Drug Discovery Task

Drug discovery is accelerating through the application of artificial intelligence, aiming to efficiently identify promising drug candidates. Current research focuses on developing generative models, including diffusion models and large language models, to design molecules with desired properties and predict their effectiveness, often incorporating techniques to address data scarcity and covariate shift. These advancements leverage multi-modal data integration and incorporate explicit knowledge of protein-ligand interactions or desired chemical properties to improve the reliability and efficiency of the drug discovery process. Ultimately, these methods aim to reduce the time and cost associated with traditional drug development, leading to faster delivery of new therapeutics.