Integrating predictive biomarkers and classifiers into oncology clinical development programmes

被引：82

作者：

Beckman, Robert A. ^{[1
]}

Clark, Jason ^{[2
]}

Chen, Cong ^{[3
]}

机构：

[1] Daiichi Sankyo Pharmaceut Dev, Clin Res Oncol, Edison, NJ 08837 USA

[2] Incyte Pharmaceut, Biostat, Wilmington, DE 19880 USA

[3] Merck Res Labs, Biostat & Res Decis Sci, N Wales, PA 19454 USA

来源：

NATURE REVIEWS DRUG DISCOVERY | 2011年 / 10卷 / 10期

关键词：

METASTATIC BREAST-CANCER; PHASE-II; MONOCLONAL-ANTIBODY; COLORECTAL-CANCER; TRIAL DESIGN; THERAPY; CHEMOTHERAPY; MUTATIONS; SIGNATURE; SPECIMENS;

D O I：

10.1038/nrd3550

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

The future of drug development in oncology lies in identifying subsets of patients who will benefit from particular therapies, using predictive biomarkers. These technologies offer hope of enhancing the value of cancer medicines and reducing the size, cost and failure rates of clinical trials. However, examples of the failure of predictive biomarkers also exist. In these cases the use of biomarkers increased the costs, complexity and duration of clinical trials, and narrowed the treated population unnecessarily. Here, we present methods to adaptively integrate predictive biomarkers into clinical programmes in a data-driven manner, wherein these biomarkers are emphasized in exact proportion to the evidence supporting their clinical predictive value. The resulting programme demands value from predictive biomarkers and is designed to optimally harvest this value for oncology drug development.

引用

页码：735 / 748

页数：14

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