Smart Biotech Scientist | Master Bioprocess CMC Development, Biologics Manufacturing & Scale-up, Cell Culture Innovation

• 214: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari - Part 2

  Computational methods can predict stability issues before the lab. But how do you actually implement these approaches in your formulation workflow? From excipient selection to long-term stability prediction, in silico tools are transforming how biotech teams develop robust formulations while reducing costly trial-and-error cycles.In Part 2, Giuseppe Licari, Principal Scientist in Computational Structural Biology at Merck KGaA, returns to share practical implementation strategies for integrating computational methods into biologics formulation development. Giuseppe reveals how molecular dynamics simulations guide excipient selection, where current methods hit their limits, and how emerging AI capabilities are expanding what's possible in formulation prediction.Whether you're at a well-resourced pharma company or a lean startup, Giuseppe offers actionable guidance for leveraging computational tools to predict protein behavior, optimize formulations, and accelerate your development timeline.Topics covered:Predicting protein aggregation and excipient interactions before manufacturing (00:45)Using molecular dynamics to understand protein behavior over time and in different environments (03:03)The interplay between computational predictions and experimental stability studies (04:49)The limitations of current in silico methods for predicting long-term stability (05:08)Emerging use of AI and machine learning to predict protein properties and improve developability (06:36)Future possibilities: Generative AI for protein design and formulation prediction (08:06)Advice for small companies: leveraging software-as-a-service and external partners to access computational tools (09:55)The impact of increasing computational power on the field's evolution (11:12)Most important takeaway: being open and curious about new computational techniques in biotech formulation (12:08)Discover how to bridge computational predictions with experimental validation, navigate the current limitations of in silico stability forecasting, and position your organization to benefit from AI-driven formulation development, regardless of your resource constraints.Connect with Giuseppe Licari to continue the conversation and explore how computational approaches can solve your formulation challenges before you ever step into the lab.Connect with Giuseppe Licari:LinkedIn: www.linkedin.com/in/giuseppe-licariNext step:Need fast CMC guidance? → Get rapid CMC decision support hereSupport the show

  --------  

  14:49

  --------

  14:49
• 213: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari - Part 1

  What if you could predict formulation failures before ever touching a pipette? Computational approaches are revolutionizing biologics development, replacing trial-and-error experimentation with predictive intelligence that catches stability issues early and accelerates your path from candidate selection to clinic.In this episode, David Brühlmann welcomes Giuseppe Licari, Principal Scientist in Computational Structural Biology at Merck KGaA. A chemist by training, Giuseppe transitioned from wet lab experimentation to the predictive power of in silico modeling. Today, he operates at the intersection of computational biology and CMC development, using digital tools to screen candidates for developability, predict formulation challenges, and de-risk development programs before committing resources to the lab.Discover how computational methods are transforming the way biotech companies approach developability assessment and formulation strategy:Why maximizing shelf life isn’t always necessary in early development phases (02:56)The critical role of communication between computational and bench scientists (06:46)Core properties to assess for developability, including hydrophobicity, aggregation, charge, and immunogenicity (11:06)How accurate are in silico predictions, and where do they add the most value? (13:23)The limitations and strengths of machine learning and physics-based models in predicting protein behavior (15:19)The differences between developability, formulation development, and formulatability, and the value of early cross-functional collaboration (17:17)When to use platform formulations and when tailored approaches are needed for complex molecules (19:25)The advantages of using computational methods at any stage, especially for de-risking strategies (20:13)Listen in for practical strategies for integrating in silico predictions into your developability and CMC workflows, catching stability issues before the lab, and making smarter development decisions that save time, material, and money.Connect with Giuseppe Licari:LinkedIn: www.linkedin.com/in/giuseppe-licariNext step:Need fast CMC guidance? → Get rapid CMC decision support hereOne bad CDMO decision can cost you two years and your Series A. If you're navigating tech transfer, CDMO selection, or IND prep, let's talk before it gets expensive. Two slots open this month.Support the show

  --------  

  25:21

  --------

  25:21
• 212: When the Innovator Becomes the Patient: Manufacturing Reality vs. Patient Urgency with Jesús Zurdo - Part 2

  What happens when cell therapy innovation meets real patient urgency? In this conversation, the barriers between scientist and patient all but vanish, bringing clarity—and a new sense of mission—to some of the biggest problems facing advanced therapy manufacturing and delivery.Meet Jesús Zurdo, a biotech leader whose three decades of experience in innovation took on a whole new perspective when he became a leukemia patient himself. Seamlessly straddling the worlds of industry and patient care, Jesús Zurdo brings a refreshingly honest, systems-level view to cell therapies, manufacturing bottlenecks, and the realities of getting therapies from the lab to bedside.Topics discussed:Experiences and lessons from stem cell registries and point-of-care manufacturing models (03:15)Challenges and potential of autologous and allogeneic cell therapies, including scalability and accessibility (06:08)The promise and limitations of in vivo cell therapy, delivery risks and patient safety (07:06)Reflections on current trends in manufacturing automation, delivery platforms, and the risk of overengineering (09:49)Barriers to wider adoption of advanced cell therapies, including hospital infrastructure and economic constraints (13:31)The case for earlier lines of treatment with new modalities and value in learning from actual patient experiences (14:30)The importance of integrating voices of patients, clinicians, and developers when solving complex problems (17:31)Why urgency and remembering our future roles as patients should guide therapy development (18:51)Ready for bioprocessing to serve patients, yours included? For more insights and hands-on support, please subscribe so you never miss the next perspective-shifting episode.Connect with Jesús Zurdo:LinkedIn: https://www.linkedin.com/in/jesuszurdoEmail: [email protected] step:Need fast CMC guidance? New on-demand CMC advisory → Learn more hereSupport the show

  --------  

  22:13

  --------

  22:13
• 211: When the Innovator Becomes the Patient: Manufacturing Reality vs. Patient Urgency with Jesús Zurdo - Part 1

  Real progress in cell and gene therapy shouldn’t be measured solely by scientific innovation, but by whether those innovations actually reach the patients who need them most.In this episode, David Brühlmann sits down with Jesús Zurdo, a scientist who’s spent three decades engineering life-changing biotechnologies, but whose outlook on the field shifted dramatically after becoming a leukemia patient himself.With experience on both sides of the system, Jesús Zurdo brings a rare, unfiltered perspective to the persistent gap between scientific promise and real-world patient access.Here’s why this conversation will reshape the way you think about bioprocessing, scale-up, and the meaning of “patient-centric” innovation:The challenges of scaling up advanced therapies beyond just volume: shifting from “how much can we make” to “how many patients can we reach?” (00:21)Jesús Zurdo’s personal journey—from biotech innovator to patient—and how it reshaped his thinking on product design and patient needs (04:12)How the biotech industry often overemphasizes automation, cost of goods, and new technologies at the expense of true patient access (08:02)The importance of designing products and manufacturing processes with patients’ lived experience in mind—not just clinical metrics (05:43)Why the business model and value proposition of therapies may need to change to address the high cost and limited accessibility of new treatments (12:09)Lessons from point-of-care manufacturing and real-world delivery of cell therapies—speed versus perfection (09:11)How patient involvement in both development and long-term outcome tracking could drive better treatments and wider adoption (15:10)The limitations of current clinical trial endpoints and the need to integrate patient-reported outcomes and new data sources like wearables (17:10)Real progress in biotech isn’t just about scientific breakthroughs, it’s about ensuring those advances reach the millions who need them most.Let’s rethink our business models and deployment strategies to bridge this gap for real-world impactConnect with Jesús Zurdo:LinkedIn: https://www.linkedin.com/in/jesuszurdoEmail: [email protected] step:Need fast CMC guidance? New on-demand CMC advisory → Learn more hereSupport the show

  --------  

  21:25

  --------

  21:25
• 210: From Batch to Continuous: Building Innovation Culture in Conservative Biotech Environments with Irina Ramos - Part 2

  From pandemic-speed vaccine deployment to AI-powered process control, what separates hype from real manufacturing transformation?The biotech industry faces a fundamental challenge: how do you maintain rigorous quality standards while accelerating development timelines, personalizing therapies, and adopting transformative technologies? The answer isn't found in chasing every innovation trend, it's in understanding which changes create genuine value and when to implement them across the product lifecycle.Irina Ramos brings a perspective earned through high-stakes execution. After leading the global technology transfer of AstraZeneca's COVID-19 vaccine, a project that compressed typical timelines while maintaining uncompromising quality standards, she's applying those lessons to the industry's next wave of challenges: phase-appropriate CMC strategy, the practical realities of AI integration, and building teams that bridge generational experience gaps in an era of rapid technological change.This conversation cuts through the noise. Irina discusses when continuous processing actually makes strategic sense (hint: it's not always the right answer), why AI in bioprocessing requires more human expertise rather than less, and the collaborative frameworks that enabled one of the fastest vaccine rollouts in history—lessons directly applicable to your current CMC challenges.Episode highlights:How the biotech community is constantly changing, and the importance of adaptability for future scientists (00:00)Navigating phase-appropriate CMC strategy: What to focus on in early clinical phases and which decisions set the foundation for compliance (02:36)Scenarios for switching from batch to continuous processing, including barriers and benefits for early-stage vs. established products (02:58)Lessons from leading AstraZeneca's COVID-19 vaccine technology transfer: Collaboration, rapid regulatory communication, and mission-driven teams (05:20)Adapting lessons from the pandemic for ongoing drug development—balancing speed and risk while maintaining quality (08:24)Realistic perspectives on integrating AI in bioprocessing: demystifying its applications, emphasizing human-critical oversight, and practical use cases in manufacturing (10:40)Key skills for scientists in a biotech world shaped by AI—why foundational understanding and strong mentorship matter (13:51)Bridging experience gaps: How to foster collaboration and creativity between new and established professionals in regulated environments (15:45)Final takeaway: Start small, remain mission-driven, and remember that one size does not fit all in continuous manufacturing (17:15)Whether you're evaluating process platform decisions for Phase I programs, building cross-functional teams for tech transfer, or determining which digital tools deserve investment beyond the buzzword, this episode provides decision frameworks grounded in real-world execution at global scale.Connect with Irina Ramos:LinkedIn: www.linkedin.com/in/irinaramosNext step:Need fast CMC guidance? New on-demand CMC advisory → Learn more hereBook a 20-minute call to help you get started on any questions you may have about bioprocessing analytics: https://bruehlmann-consulting.com/call🧬 Stop second-guessing your CMC strategy. Get an investor-ready CMC roadmap in 2 weeks, before mistakes cost you $2M+ and 18 months of delays. Secure your spot here.Support the show

  --------  

  21:49

  --------

  21:49

More Science podcasts

Trending Science podcasts

About Smart Biotech Scientist | Master Bioprocess CMC Development, Biologics Manufacturing & Scale-up, Cell Culture Innovation