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<p>Over the past decade, about one-fifth of FDA-approved drugs each year involve novel mechanism-of-action human targets. Although riskier than modulating well-known targets, these therapies address unmet needs and strengthen sector innovation. The Open Targets Platform is a valuable open resource for identifying novel targets, integrating diverse datasets with regular updates and a user-friendly interface. To expand its capabilities, we implement comprehensive timestamping across millions of biomedical data points and introduce a target novelty metric for disease contexts, enabling discovery of novel targets within the ecosystem. We also present a retrospective analysis of novel drug target approvals over two decades, revealing a shift around 2015: supportive biomedical evidence (e.g., human genetics, literature-derived insights, differential expression, and pathway data) increasingly appears before rather than after the approval year. These findings underscore the importance of time-based evidence assessments for earlier identification of novel clinical opportunities and offer guidance for future target selection trends.</p>

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Temporal trends in evidence supporting novel drug target discovery

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月7日

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  • Maria J. Falaguera,
  • Ellen M. McDonagh,
  • David Ochoa,
  • Polina V. Rusina,
  • Juan Maria Roldan-Romero,
  • David G. Hulcoop,
  • Andrew R. Leach,
  • Ian Dunham

摘要

Over the past decade, about one-fifth of FDA-approved drugs each year involve novel mechanism-of-action human targets. Although riskier than modulating well-known targets, these therapies address unmet needs and strengthen sector innovation. The Open Targets Platform is a valuable open resource for identifying novel targets, integrating diverse datasets with regular updates and a user-friendly interface. To expand its capabilities, we implement comprehensive timestamping across millions of biomedical data points and introduce a target novelty metric for disease contexts, enabling discovery of novel targets within the ecosystem. We also present a retrospective analysis of novel drug target approvals over two decades, revealing a shift around 2015: supportive biomedical evidence (e.g., human genetics, literature-derived insights, differential expression, and pathway data) increasingly appears before rather than after the approval year. These findings underscore the importance of time-based evidence assessments for earlier identification of novel clinical opportunities and offer guidance for future target selection trends.