Drug repurposing represents an attractive alternative to the costly and time-consuming process of new drug development, particularly for serious, widespread conditions with limited effective treatments, such as Alzheimer’s disease (AD). Emerging generative artificial intelligence (GAI) technologies like ChatGPT offer the promise of expediting the review and summary of scientific knowledge. To examine the feasibility of using GAI for identifying drug repurposing candidates, we iteratively tasked ChatGPT with proposing the twenty most promising drugs for repurposing in AD, and tested the top ten for risk of incident AD in exposed and unexposed individuals over age 65 in two large clinical datasets: (1) Vanderbilt University Medical Center and (2) the All of Us Research Program. Among the candidates suggested by ChatGPT, metformin, simvastatin, and losartan were associated with lower AD risk in meta-analysis. These findings suggest GAI technologies can assimilate scientific insights from an extensive Internet-based search space, helping to prioritize drug repurposing candidates and facilitate the treatment of diseases.

药物再利用是一种有吸引力的替代方案，可以替代昂贵且耗时的新药开发过程，特别是对于有效治疗有限的严重、广泛的疾病，例如阿尔茨海默氏病（AD）。ChatGPT 等新兴的生成人工智能 (GAI) 技术有望加快科学知识的审查和总结。为了检验使用 GAI 识别药物再利用候选者的可行性，我们反复委托 ChatGPT 提出 20 种最有希望在 AD 中再利用的药物，并在两个大的 65 岁以上暴露和未暴露个体中测试了前十种药物的 AD 事件风险。临床数据集：（1）范德比尔特大学医学中心和（2）我们所有人研究计划。在 ChatGPT 推荐的候选药物中，荟萃分析显示二甲双胍、辛伐他汀和氯沙坦与较低的 AD 风险相关。这些发现表明，GAI 技术可以从广泛的互联网搜索空间中吸收科学见解，有助于确定药物再利用候选者的优先顺序并促进疾病的治疗。