Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization

被引:146
作者
Amur, S. [1 ]
LaVange, L. [2 ]
Zineh, I. [3 ]
Buckman-Garner, S. [1 ]
Woodcock, J. [4 ]
机构
[1] US FDA, Ctr Drug Evaluat & Res, Off Translat Sci, Silver Spring, MD 20993 USA
[2] US FDA, Ctr Drug Evaluat & Res, Off Translat Sci, Off Biostat, Silver Spring, MD USA
[3] US FDA, Ctr Drug Evaluat & Res, Off Translat Sci, Off Clin Pharmacol, Silver Spring, MD USA
[4] US FDA, Ctr Drug Evaluat & Res, Silver Spring, MD USA
关键词
SURROGATE END-POINTS; DRUG DEVELOPMENT; PRINCIPAL STRATIFICATION; CLINICAL-TRIALS; PROGRESSION; RNA; VALIDATION; PARADIGM; ISSUES; LEVEL;
D O I
10.1002/cpt.136
中图分类号
R9 [药学];
学科分类号
100702 [药剂学];
摘要
The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration.
引用
收藏
页码:34 / 46
页数:13
相关论文
共 40 条
[1]
Prentice's approach and the meta-analytic paradigm: A reflection on the role of statistics in the evaluation of surrogate endpoints [J].
Alonso, A ;
Molenberghs, G ;
Burzykowski, T ;
Renard, D ;
Geys, H ;
Shkedy, Z ;
Tibaldi, F ;
Abrahantes, JC ;
Buyse, M .
BIOMETRICS, 2004, 60 (03) :724-728
[2]
Surrogate marker evaluation from an information theory perspective [J].
Alonso, Ariel ;
Molenberghs, Geert .
BIOMETRICS, 2007, 63 (01) :180-186
[3]
A prototypical process for creating evidentiary standards for biomarkers and diagnostics [J].
Altar, C. A. ;
Amakye, D. ;
Bounos, D. ;
Bloom, J. ;
Clack, G. ;
Dean, R. ;
Devanarayan, V. ;
Fu, D. ;
Furlong, S. ;
Hinman, L. ;
Girman, C. ;
Lathia, C. ;
Lesko, L. ;
Madani, S. ;
Mayne, J. ;
Meyer, J. ;
Raunig, D. ;
Sager, P. ;
Williams, S. A. ;
Wong, P. ;
Zerba, K. .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2008, 83 (02) :368-371
[4]
Am Diabetes Assoc, 2006, DIABETES CARE, V29, pS4
[5]
[Anonymous], INN STAGN CHALL OPP
[6]
Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework [J].
Atkinson, AJ ;
Colburn, WA ;
DeGruttola, VG ;
DeMets, DL ;
Downing, GJ ;
Hoth, DF ;
Oates, JA ;
Peck, CC ;
Schooley, RT ;
Spilker, BA ;
Woodcock, J ;
Zeger, SL .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2001, 69 (03) :89-95
[7]
Reproducibility in Science Improving the Standard for Basic and Preclinical Research [J].
Begley, C. Glenn ;
Ioannidis, John P. A. .
CIRCULATION RESEARCH, 2015, 116 (01) :116-126
[8]
Surrogate threshold effect: An alternative measure for meta-analytic surrogate endpoint validation [J].
Burzykowski, Tomasz ;
Buyse, Marc .
PHARMACEUTICAL STATISTICS, 2006, 5 (03) :173-186
[9]
Power failure: why small sample size undermines the reliability of neuroscience [J].
Button, Katherine S. ;
Ioannidis, John P. A. ;
Mokrysz, Claire ;
Nosek, Brian A. ;
Flint, Jonathan ;
Robinson, Emma S. J. ;
Munafo, Marcus R. .
NATURE REVIEWS NEUROSCIENCE, 2013, 14 (05) :365-376
[10]
Buyse M, 2000, DRUG INF J, V34, P447, DOI 10.1177/009286150003400213