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-licari

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