Many biotech teams are sprinting to create breakthrough therapies, but often encounter the intricate and numerous challenges of CMC development.

As the industry advances the frontiers of cell and gene therapies, distinct analytical and manufacturing obstacles are emerging—far more complex than those faced with traditional biologics. To succeed, companies must embrace new approaches that balance scientific precision with commercial practicality.

In this episode from the Smart Biotech Scientist Podcast, David Brühlmann meets Daniel Galbraith, Chief Scientific Officer with Solvias, a Swiss-based global CRO providing analytical services for small molecules, biologics, and cell and gene therapies.

Key Topics Discussed

• Comparing cell and gene therapy progress with monoclonal antibodies.
• Unique testing and characterization issues in advanced therapies.
• How biosimilars changed analytical and regulatory strategies.
• Lasting effects of pandemic-driven collaboration in biotech.
• Key traits for today’s biotech Chief Scientific Officers.
• Choosing a CRO – Criteria for selecting strong analytical support partners.
• CRISPR breakthroughs, ADC growth, and mRNA overhype.

Episode Highlights

• Why cell and gene therapies face unique challenges compared to the progression seen with monoclonal antibodies [03:04]
• Daniel’s career path: from entering biotech in 1996 to CSO at Solvias, and the rapid evolution of the industry [05:00]
• The analytical hurdles in characterizing cell-based products and how their inherent variability impacts development [09:46]
• Approaches to analytical method requirements for autologous cell therapies, and how data is gathered iteratively in these cases [13:02]
• The biggest obstacles to scaling up cell and gene therapies, and why innovative cell manipulation technologies are needed [16:06]
• Current trends in therapeutic modalities: why antibody-drug conjugates stand out, and whether mRNA therapies are losing momentum [18:37]
• Practical advice on choosing an analytical CRO as a strategic partner—what to look for, what questions to ask, and why enthusiasm and standardization matter [21:55]

In Their Words

As a CRO, you want to be as excited, you want to be part of that journey with them. And I think that's something that I would say, you want to get a sense that these people have a commitment. They want to spend time talking about your product, listening about your product. If they're not willing to do that at the start, they definitely aren't going to be willing to do that later on. So get people that are excited and want to hear about your product and willing to listen.

Now, in our practical side of things, there's a couple of things. Everybody thinks the product is unique, but there are some common features of products. So you want to know that you'll spend time and effort looking at the unique part of your product, but there's also an ability to actually a lot of the routine stuff can be done very quickly and easily. We're not reinventing the wheel for every single aspect of the characterization you need to do for your products.

Episode Transcript: Mastering CRO Selection: Essential Questions for CMC Analytical Development - Part 1

David Brühlmann [00:00:53]:
Are you struggling to find the right analytical strategy and partner for your CMC development? You are not alone. Many biotech teams waste months over engineering methods or partnering with the wrong CRO.

Today I'm joined by Daniel Galbraith, who is the Chief Scientific Officer at Solvias, who has guided analytical development for nearly three decades. In part one, we'll uncover his journey, the biggest industry shifts and critical techniques for safer cell and gene therapy development. I'm David Brühlmann. Welcome to the Smart Biotech Scientists Podcast. Let's dive in.

Welcome, Daniel, to the Smart Biotech Scientist. It's good to have you on today.

Daniel Galbraith [00:02:53]:
Thanks very much. Lovely to be here. Thanks.

David Brühlmann [00:02:55]:
Daniel, share something that you believe about bioprocess development that most people disagree with.

Daniel Galbraith [00:03:04]:
So you're asking me to be controversial. I like it just as a kickoff. One thing that I think in bioprocessing, if I look at specifically cell and gene therapy at the moment, everybody seems to think that it will follow the same path that monoclonal antibodies took 30 years ago. Monoclonals are very specialized, difficult to manufacture. And over a period of time, we gradually got better and better. And now we have huge scale and it's relatively cheap to produce. And we have that all over the world, really. And everybody seems to think that cell and gene therapy is going to follow that same path, but I'm not sure that's true. I think we've still got a long way to go before we've got these products that are going to be as scalable and manufacturable, if that's a word, as monoclonals. I'm a little bit nervous that people are very optimistic about it following the same pathway as mAbs. I think we've got a number of innovative processes to develop before we get anywhere near that. So I'm a little less optimistic than a lot of people on that one.

David Brühlmann [00:04:06]:
Well, this is a valid point, Daniel, because advanced therapies are much more complex than traditional biologics. So I think there's things that will translate over. But there are unique challenges that we have not seen in the biologic space. So also curious to see how this will play out.

Daniel Galbraith [00:04:26]:
There's a lot of pressure. You can see that in the market, the conferences. Everybody talks about scalability and making this cheaper, cost of goods, all of that. So there is a lot of pressure. Just don't know if we'll got the tools quite yet to be able to get there.

David Brühlmann [00:04:40]:
Before we dive deeper into the science, let's talk about yourself. Daniel, draw us into your fascinating journey from starting your career to now becoming the chief scientific officer at Solvias. What initially drew you into biotech and what were some interesting pit stops along the way?

Daniel Galbraith [00:05:00]:
Yes, interesting. Yes, long career. It's gone so fast in many ways that you think when people ask you that question, you've been in a long time, you think, I've not really. But then I started actually in 1996, actually in biotech, which is almost 30 years. Next year will be 30 years. What drew me into it was that mid-1990s period you started to get the approvals of the first real biologic monoclonal drugs, they were starting to kind of come.

The regulators were getting interested in putting regulations in place. So it really was that there was an inflection point definitely there where there was these new drugs were coming, different challenges. As I said earlier, they were difficult to produce in those days. They were expensive to produce, it was small batches, all of that thing. But they presented a lot of challenges in how to characterize them, how to make them safely. What were the risks? What were the first time we're making products really in cells? What were the virology risks? What were the bacterial contamination risks? How do we characterize them?

So that's what kind of started me off, starting to look at these drugs. It was novelty, it was new. And people that are attracted to the new. Along the way, there have been other things that have happened. We started off with them being every product was unique. And then all of a sudden, in the 2000, mid-2000s, 2005, 2008, we started to look at biosimilars. You know, all of a sudden we could make a copy of these drugs. And then the analytical challenge is with this unique product process, how did we make a copy of that with another product process? So then the analytics started to get more complicated again. This time we were using different technologies to look at these drugs. So again, that was really interesting, looking at that different aspect of it.

And then more recently, we've started seeing cell and gene therapy. And you know, just around pre COVID, the COVID time, two things happened. We saw what we could do as an industry around COVID. And I thought that's fascinating. We really put our mind to it as an industry. Sometimes I think we've forgotten very quickly what we managed to do during that COVID period. So that was. It keeps you very interested. When it is an industry, we can rise to that challenge. Along with that, we've seen the advent and the approval of so many cell and gene therapy, mostly autologous drugs, but a lot of drugs that can cure diseases that when I started, we thought we would never have a chance of curing, like sickle cell disease, all of these kind of conditions.

Now that we've got approved drugs for, that keeps you interested, that you can't fail to be interested when you're meeting a medical challenge like that. I'm not on the clinical side of things, obviously I'm more on the manufacturing side. But you're part of that journey. You're an important part of that journey. And to still be able to at least contribute even to a small extent, I think in that journey is it keeps you interested and it's also what's next? From when I started out in ‘96 and 2005, you've seen such huge changes now and you think, Well, another five years, where are you going to be now? So you're always looking to the future. I feel keeps you young.

David Brühlmann [00:08:06]:
I hope it's evident that you are curious and you've been very excited about all these amazing changes over these last 30 years. What was that spark that drew you eventually into a leadership position and now the CSO of quite a big company?

Daniel Galbraith [00:08:21]:
I think you have the scientist role, which is that technical role and understanding what’s going on. But I think you need a little bit of that entrepreneurial spirit — that interest in kind of going, “What’s next? What can we improve? What can we make better?”

And I think that’s where the CSO role comes in. I don’t think of it solely as a purely technical role. Obviously, you have to have that technical background, because that’s really where the vast majority of what you do is. But you also need to think: how does it work as a business function, as well as a technical function?

I think your job is to inspire. That’s really what made me want to move into a more leadership role — that ability to get people excited about the science, to get people excited about what we can do. If you can do that, either internally with your own company or externally to match the excitement that these innovator companies have with new drugs, I think that’s what makes you ready to be in that leadership role. Inspiring the science is really what I think of with that. I’m not saying I’m great at it, but I feel like I can help with that.

David Brühlmann [00:09:28]:
And with respect to the cell and gene therapies, as you said, we are now able to treat sickle cell disease and a lot of other diseases we previously thought it would never be possible. What are the specific analytical challenges we are now seeing with these new modalities?

Daniel Galbraith [00:09:46]:
That keeps you young as well. We’re trying to tackle some of these challenges. So when we think about these products, we’ve got cells, essentially, and cells are a population — they’re not all the same. Essentially, what we’re trying to do with the analytics is actually come up with some sort of measure on a population. And that’s, for number one, an analytical challenge: how do you characterize a population?

It’s different when you’re characterizing a batch of proteins or a molecule, a drug like aspirin or something, where everything is expected to be the same. With these products, we expect everything to be different — all of the cells will be slightly different in some way. So we need to sort of make an average or make a summation of what’s going on there.

At a fundamental level, we have to just think of these products differently. We can’t expect them to behave or to be measured in the same way that we would measure a monoclonal antibody. Even so, we have to bear that in mind.

I think also, cells don’t just have one activity — they do lots of different things, especially when we’ve manipulated them. Normally, we’ve inserted a gene or modified a gene or something like that — something has happened. We’ve upset them, we’ve upset their DNA in some way, usually to make them do something different. And cells will respond in different ways to that.

In some cases, in some of the CAR-T therapies, we can see adverse effects once we’ve manipulated them in certain ways. So we need to be able to measure that, to understand what the negative things could have been. Sometimes the cells will die; sometimes they’ll grow in a particular way.

The summation of all of these changing things means that, analytically, we have to apply techniques that can make an estimation of what’s going on. We need to understand that they’ll change over time — because if you take a sample on day one and then look again on day two, day three, or day ten, you expect change. The cells will grow, divide, or do something.

What are we doing, when are we doing it, and what parameters are we putting on there? What specifications do we want to put on there? Understanding what makes a good batch and what makes a not-so-good batch is a big challenge, because normally we’re dealing with really small patient batches. When I say “patient batches,” I mean the number of patients we treat — you might only be making ten batches for ten patients. So we don’t have a big population of batches to be able to make a specification. We need to understand that as well. The challenges are multiple, on different levels: what we’re measuring, how we’re measuring it, when we’re measuring it — and then, once we have measured it, how we’re determining what’s good and what’s bad.

David Brühlmann [00:12:26]:
And one major difference I see also between traditional biologics and cell and gene therapy is in certain scenarios, especially in the cells therapy side, you don't have the classical clinical study progression because you have a patient population of one, obviously. So how does this play out now when it comes to the requirements with respect to analytical methods? Because usually when we talk about biologics, we have a phase appropriate approach. Do we still see something similar on the cell and gene therapy side or how is this adapted?

Daniel Galbraith [00:13:02]:
To some extent, we do. I mean, the difference between what I would call autologous therapies compared to other therapies is really quite important, because you’re absolutely right — if we’re making one product for a particular patient for treatment, we have to consider that differently from what we would do for a product that we can give to multiple people, all of those sorts of things.
But just to take the autologous therapies — because those are the most common ones that we have at the moment that are out there and approved — we have to understand what the mode of action of the drug is intended to do.

So, you can just use the CAR-T therapies to start with. Essentially, they will express something on the cell surface — that expressed molecule on the surface will go in, make some interactions, and then, obviously, lead to a treatment outcome that results in an improvement in the patient’s condition.
Each batch, as you say, is patient-specific. So how do we do that? Essentially, we then look at an empirical level: do the cells express enough of this protein that we think will be clinically able to achieve a change in the patient that will lead to an improvement?

And I think that’s where you have to look at historical data — things that are published in the literature — and actually see if, in the past, when we’ve seen this level of expression of this type of protein, we’ve also seen an improvement.

For early-stage clinical trials, we’re really looking at historical data, and that’s all we can go on. Usually, the regulators would expect you to be able to reference other clinical trials that have shown that a certain level of expression of a particular molecule can achieve the treatment effect we’re looking for.

For these autologous therapies, we’re really just measuring the amount that’s there and then looking back and asking, is this good enough? As things move forward and they treat more and more patients, they gather enough data to say, “When we saw this amount of expression, we saw an improvement in the patients.” Gradually, they build up more and more information that way.

It’s really a step-by-step process, and they can slowly introduce more specification within it. It’s not — I wouldn’t say — in the same way that we would see for traditional biologics, where you have a phase one kind of validation and characterization of the assays, then phase two, phase three, and finally commercial release. You don’t have that. It’s more of an iterative process with autologous products, where they gradually see what works and what doesn’t, and they introduce changes that way. That seems to be the way they move with those ones.

David Brühlmann [00:15:36]:
We know that in the cell and gene therapy we have one big challenge. It's the cost, and we have amazing therapies, but only few people can access them today. So my question now, Daniel, is what technologies do you see that us make better therapeutics faster, cheaper, and perhaps even if we talk about allergenic, perhaps even scale to bigger scales, what do you see coming there?

Daniel Galbraith [00:16:06]:
One of the things I mentioned at the start was that, I mean, I think we still need some innovation in this space. I think we definitely do, because from what I’ve seen, it’s a tough nut to crack — making things to the same quality, to that high specification that we have for patient safety.

We have seen some products coming through. When we look at gene therapies and cell therapies that are using viruses to manipulate the cells and actually create the product, those are quite challenging to scale on an individual basis — really, just because of the vectors that we’re using.
So I think, if we’re looking much further into the future, we need to find methods that can manipulate the cells using techniques that don’t rely on some of these very expensive vectors that are currently part of the manufacturing process. I think we need to solidly look at that.

Now, there are some people using CRISPR technologies to modify the cells that way, but the efficiency of those — and the side effects and issues around using CRISPR — are still challenges. So I think we probably need some innovation in that space, to find a way to manipulate the cells in a more efficient way before we can properly scale these.

There are a number of techniques we can use to scale the amount of cells we produce — and that’s been around for quite some time. But to me, it’s more in the manipulation of the cells that actually create the gene therapy where we need to focus.

There are some innovative technologies looking at different ways of manipulating the cells to make them more receptive to the DNA being inserted or modified, or whatever the change may be. These are very early-stage techniques — not really taken into the clinic yet — but I think in the next few years, if we can get around that issue, the scaling of the cells themselves shouldn’t really be a problem for us.

We’ve got so much expertise within many companies looking at cells and how to grow them. The media we use to grow the cells, how we harvest them, and how we characterize the cells — all of that is already there.
But to me, the first step we need to get better at…

David Brühlmann [00:18:27]:
And which therapeutic modalities are the most popular right now? Which of those you think will gain momentum and perhaps other ones are maybe overhyped?

Daniel Galbraith [00:18:37]:
If you look across all modalities, everyone’s getting very excited about the peptides and what peptides can do. There’s obviously a big push in that direction. Looking at the biologics space, the antibody–drug conjugates (ADCs) over the past couple of years seem to have really come to the fore. The opportunities these are presenting — the payloads, the linker technology — have improved so much. There’s now a lot more choice, and many more manufacturing sites are able to handle these toxic compounds.

A lot of antibodies are also being repurposed — used as these antibody–drug conjugates rather than just as antibodies themselves. Another interesting development we’re seeing is that ADCs are being used in combination with other therapies as well — traditional chemotherapies, radiotherapies, and biologics. It’s really quite exciting to see these combinations of therapies coming together from that point of view.

Now, not to say they’re overhyped — I wouldn’t say that — but I do think ADCs still have a long way to go. Financially, a lot of companies see them as commercially viable, with a strong return on investment. So, in the biologics space, I’d say that’s probably the most exciting area right now.

On the other hand, one thing that seems to have gone a bit off the boil is some of the mRNA technologies. They were very exciting during COVID — seeing the opportunities that these mRNA vaccines presented. Before COVID, only a couple of companies were really interested in this technology. Then suddenly, everybody — all of the large pharma companies — had RNA as part of their portfolio.

That does seem to have cooled off a bit. Maybe we just need to see a bit more investment, a few more successes, and it might come back. But it’s been a little disappointing not to see a couple of blockbuster examples really showing what mRNA technologies can do.
Everyone still seems to be working on it, but progress has probably been a lot slower than expected, especially after what we saw with COVID and the opportunities that came out of the vaccine programs.

I guess now, because we’re moving away from the pure vaccine use of these technologies into other treatments, it’s taken an unexpectedly long time. It was probably a little bit overhyped — as you suggested — how quickly some of these could come through.
But overall, I’d say the ADCs definitely look like a great opportunity area.

David Brühlmann [00:21:09]:
On the podcast, we have covered and talked about choosing a CDMO several times already, but we have never had the opportunity to talk about an analytical partner, a CRO, which also can be or in oftentimes is a strategic partnership. So I would like to know a bit more about that. How to make the best decisions, how to choose the right partner.

Let's assume I am the CEO of a biotech startup and I need analytical support because we're lacking certain analytical methods. So when selecting an analytical partner, what are the critical questions I should ask to ensure that the collaboration will be successful?

Daniel Galbraith [00:21:55]:
You make a very good point. This product that you’re making as a manufacturer is the most precious thing you have — and you’re handing it over to someone in a CRO to analyze it, characterize it, and then produce reports that you’ll take to the regulators to get approval to move on to your next stage of clinical studies, or to get approval to make it a commercial product.

So this is really important — it’s your baby, really. You’re absolutely right: choosing the right partner from that respect is crucial. Now, there are a few aspects that, as a CEO, you’ll be interested in. One is: can they meet the timelines that we have for getting into the clinic and doing all the things we need to do? Can that partner meet those timelines? Does the company have the right expertise? Have they worked with these types of products before? Sometimes you do get very unique products where, with all due respect, nobody’s really got that specific expertise. But do they have the mindset — the inquiring mindset — to be able to work on your product and take an interest in it?

And I think that’s maybe one of the softer things to ask, and it’s more of a feeling: do they get excited about your product in the same way that you do when you describe it? I’ve been in many meetings — and I love being in these meetings — where the drug company is telling you about the patients they want to treat, about what this new drug will do and how much it will improve these patients’ lives. It’s lovely to hear that. And as a CRO, you want to be just as excited — you want to be part of that journey with them.

That’s something I’d emphasize: you want to get a sense that these people have commitment, that they want to spend time talking about your product and listening to you. If they’re not willing to do that at the start, they definitely aren’t going to be willing to do that later on. So, get people who are excited, who want to hear about your product, and who are willing to listen.

Now, on the practical side of things, there are a couple of points. Everybody thinks their product is unique — but there are some common features across products. You’ll spend time and effort looking at the unique part of your product, but there should also be an ability to handle a lot of the routine work quickly and easily.

We’re not reinventing the wheel for every single aspect of the characterization you need to do for your product. There are some off-the-shelf solutions that can give you quick and easy answers to certain questions. Ask those questions: What can you do for me quickly? What’s going to take time? Get an understanding of that — because not everything is difficult, but not everything is easy either.

So, where can I save time? Where can I save money by using existing expertise, so we don’t have to re-develop every analytical technique? There should be a lot of standard things the CRO can offer. Then, once you understand that aspect, you can look at what resources they need to put toward your product — to characterize it, to make it unique — and understand what they can do there.

Those are probably the key things you want to think about. There’s also some basic stuff — the GMP quality, the quality systems, the SOPs, all of the procedures. You want to make sure all of those are in place. But those should really be table stakes. You shouldn’t have to worry too much about that — if you’re going to a CRO and you intend to go into an IND, all of those things should already be in place. Still, you want to make sure they are. Just check that out.

David Brühlmann [00:25:16]:
That wraps up part one with Daniel Galbraith. We've covered his incredible journey and evolving landscape of analytical development. In part two, we'll tackle the practical challenges, from common pitfalls that trip up teams to phase appropriate strategies that actually accelerate your CMC timeline.

Speaking of streamlining your CMC journey, check out my new Notion CMC Dashboard that will help you transform chaos into confidence. This dashboard also includes a proven roadmap that will give you the exact step by step process that consistently hits IND timelines without the guesswork. And hey, if this episode added value, please leave us a review on Apple Podcasts or whatever platform you found us on. Thank you so much for tuning in 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 tuning in and joining us on 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.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.

Next Step

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About Daniel Galbraith

Daniel Galbraith, Ph.D. is the Chief Technology Officer for Large Molecules and Advanced Therapies at Solvias, bringing over 25 years of experience in the life science and biopharmaceutical industry. He has held senior leadership roles at Merck Life Science, BioReliance, and Sartorius Stedim BioOutsource, where he drove innovation in analytical development, product characterization, and advanced therapeutic technologies. Daniel began his career in virology and biosafety, holding positions at Covance Laboratories, MedImmune Vaccines, and Q-One Biotech.

He holds a Ph.D. in Immunology from the University of Abertay, an M.Sc. in Forensic Science from the University of Strathclyde, and a B.Sc. (Hons) in Microbiology from the University of Glasgow. Known for his strategic vision and scientific leadership, Daniel advocates for innovation, analytical excellence, and collaborative partnerships in advancing next-generation biotherapies.

Connect with Daniel Galbraith 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.  

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