Artificial intelligence in drug discovery: recent advances and future perspectives
José Jiménez-Luna, Francesca Grisoni, Nils Weskamp, Gisbert Schneider
Abstract
: Deep learning-based approaches have only begun to address some fundamental problems in drug discovery. Certain methodological advances, such as message-passing models, spatial-symmetry-preserving networks, hybrid de novo design, and other innovative machine learning paradigms, will likely become commonplace and help address some of the most challenging questions. Open data sharing and model development will play a central role in the advancement of drug discovery with AI.
Topics & Concepts
Drug discoveryCheminformaticsComputer scienceArtificial intelligenceData scienceDeep learningSkepticismMachine learningBioinformaticsEpistemologyBiologyPhilosophyComputational Drug Discovery MethodsMachine Learning in Materials ScienceGenetics, Bioinformatics, and Biomedical Research