AI/ML-Powered Formulation Design: Accelerating Innovation

DATE

May 29, 2025

TIME

8:00 a.m. PDT, 11:00 a.m. EDT, 16:00 BST, 17:00 CEST - Duration: 60 Minutes

Overview

Machine learning (ML) is revolutionizing formulation design by enabling data-driven predictions of critical performance indicators, such as solubility, viscosity, stability, and even sensory properties. Chemistry-informed AI/ML models provide a powerful framework for accelerating innovation across a wide range of formulations — from personal care and food, to pharma and battery electrolytes. By analyzing large, diverse datasets, ML can predict the behavior of new formulations, including complex mixtures and ingredients that are combinations of multiple mixtures, dramatically reducing reliance on trial-and-error approaches and speeding time-to-market.

Automated solutions can integrate ingredient composition and molecular structure to generate predictive models that optimize formulation performance. This empowers R&D teams to explore complex formulation spaces, reduce development cycles, and innovate more effectively. In this webinar, we will demonstrate how Schrödinger’s integrated ML- and physics-based approaches are transforming formulation design, with an emphasis on applications relevant to consumer packaged goods (CPG).

Key Learning Objectives:

How physics-based models can help generate meaningful data for enhancing ML models in projects with limited data inputs
How an automated ML solution, incorporating chemistry and composition, can predict solubility in multi-component systems
How ML models that are enhanced with physics-based descriptors can improve viscosity predictions
How formulation ML tools enable non-computational experts to design novel CPG products that meet multiple target criteria—a case study with shampoo formulations

Who Should Attend:

R&D Leaders
Innovation Managers
Digitization Managers
Synthetic Chemists
Materials Scientists
Chemical Engineers
Materials Research Engineers
Computational Chemists
Computational Materials Scientists

Brought to you by:

Speakers

Jeffrey Sanders
Product Manager and Technical Lead for CPG,
Schrödinger

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