Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data.

Journal: Drug discovery today
Published Date:

Abstract

'Artificial Intelligence' (AI) has recently had a profound impact on areas such as image and speech recognition, and this progress has already translated into practical applications. However, in the drug discovery field, such advances remains scarce, and one of the reasons is intrinsic to the data used. In this review, we discuss aspects of, and differences in, data from different domains, namely the image, speech, chemical, and biological domains, the amounts of data available, and how relevant they are to drug discovery. Improvements in the future are needed with respect to our understanding of biological systems, and the subsequent generation of practically relevant data in sufficient quantities, to truly advance the field of AI in drug discovery, to enable the discovery of novel chemistry, with novel modes of action, which shows desirable efficacy and safety in the clinic.

Authors

  • Andreas Bender
    Centre for Molecular Informatics, Yusuf Hamied Department of Chemistry, University of Cambridge UK ab454@cam.ac.uk.
  • Isidro Cortes-Ciriano
    †Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3825, 25, rue du Dr Roux, 75015 Paris, Ile de France, France.