Opportunities and challenges in phenotypic drug discovery: an industry perspective
Opportunities and challenges in phenotypic drug discovery: an industry perspective
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DOI：
10.1038/nrd.2017.111
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发表时间：
2017-08-01
影响因子：
120.1
通讯作者：
Prunotto, Marco
中科院分区：
文献类型：
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作者：
Moffat, John G.;Vincent, Fabien;Prunotto, Marco
表型药物发现(PDD)方法不依赖于特定药物靶点的身份知识或关于其在疾病中作用的假设，这与过去30年来在制药行业广泛使用的基于靶点的策略形成了鲜明对比。然而，近年来，人们对PDD方法的兴趣重新抬头，因为它们有潜力解决尚未完全了解的疾病的复杂性，它们有望提供一流的药物，以及基于细胞的表型筛选工具的重大进展。然而，PDD方法也面临着相当大的挑战，例如命中验证和目标去卷积。本文着重于制药行业从事PDD研究的研究人员吸取的教训，并考虑了在精确医学时代，组学知识在定义细胞疾病表型方面的影响，引入了可翻译链的概念。我们的目标尤其是确定PDD能够最好地为药物发现组合提供价值并能够为新药的识别和开发做出贡献的特征和领域，并阐明与PDD相关的挑战和不确定性，以帮助设定对其收益和成本的现实预期。
Phenotypic drug discovery (PDD) approaches do not rely on knowledge of the identity of a specific drug target or a hypothesis about its role in disease, in contrast to the target-based strategies that have been widely used in the pharmaceutical industry in the past three decades. However, in recent years, there has been a resurgence in interest in PDD approaches based on their potential to address the incompletely understood complexity of diseases and their promise of delivering first-in-class drugs, as well as major advances in the tools for cell-based phenotypic screening. Nevertheless, PDD approaches also have considerable challenges, such as hit validation and target deconvolution. This article focuses on the lessons learned by researchers engaged in PDD in the pharmaceutical industry and considers the impact of 'omics' knowledge in defining a cellular disease phenotype in the era of precision medicine, introducing the concept of a chain of translatability. We particularly aim to identify features and areas in which PDD can best deliver value to drug discovery portfolios and can contribute to the identification and the development of novel medicines, and to illustrate the challenges and uncertainties that are associated with PDD in order to help set realistic expectations with regard to its benefits and costs.