芯片上器官
钥匙(锁)
药物发现
风险分析(工程)
药品
药物开发
计算机科学
边疆
数据科学
重症监护医学
业务
医学
生化工程
药理学
纳米技术
工程类
生物信息学
生物
计算机安全
政治学
法学
材料科学
微流控
标识
DOI:10.1016/j.drudis.2023.103515
摘要
Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Recently, a dramatic regulatory change has removed FDA's mandated reliance on antiquated, ineffective animal studies. A new frontier is an integration of several disruptive technologies [machine learning (ML), patient-on-chip, real-time sensing, and stem cells], which when integrated, have the potential to address this challenge, drastically cutting the time and cost of developing drugs, and tailoring them to individual patients.
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