人工智能驱动的临床试验的进展、缺陷和影响。

IF 6.3 2区医学 Q1 PHARMACOLOGY & PHARMACY

Clinical Pharmacology & Therapeutics Pub Date : 2024-12-25 DOI:10.1002/cpt.3542

Dominika Wilczok, Alex Zhavoronkov

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引用次数: 0

摘要

自2010年代初的深度学习革命以来，在将人工智能（AI）应用于药物发现和开发（AIDD）方面投入了大量努力和数十亿美元。然而，尽管有很高的期望，人工智能发现或设计的药物很少进入人体临床试验，没有一个获得临床批准。从这个角度来看，我们研究了阻碍进展的挑战，并强调了利用人工智能在改变药物发现和开发方面的潜力的机会。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Progress, Pitfalls, and Impact of AI-Driven Clinical Trials.

Since the deep learning revolution of the early 2010s, significant efforts and billions of dollars have been invested in applying artificial intelligence (AI) to drug discovery and development (AIDD). However, despite high expectations, few AI-discovered or AI-designed drugs have entered human clinical trials, and none have achieved clinical approval. In this perspective, we examine the challenges impeding progress and highlight opportunities to harness AI's potential in transforming drug discovery and development.

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来源期刊

Clinical Pharmacology & Therapeutics 医学-药学

CiteScore

12.70

自引率

7.50%

发文量

290

审稿时长

2 months

期刊介绍： Clinical Pharmacology & Therapeutics (CPT) is the authoritative cross-disciplinary journal in experimental and clinical medicine devoted to publishing advances in the nature, action, efficacy, and evaluation of therapeutics. CPT welcomes original Articles in the emerging areas of translational, predictive and personalized medicine; new therapeutic modalities including gene and cell therapies; pharmacogenomics, proteomics and metabolomics; bioinformation and applied systems biology complementing areas of pharmacokinetics and pharmacodynamics, human investigation and clinical trials, pharmacovigilence, pharmacoepidemiology, pharmacometrics, and population pharmacology.