药物发现
生成语法
精密医学
虚拟筛选
数据科学
药物开发
人工智能
计算机科学
临床试验
机器学习
药品
生物信息学
生物
医学
药理学
病理
作者
Maria Bordukova,Nikita Makarov,Raul Rodriguez‐Esteban,Fabian Schmich,Michael P. Menden
标识
DOI:10.1080/17460441.2023.2273839
摘要
Introduction The concept of Digital Twins (DTs) translated to drug development and clinical trials describes virtual representations of systems of various complexities, ranging from individual cells to entire humans, and enables in silico simulations and experiments. DTs increase the efficiency of drug discovery and development by digitalizing processes associated with high economic, ethical, or social burden. The impact is multifaceted: DT models sharpen disease understanding, support biomarker discovery and accelerate drug development, thus advancing precision medicine. One way to realize DTs is by generative artificial intelligence (AI), a cutting-edge technology that enables the creation of novel, realistic and complex data with desired properties.
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