AI Approaches for the Discovery and Validation of Drug Targets

Overview

Journal Camb Prism Precis Med

Publisher Cambridge University Press

Date 2024 Sep 11

PMID 39258224

Authors

Aaron Wenteler

Claudia P Cabrera

Wei Wei

Victor Neduva

Michael R Barnes

Affiliations

Soon will be listed here.

Abstract

Artificial intelligence (AI) holds immense promise for accelerating and improving all aspects of drug discovery, not least target discovery and validation. By integrating a diverse range of biological data modalities, AI enables the accurate prediction of drug target properties, ultimately illuminating biological mechanisms of disease and guiding drug discovery strategies. Despite the indisputable potential of AI in drug target discovery, there are many challenges and obstacles yet to be overcome, including dealing with data biases, model interpretability and generalisability, and the validation of predicted drug targets, to name a few. By exploring recent advancements in AI, this review showcases current applications of AI for drug target discovery and offers perspectives on the future of AI for the discovery and validation of drug targets, paving the way for the generation of novel and safer pharmaceuticals.

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