临床试验
认知
背景(考古学)
药物开发
走/不走
疾病
药物发现
集合(抽象数据类型)
心理学
机制(生物学)
动作(物理)
药品
医学
计算机科学
数据科学
生物信息学
药理学
精神科
机器学习
物理
哲学
病理
古生物学
程序设计语言
认识论
生物
量子力学
作者
Alette M. Wessels,Chris J. Edgar,Pradeep J. Nathan,Eric Siemers,Paul Maruff,John Harrison
标识
DOI:10.1016/j.drudis.2021.01.012
摘要
Go/No-Go decision making in early phase clinical trials is challenging for drug developers working in Alzheimer's disease. Recent negative trial results have been attributed to a lack of efficacy and important safety concerns. Furthermore, demonstrated target engagement has rarely translated into demonstrable clinical efficacy. Cognitive data might provide valuable insights at various points during drug development, and a thoughtful and robust set of decision-making criteria, specified a priori, can and should be applied under many circumstances. This review provides insights into how to utilize cognitive data for Go/No-Go decisions, with an emphasis on how these cognitive criteria differ depending on the context (e.g., stage of development, mechanism of action and trial design).
科研通智能强力驱动
Strongly Powered by AbleSci AI