09:00 – 9:05 Opening Remarks
09:05 -10:20 | Session I: De-novo Drug Design
- 09:05 – 09:30 Gisbert Schneider (ETH Zürich) Drug design with machine intelligence
- 09:30 – 09:55 Djork-Arné Clevert (Pfizer) From Models to Molecules: Controllable, Structure-Based Molecular Generation
- 09:55 – 10:05 Mahule Roy, Subhas Roy: Co-Diffuse: Generative Co-Design of Protein–Ligand Interactions via 3D Equivariant Diffusion Models with Induced-Fit Awareness
- 10:05 – 10:15 Alessandro Luongo, Konstantina Koteva, El Amine Cherrat, Enrico Petretto, Alexander Rodin Quantum-Enhanced Generative AI Pipeline for Molecular Design
10:15 – 10:40 Coffee/Tea Break
10:40 – 12:00 | Session II: Active Learning
- 10:40 – 11:10 J.B. Brown (Boehringer-Ingelheim) Active Learning Drug Discovery at Boehringer-Ingelheim : expectations, realities, and best practices
- 11:10 – 11:40 Jake Taylor-King (Relation Therapeutics) AI in genomics: genetics, spatial transcriptomics, and experimental design
- 11:40 – 11:50 Samarth Kadaba, Connor C. Call, Alexander E. Vlahos, Hank Jones, Xiaojing J Gao SMPO: Score-Matching Preference Optimization for Protein Fitness Modeling
- 11:50 – 12:00 Mehyar Mlaweh, Tristan Cazenave, Ines Alaya BeeRNA: tertiary structure-based RNA inverse folding using Artificial Bee Colony
12:00 – 13:30 Lunch
13:30 – 14:50 | Session III: Multi-Modal Learning:
- 13:30 – 14:00 Le Song (GenBio AI) Towards AI-Driven Digital Organism: A System of Multiscale Foundation Models for Biology
- 14:00 – 14:30 Jianying Hu (IBM) GenAI for Biomedical Research and Discovery
- 14:30 – 14:40 Le Huy Khiem, Sreejata Dey, Marcos Martínez Galindo, Vanessa Lopez, Ting Hua, Nitesh V Chawla, Hoang Thanh Lam Towards Generalist Large Language Models for Molecular Property Prediction: Distilling Knowledge from Specialist Models
- 14:40 – 14:50 Ahmed A. A. Elhag, Arun Raja, Alex Morehead, Samuel M Blau, Garrett M Morris, Michael M. Bronstein Learning Inter-Atomic Potentials without Explicit Equivariance
14:50 – 15:10 Coffee/Tea Break
15:10 – 16:30 | Session IV: Causal AI
- 15:10 – 15:40 Patrick Schwab (GSK) TBD
- 15:40 – 16:10 Yoshihiro Yamanishi (Nagoya University) Data-driven identification of therapeutic targets and drug candidates
through machine learning - 16:10 – 16:20 David Scott Lewis, Enrique Zueco Agentic Causal Graph Learning for Drug Target Discovery: A Self-Directed AI System at STRING Scale
- 16:20 – 16:30 Crystal Su MedRule-KG: A Knowledge-Graph–Steered Scaffold for Reliable Mathematical and Biomedical Reasoning
16:30 – 17:30 Poster Session
17:30 – 18:00 Panel Discussion