Fostering the Development of Impactful AI Models in Drug Discovery - ICML 2023 Panel

Explore a 39-minute panel discussion from ICML 2023 on fostering impactful AI models in drug discovery. Gain insights from industry experts and researchers as they address challenges in implementing academic research in real-world settings, discuss ways to support academia, examine the lack of open datasets, and explore methods for effective model evaluation and benchmarking. Learn about the gap between research results and real-world value in drug discovery programs, and hear perspectives from leaders at Recursion Pharma, Merck, GSK, and ETH Zurich. Engage with the open Q&A session to further understand the complexities of AI applications in pharmaceutical research and development.

- Intro from Chris Gibson
- Intro from Daniel Cohen
- Introducing our Panelists
- What are some of the most common challenges faced by researchers in the industry when attempting to implement and deploy new academic research?
- What do you think industry groups can do to better support academia and attempt to resolve some of these challenges? 
- Why haven’t we opened up more datasets for the academic community in general?
- Model evaluation & benchmarking, how do we ensure that the methods we develop are useful in real-world settings?
- Open Q+A from the audience