Advancing Computational Drug Design: New Mathematical approaches from Multiscale to AI

The landscape of drug design is rapidly evolving, with computational methods and artificial intelligence (AI) playing an increasingly important role. This workshop aims to explore cutting-edge mathematical approaches that are transforming the field of computational drug design. We will delve into multiscale modeling techniques that bridge the gap between molecular and macroscopic levels, providing a comprehensive understanding of drug interactions and dynamics. Additionally, we will highlight the integration of generative AI and machine learning (ML) algorithms in predicting drug efficacy, optimizing molecular structure, speeding up drug repurposing, understanding potential toxicity, and thus accelerating the drug discovery and development process. By bringing together diverse experts from academia, industry, and innovation support organizations, and adding early career researchers to the mix, this workshop will foster interdisciplinary collaboration and innovation. Participants will gain insights into the latest developments, discuss challenges, and explore future opportunities in the quest for more effective and efficient drug design.