The Future Impact of Machine Learning on Drug Discovery

This event brought together 50 leaders from the pharmaceutical industry, academia, and funding organisations to discuss how artificial intelligence (AI) and machine learning (ML) have the potential to transform drug discovery.

Earlier this year, the 2024 Nobel Prizes emphasised the transformative impact of machine learning, with two UCL alumni among the laureates. A significant part of the Chemistry Prize recognised the development of AlphaFold, an AI-driven tool devised by DeepMind that predicts protein structures with unprecedented accuracy. AlphaFold’s success illustrates the power of machine learning applied to curated datasets like the Protein Data Bank, revolutionising our understanding of biology.

Building on this momentum, the meeting introduced pioneering screening platforms under development at SGC, including DNA-Encoded Libraries combined with Machine Learning (DEL-ML) and Affinity Selection Mass Spectrometry (ASMS). These platforms, alongside initiatives like Donate Your Proteins to SGC, AIRCHECK, and MAINFRAME, aim to generate robust and high-quality datasets of small molecule-protein interactions.

Such datasets will be critical for developing next-generation machine learning algorithms to predict small molecule binders for biological targets, addressing one of the biggest challenges in early drug discovery. As one of the seven SGC research sites, UCL stands as a key player in advancing these efforts and supporting SGC’s mission to democratize drug discovery through open science and collaboration.

Image: A graphic that shows the UCL-SGC roadmap and the various processes start to finish.

“This meeting marked a milestone in our collective efforts to leverage open science and ML-driven innovation,” said Aled Edwards, CEO of the SGC. “By collaborating across academia, industry, and technology sectors, we are laying the groundwork for a new era in drug discovery.”

Professor Matthew Todd, Chair of Drug Discovery at the UCL School of Pharmacy, added, “This is an incredibly exciting project in a fast-moving area. The Nobel Prizes highlighted the transformative potential of machine learning in understanding fundamental biology. This meeting showcased how UCL’s academic strength and London’s vibrant AI ecosystem can drive this mission forward.”

About the Structural Genomics Consortium (SGC)
The Structural Genomics Consortium is a global public-private partnership that seeks to accelerate drug discovery by fostering collaboration among a large network of scientists in academia and industry and making all research outputs openly available to the scientific community. The current SGC research sites are located at Goethe University in Frankfurt, Karolinska Institute, McGill University, UCL, the University of North Carolina, Chapel Hill, the University of Toronto and Unicamp.

Contact:

SGC contact: Sofia Melliou - communications@thesgc.org
UCL contact: Fiona Marquet - f.marquet@ucl.ac.uk