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<p>Drug discovery and development is time-intensive, expensive and laden with risk. Identifying the right drug targets is crucial for increasing the probability of success, but traditional target identification and validation often take years, and a target is only fully validated once a drug based on it receives approval by regulatory agencies. Given its proficiency in analysing large datasets and intricate biological networks, artificial intelligence (AI) is playing an increasingly important role in drug target identification and assessment. This article reviews recent advances in target discovery, emphasizing key considerations in target selection and breakthroughs in the application of AI-driven approaches for therapeutic target exploration, as well as challenges and limitations. We also highlight examples where AI tools have enabled or supported the identification of targets for which drug candidates have entered clinical trials.</p>

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Target identification and assessment in the era of AI

  • 期刊论文

  • 发表日期：

    2026年4月20日

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  • Frank W. Pun,
  • Dmitriy Podolskiy,
  • Evgeny Izumchenko,
  • Andrew Mortlock,
  • Tudor I. Oprea,
  • Morten Scheibye-Knudsen,
  • Kristen Fortney,
  • Eric Morgen,
  • Feng Ren,
  • Alex Zhavoronkov

摘要

Drug discovery and development is time-intensive, expensive and laden with risk. Identifying the right drug targets is crucial for increasing the probability of success, but traditional target identification and validation often take years, and a target is only fully validated once a drug based on it receives approval by regulatory agencies. Given its proficiency in analysing large datasets and intricate biological networks, artificial intelligence (AI) is playing an increasingly important role in drug target identification and assessment. This article reviews recent advances in target discovery, emphasizing key considerations in target selection and breakthroughs in the application of AI-driven approaches for therapeutic target exploration, as well as challenges and limitations. We also highlight examples where AI tools have enabled or supported the identification of targets for which drug candidates have entered clinical trials.