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通过人类数据驱动发现(HD)重塑药物研发

Rewiring Drug Research and Development through Human Data-Driven Discovery (HD).

作者信息

Jackson David B, Racz Rebecca, Kim Sarah, Brock Stephan, Burkhart Keith

机构信息

Molecular Health GmbH, 69115 Heidelberg, Germany.

Division of Applied Regulatory Science, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993, USA.

出版信息

Pharmaceutics. 2023 Jun 7;15(6):1673. doi: 10.3390/pharmaceutics15061673.

Abstract

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and, as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry- and science-related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through the pursuit of a Human Data-driven Discovery (HD) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather on the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, the rational design of combination therapies and the global response to the COVID-19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human-focused, systems-based approach to drug discovery and research.

摘要

在一个技术进步无与伦比的时代,制药行业正努力将数据转化为更高的研发效率,并进而为患者研发新药。在此,我们简要回顾一下围绕这场违反直觉的创新危机经常讨论的一些问题。从行业和科学相关因素两方面来看,我们认为传统临床前研究正在用不太可能在患者身上取得成功的数据和候选药物使研发流程前期负担过重。通过应用第一性原理分析,我们突出了关键问题所在,并就如何通过追求以人类数据驱动的发现(HD)范式来纠正这些问题提出建议。与颠覆性创新的其他例子一致,我们认为新的成功水平并不依赖于新发明,而是依赖于对现有数据和技术资产的战略整合。为支持这些建议,我们通过最近在药物安全性分析与预测、药物重新定位、联合疗法的合理设计以及全球对新冠疫情的应对等领域发表的概念验证应用,突出了HD的力量。我们得出结论,创新者必须在加快迈向以人类为中心、基于系统的药物发现与研究方法的道路上发挥关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f99e/10303279/4a2ecdabe83c/pharmaceutics-15-01673-g001.jpg

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