CRS 2026
Date & Time - July 6th-9th, 2026
Location - Lisbon, Portugal
Schrödinger is excited to be participating in the CRS 2026 conference taking place on July 6th – 9th in Lisbon, Portugal. Join us for a presentation by Irene Bechis, Principal Scientist I, Materials Science Applications Science at Schrödinger, titled “Combining physics-based and machine learning approaches to accelerate pharmaceutical formulations design and development.” Stop by booth #38 to speak with Schrödinger scientists.
Combining physics-based and machine learning approaches to accelerate pharmaceutical formulations design and development
Speaker:
Irene Bechis, Principal Scientist I, Materials Science Applications Science, Schrödinger
Abstract:
The successful translation of an active pharmaceutical ingredient (API) into a viable clinical therapy hinges critically on the development of an optimal drug formulation. Engineering a formulation that balances bioavailability, stability, and targeted delivery often presents a complex physicochemical challenge. With advances in machine learning, physics-based simulation and compute hardware, modeling is emerging as a valuable source of information to complement experimental characterization and guide decisions in formulation development.
In this talk, we showcase how the tools from the Schrödinger platform can be applied to modeling formulations across a diverse set of therapeutic modalities, ranging from small molecules to peptides to biologics.
The talk will feature case studies on crystalline solid formulations, demonstrating the use of crystal structure prediction to map polymorph landscapes and machine learning approaches for optimal co-former selection for co-crystals. Furthermore, we will explore amorphous solid dispersions, showcasing how physics-based simulations can help predict formulation stability and understand the drug release mechanism. Finally, we will discuss methods to analyze those complex, dynamic structures that are typical of formulations in the fluid state, such as lipid-based formulations for nucleic acid delivery and excipient-protein interactions in injectables.