Clarke, Rebekah, Palazzo, Giuseppe, Ruzicka, Jiri, Ferla, Salvatore and Bassetto, Marcella ORCID: https://orcid.org/0000-0002-2491-5868
2026.
Computer-aided drug discovery: historical foundations, practical AI tools, and emerging ethical considerations.
Frontiers in Pharmacology
17
, 1866562.
10.3389/fphar.2026.1866562
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Abstract
Computer-aided drug discovery (CADD) has become an integral component of modern drug development, supporting hit identification, lead optimisation, and candidate refinement across both academia and industry. Over 4 decades of methodological progress have contributed to the discovery or optimisation of several approved therapeutics, establishing CADD as a crucial element of drug research. In parallel, recent advances in artificial intelligence (AI) and machine learning (ML) have introduced a new generation of practical tools that offer improved predictive performance, accessible software implementations, and increasing integration into everyday drug discovery and pharmacology workflows. This review provides a concise historical overview of CADD, with an updated account of approved drugs and clinical-stage candidates whose discovery or optimisation has involved computational methods and highlights a curated set of contemporary AI and ML tools that are readily usable by non-specialists. In addition, we compile and analyse two comprehensive, practice-oriented resources: a collection of cloud-based virtual-screening platforms, and an extensive suite of freely accessible ADMET prediction tools, offering medicinal chemists a consolidated guide to open-source computational workflows. Finally, we discuss emerging ethical considerations, including data bias, transparency, computational costs, and the environmental impact of large-scale models, outlining responsible paths for the continued adoption of AI in drug discovery.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Pharmacy |
| Publisher: | Frontiers Media |
| Date of First Compliant Deposit: | 7 July 2026 |
| Date of Acceptance: | 10 June 2026 |
| Last Modified: | 07 Jul 2026 09:15 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/187986 |
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