AI Article Synopsis
- Artificial intelligence (AI) can significantly enhance drug discovery processes by effectively integrating various biological data, which helps in predicting drug target properties and understanding disease mechanisms.
- There are ongoing challenges in using AI for drug target discovery, such as addressing data biases, ensuring model interpretability, and validating predicted targets.
- This review highlights recent advancements in AI applications for drug target discovery and discusses future possibilities, aiming to improve the development of new and safer medications.
Article 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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11383977 | PMC |
| http://dx.doi.org/10.1017/pcm.2024.4 | DOI Listing |
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