精密医学
个性化医疗
计算机科学
数据科学
临床试验
风险分析(工程)
计算生物学
医学
心理学
领域(数学)
梅德林
多样性(控制论)
桥(图论)
工程伦理学
生物信息学
背景(考古学)
金标准(测试)
生命银行
随机对照试验
作者
Sara Green,Henrik Vogt,Maxence Gaillard
标识
DOI:10.1007/s40656-026-00720-x
摘要
Evidence-based medicine (EBM), with meta-analysis of randomized clinical trials as its gold standard, has been criticized for failing to represent the individuality and variability of disease. Precision medicine (PM) has been proposed as an alternative to EBM's "averaging approach", leveraging genomic and other biological information at the individual level. However, PM is still an emerging and changing concept. It is unclear what constitutes acceptable evidence, when the number of patients with a specific condition approaches one. Despite large investments, PM´s overall capacity to predict and improve treatment responses remains limited. This raises the question of whether PM has failed, or whether another strategy can improve the situation. Here, we examine the implications of functional precision medicine (FPM), a strategy aiming to bridge the gap between genomic information and phenotypic complexity through functional testing of treatments on patient-derived organoid (PDO), an advanced form of cell culture. We unpack how observed treatment effects in such personalized models are emerging as a means to predict treatment efficacy in individual patients. Drawing on exploratory interviews with scientists at the forefront of clinical implementation, we examine the philosophical implications of FPM in the contexts of cystic fibrosis and cancer. We unpack how the "functional approach" addresses biological complexity by black boxing many mechanistic details and focusing on phenotypic responses in PDOs. Moreover, we show that, to work as personalized models, they paradoxically must be validated by developing the same type of population-based evidence they aim to reduce reliance on.
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