Cambridge Healthtech Institute’s 2nd Annual
AI/ML for Early Drug Discovery
Improving Speed and Efficiency of Target Discovery, Drug Design and Lead Optimization
12-13 November 2025
Cambridge Healthtech Institute’s annual conference on Artificial Intelligence (AI)/Machine Learning (ML) for Early Drug Discovery brings together chemists, biologists, data scientists and bioinformaticians to discuss how AI predictions and ML algorithms can enable data-driven decision-making for drug discovery. Case studies presented by experts in academia and industry highlight where AI/ML has been integrated and implemented in drug discovery. Time for informal, open-ended discussions allow for sharing knowledge and insights on where AI/ML works well and where it does not.
Coverage will include, but is not limited to:
- AI for accelerating target identification and validation, understanding disease pathways
- AI-enabled drug design, virtual screening and hit-to-lead prioritization
- ML approaches to predict binding and drug-like properties
- AI/ML for predicting ADME properties and safety profiles
- Effective use of generative AI, small and large language models (LLMs)
- Understanding agentic AI, high performance computing and other predictive tools
The deadline for priority consideration is 4 April 2025.
All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Healthtech Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.
Opportunities for Participation: