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AI approaches for the discovery and validation of drug targets.

Aaron WentelerClaudia P CabreraWei WeiVictor NeduvaMichael R Barnes
Published in: Cambridge prisms. Precision medicine (2024)
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.
Keyphrases
  • artificial intelligence
  • big data
  • drug discovery
  • machine learning
  • small molecule
  • deep learning
  • high throughput
  • drug induced
  • emergency department
  • mass spectrometry
  • current status
  • single cell
  • data analysis