What happens between scientific discovery and clinical trials? For too many drug candidates, the answer is “failure”—not because the idea lacked merit, but because the critical handoff between discovery and IND-enabling studies gets overlooked, rushed, or under-resourced.

This episode features Milan Tomic, whose journey stretches from nucleic acid chemistry to leading GMP manufacturing and biodefense initiatives with hundreds of millions in US government support. Milan’s focus lies in streamlining drug development, from rapid molecule design to building manufacturing infrastructure, all grounded in holistic, systems-level thinking.

Topics discussed:

• Why so many promising programs fail between discovery and the clinic, and how to close this gap through early, iterative design and testing (02:52)
• The practical advantages and considerations of cell-free protein synthesis for rapid prototyping and testing during development (07:30)
• How to decide when to deploy cell-free production versus traditional CHO systems (08:29)
• Recommendations for resource-constrained startups: what to focus on first and why stability and documentation matter most (10:55)
• Consistent success factors across Milan’s experiences, from government contract projects to launching his own company (13:54)
• Candid stories of setbacks and lessons—such as the critical importance of safety in development and the impact of overlooked technical details like facility lighting (15:30)
• The importance of linking drug design decisions to target patient needs and regulatory considerations, thinking holistically, and using target product profiles to guide development (20:22)

Smart insight: Perhaps the most powerful takeaway isn’t technical, but personal. Staying curious, open-minded, and deriving enjoyment from the process is vital for sustaining the drive necessary for biotech’s long and often unpredictable journey. The best way to bridge the valley of death in biotech is through rigorous iterative design, early testing of critical attributes, holistic planning, and a relentless commitment to learning.

If you enjoyed this episode you might also like listening to:

• Episodes 189 - 190 : Why Smart Biotech Founders Plan CMC First (While Competitors Burn Cash Later)
• Episodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan Sharfstein
• Episodes 213 - 214: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari
• Episodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri Kornmann

Connect with Milan Tomic:

LinkedIn: www.linkedin.com/in/milan-tomic-phd

Albrem Biopharma: www.albrem.com

Next Step:

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. Stay tuned for more inspiring biotech insights in our next episode.

Support the show

The "data lake" that was supposed to unify bioprocessing intelligence has, in most companies, become something else entirely: a data swamp, where information goes in and insight rarely comes back out. For anyone trying to deploy AI in GMP manufacturing, that is not a technical problem. It is the problem.

Steffen Kreye has seen it from both sides. As former upstream development lead at Bayer and now Professor of Industrial Biotechnology at Berliner Hochschule für Technik, he brings an unusually grounded perspective on where AI in bioprocessing actually stands, what the next generation of scientists needs to be equipped with, and what industry can do right now to help close the gap.

Key topics discussed:

• 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)

Smart Insight: Most companies talking about AI in bioprocessing are still solving a more fundamental problem: getting their data into a state where AI could use it at all. The breakthrough will not come from the algorithm. It will come from the unglamorous, years-long work of making data accessible, harmonized, and meaningful across sites, systems, and GMP boundaries.

Here are some other guests who touched on similar themes:

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

Connect with Steffen Kreye:

LinkedIn: www.linkedin.com/in/steffen-kreye-3b531183/

Berliner Hochschule für Technik: www.prof.bht-berlin.de/kreye

Next Step:

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. Stay tuned for more inspiring biotech insights in our next episode.

Support the show

When AI can draft a literature review in minutes, the question bioprocess educators can no longer avoid is this: what does a student actually need to learn?

Steffen Kreye has a clear answer. As Professor of Industrial Biotechnology at Berliner Hochschule für Technik, he trains engineers who step into industry ready to run a bioreactor, not just describe one. His argument is direct: hands-on lab competence is the one thing AI cannot replicate, and it is exactly what underfunding is quietly eroding.

Topics discussed:

• Why Steffen Kreye left his lab head role at Bayer to become a professor and how his career evolved (03:54)
• The unique mission of universities of applied sciences and their close connection to industry needs (11:16)
• Challenges of delivering lab-based education, including funding and equipment constraints (12:32)
• Creative strategies for partnering with biotech companies to sustain practical lab courses (14:34)
• How reading student theses, partnerships, and conferences help Steffen Kreye and his colleagues stay current in a rapidly changing field (17:43)
• The impact of AI and digital tools on research, teaching methods, and student assessment (21:18)
• Why traditional theoretical projects are less relevant, and the growing importance of problem-solving and oral examinations (22:09)

In Part 2, Steffen gives his unfiltered take on where AI in bioprocessing actually stands, which human capabilities are becoming harder to replace, and what a well-prepared bioprocess engineer will need to look like by 2035.

Smart Insight: Once AI can produce a polished report from a well-structured prompt, the only assessment that still reveals genuine understanding is the one a student has to navigate in real time, without a tool to hide behind.

Here are some other guests who touched on similar themes:

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

Connect with Steffen Kreye:

LinkedIn: www.linkedin.com/in/steffen-kreye-3b531183/

Berliner Hochschule für Technik: www.prof.bht-berlin.de/kreye

Next Step:

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. Stay tuned for more inspiring biotech insights in our next episode.

Support the show