Artificial Intelligence in Biomedicine

Artificial intelligence is rapidly transforming biomedical research and opening new perspectives for understanding complex biological systems and improving patient care. The IBSA Foundation Forum Artificial Intelligence in Biomedicine: from basic research to clinical application will bring together leading experts from biology, medicine, and computational science to explore the latest advances and emerging perspectives in AI-driven biomedical research.

The Forum, organized in collaboration with Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI), will provide a dynamic platform for presenting and discussing pioneering research, fostering interdisciplinary collaboration and promoting an integrated approach to translating innovations in artificial intelligence from fundamental discovery to clinical practice, with the ultimate goal of enabling more predictive and personalised healthcare.

Session 1 - Digital Twins and Personalised Medicine
Artificial intelligence is enabling the development of digital twins, computational models that integrate multimodal biological and clinical data to represent and predict the behaviour of individual patients. By combining data-driven learning with mechanistic and causal approaches, these models allow the simulation of disease progression and treatment responses. This session will explore recent advances in AI-driven patient modelling and their potential to support diagnosis, therapeutic decision-making, and personalised treatment strategies.

Session 2 - From Models to Molecules – Protein Design and Compound Design
Artificial intelligence is redefining what is possible in molecular medicine, enabling the transition from predicting the properties of known molecules to designing entirely new ones. By combining generative models with structural and biophysical knowledge, AI is accelerating the discovery of novel proteins, antibodies, and small-molecule therapeutics with tailored properties — compressing discovery timelines and expanding the boundaries of what can be engineered. This session will highlight recent advances in AI-driven molecular design, examining how computational approaches are bridging the gap between predictive modelling and the generation of viable drug candidates, and where the most promising — and most challenging — frontiers remain.

TBA: closing lecture