What if the biggest advancement in bioprocessing isn’t a new AI algorithm or cutting-edge bioreactor, but a renewed focus on the foundational skills that drive innovation—and a clear-eyed look at what AI can (and can’t) really do for the industry right now?

In this episode of the Smart Biotech Scientist Podcast, Steffen Kreye shares his journey from leadership roles in biopharma to academia, offering pragmatic insights on education, AI, and the future of bioprocessing. 

Key Topics Discussed

• AI is increasing the importance of soft skills like teamwork, motivation, and emotional intelligence in biotech education.
• Universities are integrating soft skills training through practical, project-based modules such as GMP-oriented team work.
• Student self-motivation, curiosity, and genuine scientific interest are key predictors of success in biotech careers.
• A major academic challenge is helping students identify their strengths, interests, and long-term motivation.
• Despite AI hype, real breakthrough applications in bioprocessing remain limited so far.
• Most companies are still building foundational infrastructure such as clean, integrated, and reliable data systems.
• Legacy systems, data silos, and GMP constraints remain major barriers to full AI and ML adoption in bioprocessing.
• The future of bioprocessing is expected to combine automation, continuous manufacturing, digital twins, and increasing product complexity.

Episode Highlights

• How soft skills like teamwork and self-motivation are becoming increasingly important for scientists, and strategies to foster them in education [02:47]
• The reality behind AI and machine learning in biotech today, including current limitations and the true state of industry adoption [05:48]
• Envisioning bioprocessing ten years from now: the potential of continuous manufacturing, digital twins, and automation, and the evolving diversity of bioprocesses [08:09]
• Practical ways industry professionals can support university education—from guest lectures to hands-on lab courses—and why it matters [10:09]
• Motivating students by connecting coursework to real industry roles and contributions [12:10]
• The importance of finding and following individual motivation in science careers [12:41]
• Reflections on moving from industry to academia: autonomy, challenges, and the satisfaction of seeing students grow into scientists [13:22]
• How strong collaboration between academia and industry leads to better innovation and prepares future scientists for success [15:53]

In Their Words

I think teaching and preparing the next generation of bioprocess scientists is extremely important. We need expertise, we need people, we need culture — to bring innovation to market and ultimately help patients. And I think everybody in industry can contribute: talk to universities, support them with expired cell culture media, donate unused bioreactors, or give guest lectures. This is something we can all benefit from. Because good education leads to good people, good companies, good products, and ultimately better therapies for patients.

Transcript: Is Bioprocess Education Keeping Up With New Tech? The Training Gap Industry Cannot Afford to Ignore - Part 2

David Brühlmann [00:00:39]:
Welcome back to our conversation with Steffen Kreye. In part one, he traced a career path from the bench at Glycotope to upstream leadership at Bayer and into the lecture hall at Berliner Hochschule für Technik in Berlin, Germany. He also examined what that vantage point reveals about how we train scientists today. Now we turn to what’s coming: AI-driven bioprocess development, the capability gaps, and the practical advice that matters — whether you are starting out or leading a team. Let's dive in.

Soft skills are becoming more important because AI can leverage a lot of the tedious tasks. What soft skills or emotional skills are you focusing on in education? And what are some gaps you're seeing in students coming into the university?

Steffen Kreye [00:02:47]:
Good question. I think soft skills are getting more important — that's correct. I think teamwork is still very, very important. This is usually not something you learn per se at university. Of course, you have lab courses and you usually do them in groups. For example, we have a GMP project module for GMP manufacturing. Instead of just standing there and reading GMP guidelines, we give the students a project and make it more interactive. They can “play” and develop their own product. We usually just give the boundaries: “This semester you have to produce a bispecific antibody for biopharmaceutical production. Please plan what kind of product you want to produce, plan the process, plan the facility, follow GMP guidelines.” Then they can go on. They can also use AI tools. Teams form, and they have experts for upstream, downstream, facilities, GMP regulations, and the actual science behind the bispecific antibody.

Then you get small teams working together. There are also sometimes conflicts — of course, every time people work together there are conflicts. Some people say, “I don’t want to work with this one,” or “I want to work with that one.” And then we say, well, later in real working life you also can’t always choose your colleagues. You have to work with the people who are there. So I think teamwork is a very, very important skill.

And then I think the most important skill that is really difficult to teach is some kind of self-motivation or drive. People should not expect everything to be prepared for them. They should have curiosity, they should want to understand things, and do things on their own — not just because they have to, but because they want to. I think every employer would agree: I would rather have someone who is very motivated with average results than someone with excellent grades but no motivation, no curiosity, and no drive.

It’s about people loving what they are doing — doing it because they love it, not because they are paid to do it. This is very difficult to teach. You can only spark interest in certain topics. I try to spark interest in biopharmaceutical manufacturing because I think it’s great. Some students resonate with that — they think, “This is awesome, I can use biotech to produce life-saving medicines.” Others say, “This is not for me, I’d rather work in wastewater treatment,” which is also fine. But this is what I can offer — I can share my perspective and enthusiasm. For some students it resonates, for others it doesn’t. And then we have other modules and other professors with different backgrounds.

I think it’s important that students find what motivates them and where they enjoy themselves. I just love working with bioreactors — that is my area where I feel confident and where I have fun. And if I can transfer that excitement to some of my students, I think I have done my job well.

David Brühlmann [00:05:23]:
I would love to have your honest take about AI and machine learning, because there is a huge hype out there. Many people are excited — perhaps there is even an oversell. There is no doubt that it generates buzz, but sometimes there is confusion around what the real value will be, especially in bioprocessing. What do you think about AI in bioprocessing?

Steffen Kreye [00:05:48]:
I recently attended a conference here in Berlin. I think it was also about AI and biopharma. I was really curious to see some use cases and the value you are talking about — where is the actual value for big pharma companies? And at those conferences you maybe see one or two case studies that are interesting and good, but not really breakthrough examples where your jaw drops. Most talks are actually about laying the foundation for AI. So I think what most companies are doing at this stage is basically trying to get their data ready to use AI. And I think this is really complicated. Even before AI this was complicated. I remember from my time at Bayer — and I guess also from your time in a biopharmaceutical company — it's so difficult.

Downstream development uses different tools than upstream and process development. Then you have different sites, and you have GMP and development environments. Even before AI, this was already a real struggle. Everybody was talking about a “data lake” where all data feeds in, but in the end it becomes a “data swamp,” where everything just gets sucked in. And when you need something, you have to go into the swamp and search for your data. So in my opinion, this is where we are right now — building the foundation. And this is extremely difficult, especially in GMP manufacturing, because data readiness and GMP regulations do not always go hand in hand. So I think we are not there yet. Of course AI can help structure data, but I think we need a few more years until companies can really structure their data in a way that allows AI to simply “press a button and do the work.”

David Brühlmann [00:07:20]:
Yeah, that totally resonates. This is something I've seen in various projects, both in big pharma and as a consultant working with companies. And this is key — you need to be able to access your data easily and avoid data silos. Sometimes it's even worse: you have different legacy systems across different sites, and it's very hard to understand what the data means at one site versus another. So there is still a lot of work to be done. Looking into the future, I find this very exciting and I would love your perspective on bioprocessing in general. How do you think we will produce biologics in 10 years from now?

Steffen Kreye [00:08:09]:
What I always preach to my students is the “holy grail” of a bioprocess. In my perspective, I love continuous manufacturing because I find it exciting from a technological perspective — a continuous process with advanced PAT tools, maybe digital twins, and all the exciting developments in the bioprocess community. And then more or less you press a button at the beginning of the cultivation, and the process runs by itself. You don’t need manual sampling anymore. Everything is being monitored with inline probes. You have a model which is running in parallel like a digital twin, seeing how the process runs and also corrects the process. And in the end the continuous process, your final product, just leaves process and you just put in some cell culture media and buffers. So this is something I envision.

This is like the perfect process from a technological perspective. Doesn't have to be the perfect process cost wise or for your specific product or project or company. So this is like the technological dream that's in my mind where I would love to see bioprocessing go to. But of course, in the end, the use case dictates what process is the best. And the cases for standard antibody manufacturing, it's just stainless steel, fat batch, no modeling, easy process and be done with it.

And there will still be even 10 years from now, even 20 years from now, there will still be those use cases where you just need to produce a typical monoclonal antibody and to just stick with the standard process. But the platform processes that we have right now, but with the way the biopharmaceutical landscape is developing, with more difficult to express proteins, other antibody formats, cell and gene therapies, I think the processes are more diversifying and I think all those technologies will to answer at least a few of those problems. That these diversifying processes and products will have in the future.

David Brühlmann [00:09:51]:
What can we as industry leaders do to help you at the university train the next generation of scientists? Or should I say — what should we do? What are a few things we can do right away in our industry jobs?

Steffen Kreye [00:10:09]:
So I think what you could do is just reach out to the university or university of applied sciences in your city and offer to give a lecture. It doesn’t have to be a lecture every Tuesday morning, but if you just stop by for an external lecture and talk about your company, you can also do some informal “advertising,” talk about the challenges, and so on. I think this is very easy to do. We do that a lot here. I wasn’t used to that from my own university background, but here we have many external lectures, especially in the master’s program. Every Friday there are external lecturers who come in and talk about lots of different topics. This is very, very exciting.

So I think this is something everybody can do — a very low-threshold way to get involved. You can simply contact the university and say, “I have this background, I think this is interesting.” You can also contribute to teaching. We have external lecturers from industry backgrounds.

Most of our lab courses are run in blocks over two weeks, and industry lecturers sometimes take a break from their jobs for those two weeks to work here in our labs and bring in a real industry perspective, working with students on bioreactors and practical setups. This is really important.

David Brühlmann [00:11:07]:
I think this is definitely great, and I thank you for the opportunity to do that at your school. Last year was great, and I’m looking forward to this year again. And also, the other thing you mentioned — I did this many years ago when I was at Merck. I was able to teach a module at a university of applied sciences in Switzerland that was part of a biotechnology master’s degree. It’s a great way to give students an industry perspective.

Steffen Kreye [00:11:35]:
I agree. It’s also like the soft skill set you mentioned. Sometimes it’s just as simple as how to set up an online meeting, how to structure an agenda, or how to write protocols and meeting minutes. These are things you usually learn on the job.
And the more you learn at university, the easier it will be to perform well in a job — or even to get the job in the first place. So I think this is extremely valuable for students.

It also motivates them. Of course, they see they have many courses and exams to study for, and they might think, “Why am I doing all this?” But once in a while, when they see someone who is an expert in bioprocessing, modeling, or AI, it really motivates them.
They realize, “This person studied biotechnology 10 years ago — I could be that person in 10 years.” And I think that’s very important. Students should not only learn to get good grades. They should understand that what they are learning is actually meaningful and can lead to doing very interesting work.

David Brühlmann [00:12:34]:
To a student listening to our conversation, Steffen, what single piece of advice would you give them?

Steffen Kreye [00:12:41]:
I would come back to what I said earlier: find what you like — find something you enjoy. And it also helps to find what you don’t enjoy. If you realize during your biotechnology studies that you hate technical work and bioreactors, then do something in genetics, molecular biology, or cell biology — that’s totally fine. Because if you do what you love, everything becomes much easier. So my advice is: look inside yourself, see what motivates you and what you enjoy, and focus on that. If you do something with passion and curiosity, it is much more fulfilling than doing something just because you are paid for it.

David Brühlmann [00:13:16]:
As we’re wrapping up, Steffen, what is one question I should have asked in this interview?

Steffen Kreye [00:13:22]:
I think we covered the education part quite a bit. Maybe one question is whether I ever regret going into academia. Actually, I never did. It was a big change going from industry to academia. When I started here, I was used to aligning everything with multiple teams — in industry you have four or five meetings a day just to synchronize timelines and updates. When I started here, I thought I had to schedule meetings and invite everyone. And people would ask, “Why are you asking us? You can just decide yourself.”

What I really like about my job is this freedom. I am responsible for my modules, lectures, and lab courses, and I can design them as I want. Sometimes I experiment — I try integrating a new lab experiment. Maybe it works, maybe it doesn’t. If students find it useful, great; if not, I remove it next year. I really enjoy this freedom.

I also miss working with modern bioreactors and cutting-edge equipment. At the moment we are in a good situation, but in 10–15 years our equipment will also age, and we will need new investments. Another thing I miss is working in large teams. Whenever I share a course or module with a colleague, it always becomes better because you get two perspectives instead of one.

Overall, I never regretted going into academia. It is very motivating to see how students develop. I see them in their early semesters, then later in lectures, lab courses, bachelor’s theses, and master’s theses — and eventually they become professionals in industry. And now, after five years, I see the first cohort I taught graduating with their master’s degrees. It is very rewarding to know I had a small role in their development. Sometimes they tell me, “I finished my master’s thesis and already received a job offer before submitting it.” That is very satisfying to hear.

David Brühlmann [00:15:45]:
This has been great. Steffen, what is the most important takeaway from our conversation?

Steffen Kreye [00:15:53]:
I think teaching and preparing the next generation of bioprocess scientists is extremely important. We need expertise, we need people, we need culture — to bring innovation to market and ultimately help patients. And I think everybody in industry can contribute: talk to universities, support them with expired cell culture media, donate unused bioreactors, or give guest lectures. This is something we can all benefit from. Because good education leads to good people, good companies, good products, and ultimately better therapies for patients.

David Brühlmann [00:16:32]:
Where can people get a hold of you? If they want to donate a bioreactor, provide media, or give a lecture — where can they reach you, Steffen?

Steffen Kreye [00:16:41]:
The easiest way is LinkedIn, of course. You can find me there under my name. Just reach out and send a message — that’s the simplest way. You can also find my contact details on the university website of Berliner Hochschule für Technik. Either email or LinkedIn works fine.

David Brühlmann [00:16:54]:
Well, thank you so much for being on the show today, Steffen, and for sharing this unique perspective on education and where it is going. Thank you very much.

Steffen Kreye [00:17:04]:
Thanks. It was a pleasure. It was really good talking to you, David.

David Brühlmann [00:17:09]:
The scientists who will define this industry in 2035 are sitting in classrooms right now or early in their industry roles. What they learn — and how they learn to think — will shape therapies that do not yet exist. That responsibility belongs to all of us. If today's conversation added value, please leave a review on Apple Podcasts or your platform of choice. Thank you for being part of this community.

For additional bioprocessing tips, visit us at 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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Thanks for tuning in to the Smart Biotech Scientist podcast and being part of this journey toward bioprocess mastery. For more insights and practical tips, visit www.smartbiotechscientist.com.

About Steffen Kreye

Steffen Kreye is an industrial biotechnology expert and professor at the Berliner Hochschule für Technik. His career spans more than a decade in bioprocess development, starting with a PhD at TU Berlin on mammalian cell line engineering for monoclonal antibody production. He progressed through multiple roles at Glycotope—from scientist to director of cell line and upstream process development—before moving to Bayer Pharmaceuticals as a lab head in upstream development. Since 2021, he has been back in academia, focusing on teaching and applied research in industrial biotechnology and bioprocess engineering.

Connect with Steffen Kreye on LinkedIn.

Further Listening

If you’re interested in exploring further the concepts we touched on, take a look at these related discussions:

Ep 175–176 : How Virtual Reality Training Solves Europe's Bioproduction Talent Shortage with Sandrine Lemoine — about training the next generation of biopharma talent.

Ep 93–94: From Lab Coat to LinkedIn: Benjamin McLeod's Journey to Cell and Gene Therapy Influencer — another career pivot story from a scientist who stepped outside the traditional industry path.

Ep 111–112: AI Meets Biology: Why Domain Expertise Still Rules in the Age of Large Language Models with Lars Brandén — very aligned with Steffen's nuanced take that AI is a tool but human expertise in bioprocessing still matters.

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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