What is the plausibility that all drugs will be designed by computers by the end of the decade?

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Abbreviations

ADMET, absorption, distribution, metabolism, excretion, and toxicology; AI, artificial intelligence; CADD, computer-aided drug design; CDDD, computationally driven drug discovery; DD, drug design; DDD, drug design and development; HTS, high-throughput screening; ML, machine learning; QSAR/QSPR: quantitative structure-activity/property-relationships.

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

A reviewer of this manuscript has disclosed that they are employed by Charles River Laboratories. Peer reviewers on this manuscript have no other relevant financial relationships or otherwise to disclose.

Additional information

Funding

This manuscript was supported by the National Autonomous University of Mexico (UNAM), the General Directorate of Academic Personnel Affairs (DGAPA), via the Support Program for Research and Technological Innovation (PAPIIT), grant No. IN201321 and the General Directorate of Computing and Information and Communication Technologies (DGTIC) for the computational resources to use the Miztli supercomputer, project LANCAD-UNAM-DGTIC-335. E López-López thanks the National Council of Humanities, Science and Technology (CONAHCyT), Mexico, for granting scholarship No. CVU: 894234.