Revolutionizing Drug Development: IIT Madras Unveils AI Framework 'PURE'

IIT Madras announces the 'PURE' AI framework, promising significant reductions in drug development timelines. Developed with Ohio State University, PURE uses reinforcement learning to optimize molecule generation, tackling drug resistance in cancer and infectious diseases. The framework advances pharmaceutical research and accelerates new material discovery.

The Indian Institute of Technology, Madras, has pioneered a game-changing AI framework named 'PURE' that is set to revolutionize the drug development process. Currently, drug discovery is an expensive, decade-long endeavor; however, PURE promises to reduce early-stage timelines significantly, presenting a leap forward in pharmaceutical research.

Researchers at IIT-M's Robert Bosch Centre for Data Science and AI and Wadhwani School of Data Science and AI have collaborated with Ohio State University on this breakthrough. The framework utilizes novel reinforcement learning approaches that closely mimic the actions of a chemist, evaluating molecular synthesisability and effectively tackling drug resistance challenges.

PURE integrates self-supervised learning with policy-based reinforcement, allowing for improved molecule generation without the bias of existing tools. The framework's potential for advancing pharmaceuticals and material discovery was published in the Journal of Cheminformatics, underlining its profound impact on the scientific community.

(With inputs from agencies.)