临床试验
药物发现
药学
医学
计算生物学
药理学
数据科学
生物信息学
计算机科学
生物
内科学
作者
Madura K P Jayatunga,Margaret Ayers,Lotte Bruens,Dhruv Jayanth,Christoph A. Meier
标识
DOI:10.1016/j.drudis.2024.104009
摘要
AI techniques are making inroads into the field of drug discovery. As a result, a growing number of drugs and vaccines have been discovered using AI. However, questions remain about the success of these molecules in clinical trials. To address these questions, we conducted a first analysis of the clinical pipelines of AI-native Biotech companies. In Phase I we find AI-discovered molecules have an 80–90% success rate, substantially higher than historic industry averages. This suggests, we argue, that AI is highly capable of designing or identifying molecules with drug-like properties. In Phase II the success rate is ∼40%, albeit on a limited sample size, comparable to historic industry averages. Our findings highlight early signs of potential for AI-discovered molecules.
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