AI Advancing Drug Design in the Pharmaceutical Industry and Academia
Day 2 | 13:00 – 13:30 | Workshop Room 3
Dr. Raquel Rodríguez-Pérez
Novartis Biomedical Research
Abstract
Artificial intelligence (AI) and Machine learning (ML) systems have become key tools for decision-making in drug discovery research. In this talk, I will discuss opportunities ML models offer to accelerate and improve compound selection, review the model life cycle, and describe practical applications at Novartis. I will also highlight synergies between academic and industrial research when applying AI/ML in drug discovery, focusing on molecular ML. Despite common open research questions and long-term goals, the nature and scope of investigations typically differ between academia and industry. I will close by discussing strategies that might improve collaborations between academic and industrial institutions and thus further advance the field.
Dr. Raquel Rodríguez-Pérez
Dr. Raquel Rodríguez-Pérez is AD & Senior Principal Data Scientist at Novartis Biomedical Research. In her current role, she integrates AI technologies into decision-making in drug discovery projects. She enables AI-driven drug design by leveraging techniques such as molecular property predictions, generative chemistry, uncertainty estimation or explainable AI. Raquel obtained her B.Sc. and M. Sc. degrees in Biomedical Engineering from the University of Barcelona, and her PhD in Computational Life Sciences from the University of Bonn. She was a Marie Sklodowska-Curie fellow and worked at the Computational Chemistry Data Science team at Boehringer Ingelheim in Germany. Her research focuses on predictive modeling and pattern recognition for different applications in chemistry and the life sciences.