery. If you enjoyed this episode, please leave a review on Apple Podcasts or your preferred podcast platform. By doing so, you help us empower more scientists like you. For additional bioprocessing tips and insights, visit us at www.bruehlmann-consulting.com

Stay tuned for more inspiring biotech conversations 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.

Next Step

Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call

About Niklas Jungnelius 

Niklas Jungnelius serves as Process Modeling Leader at Cytiva, guiding biopharmaceutical manufacturers, industry groups, and internal stakeholders in evaluating the impact of various process technology options. His work supports organizations in making strategic choices that enhance process efficiency, productivity, and environmental performance.

Niklas earned his master’s degree in Chemical Engineering from Chalmers University of Technology and has more than 25 years of experience in the life sciences sector, including over a decade in strategic roles at Cytiva and GE Healthcare.

Connect with Niklas Jungnelius on LinkedIn.

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

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