Smart Biotech Scientist | The CMC and Bioprocessing Podcast for Process Development and Manufacturing Leaders
The go-to CMC and biomanufacturing podcast for bioprocess development scientists and CMC leaders scaling biologics into regulatory-ready therapies with less trial and error.
Practical, execution-focused, and strategic guidance on CMC development, tech transfer, scale-up, GMP readiness, CDMO partnerships, and manufacturing economics for biologics, cell and gene therapies, cultivated meat, and biomaterials.
Hosted by Dr. David Brühlmann, CMC strategist, former Bioprocess Innovation Manager at Merck, PhD in glycoengineering, and close to 20 years of biomanufacturing experience. Smart Biotech Scientist delivers actionable insights for the people doing the hard work of turning promising molecules into scalable, regulatory-ready therapies.
This podcast is for you if:
- You are a process development scientist or CMC lead managing a technology transfer, scale-up, or CDMO partnership
- You are a biologics developer working on upstream or downstream process development, cell culture optimization, or GMP manufacturing readiness
- You are a biotech founder preparing for an IND filing or Series A fundraise, and need a CMC strategy that holds up under investor and regulatory scrutiny
- You are building or advising an early-stage biopharma team and need to make smart manufacturing decisions with limited resources
What you will learn:
CMC strategy and regulatory planning, bioprocess scale-up from lab to clinical and commercial manufacturing, cell culture process development and media optimization, technology transfer best practices, CDMO selection and partnership management, hybrid modeling, manufacturing economics, continuous manufacturing, digitization, and Industry 4.0 in biopharma.
Top 10 life sciences podcast with 200+ episodes and guests from Merck, FUJIFILM Irvine Scientific, Cytiva, KBI Biopharma, Eppendorf, and biotech innovators worldwide.
New episodes released weekly. Subscribe and join 400+ biotech leaders already using these insights to accelerate development, reduce manufacturing costs, and de-risk scale-up.
Next Steps:
Visit the Website: https://smartbiotechscientist.com
Email us: hello@bruehlmann-consulting.com
Smart Biotech Scientist | The CMC and Bioprocessing Podcast for Process Development and Manufacturing Leaders
251: Why a Single Large DoE Fails Biosimilar Glycan Optimization — And the Parallel Screening Method That Actually Works
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Are you stuck screening endless compounds in biosimilar development and still not hitting your quality targets? Efficient compound screening is one of the toughest bottlenecks in biopharma, with outdated methods slowing progress and risking critical quality attributes in monoclonal antibody development.
David Brühlmann breaks down a practical, parallel framework for rapid compound screening that addresses interaction effects, masking, and data quality. Methods proven in challenging biosimilar development programs.
Topics discussed:
- The historical bottleneck of one-at-a-time screening in drug discovery and the impact of high throughput methods (01:04)
- Problems with both one-factor-at-a-time and large design of experiments approaches when handling many variables (02:10)
- Description of the parallel group method: splitting 17 quality modulating compounds into five biologically relevant groups and running experiments in parallel (06:09)
- How grouping compounds by biological mechanism improves interpretability and experimental design (06:43)
- Strategies for minimizing dilution effects, toxicity risks, and masking in multi-factor screens (08:24)
- The importance of multivariate analysis: using principal component analysis (PCA), Mahalanobis distance, and decision trees to interpret and select optimal experimental conditions (10:31)
- Real-world outcomes: identifying optimal compound combinations in just two rounds of screening (15:20)
- Reflections on the evolving role of hybrid modeling and machine learning in biosimilar process optimization (15:54)
In Part 2, the focus shifts to a hands-on approach, covering how to design compound groups based on biology, set concentration ranges without compromising data quality, and execute a 96-well screen with the rigor the method demands. It also highlights three key aspects that would be approached differently if the study were conducted today.
Strategic insight:
Effective compound screening shifts from one-at-a-time testing to biology-driven parallel grouping combined with multivariate analytics, enabling faster identification of optimal combinations while preserving data quality and capturing interaction effects.
If you want more detail, you can read the full article “Parallel experimental design and multivariate analysis provides efficient screening of cell culture media supplements to improve biosimilar product quality” published in Biotechnology and Bioengineering, which outlines the methods and findings behind this approach.
If you’re interested in hybrid modeling, here’s what previous podcast guests have shared on the topic, offering perspectives from fundamentals to real-world applications.
- Episodes 05 - 06: Hybrid Modeling: The Key to Smarter Bioprocessing with Michael Sokolov
- Episodes 99 - 100: From Raw Data to Actionable Insights: Unlocking the Power of Process Models with Fabian Feidl
- Episodes 137 - 138: Skip 90% of Bioreactor Runs: The In Silico Revolution in Bioprocess Development with Yossi Quint
- Episodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist Gernaey
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