Impurity Identification in API Analytical Research

Webinars2025-09-17

The rapid advancements in computational material science and process simulation have made computational methods indispensable in modern drug development and manufacturing workflows. These approaches enable more efficient navigation through the multidimensional complexities of pharmaceutical process development. By integrating computational and experimental methodologies, we can significantly de-risk pharmaceutical development while achieving substantial time and cost efficiencies. Among these techniques, molecular modeling and data science have emerged as particularly powerful tools—offering a rational, evidence-based framework to guide drug development workflows, as highlighted in recent publications. This structured approach allows researchers to prioritize the most promising solutions for targeted experimental validation, thereby optimizing resource allocation.We are truly privileged to welcome today's speaker: Dr. Yuriy Abramov, Executive Director of Computational Chemistry & Data Science at Porton J-STAR. In this session, he will deliver an expert analysis of computational chemistry and data science strategies designed to streamline drug development and reduce costs.