From Methods to Molecules
This workshop aims to connect algorithmic innovations in AI with the practical challenges of discovering and developing new medicines, emphasizing methodologically rigorous approaches that address long-standing bottlenecks such as target identification, chemical space exploration, and translational models that can de-risk drug development. By bringing together academic and industry experts from AI, computational life sciences, and pharmaceutical research, the workshop will foster cross-disciplinary exchange, showcase recent advances, and chart future directions at the interface of AI and drug discovery.
Topics
- De-novo Drug Design: the use of advanced AI methods to generate new molecules that have the desired properties.
- Active Learning: iteratively steer experiments to generate the most informative data that accelerate model improvements and enhance drug discovery efficiency.
- Multi-Modal Learning: leveraging diverse data sources to build integrative AI models to enhance drug discovery success rates.
- Casual AI: moving beyond correlations to uncover causal relationships to derive actionable insights and enable the prediction of drug effects.
Format of Workshop
There are four oral sessions each covering distinct research themes. Each session will open with two invited presentations, followed by two oral presentations selected from the submissions. There is a poster session featuring submitted content. A final session will contain a panel discussion by the senior and up-and-coming researchers, focusing on next steps for the community. The workshop will take place over 1 day.
Attendance
Invited speakers will be internationally recognized experts in their respective domains and will anchor the sessions with a total of 8 keynote talks. We expect to select 8 contributed oral presentations to complement the program and highlight emerging work in the field.
We invite everyone interested in advancing drug discovery via AI to attend, specifically:
- AI researchers who wish to understand critical bottlenecks in drug discovery;
- Drug discovery professionals who wish to be informed on the latest AI advances.
Due to venue constraints, priority will be given to contributors of the workshop.