Biomarker definitions and their applications

Abstract

Biomarkers are critical to the rational development of medical therapeutics, but significant confusion persists regarding fundamental definitions and concepts involved in their use in research and clinical practice, particularly in the fields of chronic disease and nutrition. Clarification of the definitions of different biomarkers and a better understanding of their appropriate application could result in substantial benefits. This review examines biomarker definitions recently established by the U.S. Food and Drug Administration and the National Institutes of Health as part of their joint Biomarkers, EndpointS, and other Tools (BEST) resource. These definitions are placed in context of their respective uses in patient care, clinical research, or therapeutic development. We explore the distinctions between biomarkers and clinical outcome assessments and discuss the specific definitions and applications of diagnostic, monitoring, pharmacodynamic/response, predictive, prognostic, safety, and susceptibility/risk biomarkers. We also explore the implications of current biomarker development trends, including complex composite biomarkers and digital biomarkers derived from sensors and mobile technologies. Finally, we discuss the challenges and potential benefits of biomarker-driven predictive toxicology and systems pharmacology, the need to ensure quality and reproducibility of the science underlying biomarker development, and the importance of fostering collaboration across the entire ecosystem of medical product development. Impact statement Biomarkers are critical to the rational development of medical diagnostics and therapeutics, but significant confusion persists regarding fundamental definitions and concepts involved in their use in research and clinical practice. Clarification of the definitions of different biomarker classes and a better understanding of their appropriate application could yield substantial benefits. Biomarker definitions recently established in a joint FDA-NIH resource place different classes of biomarkers in the context of their respective uses in patient care, clinical research, or therapeutic development. Complex composite biomarkers and digital biomarkers derived from sensors and mobile technologies, together with biomarker-driven predictive toxicology and systems pharmacology, are reshaping development of diagnostic and therapeutic technologies. An approach to biomarker development that prioritizes the quality and reproducibility of the science underlying biomarker development and incorporates collaborative regulatory science involving multiple disciplines will lead to rational, evidence-based biomarker development that keeps pace with scientific and clinical need.

Keywords: Biomarkers; cardiovascular; epidemiology; medicine; monitoring; pharmacology/toxicology.

Figure 1.

Steps in the evaluation framework for biomarkers. Adapted from: Institute of Medicine. Evaluation of biomarkers and surrogate endpoints in chronic disease. Summary. Washington, D.C.: National Academies Press, 2010.

Figure 2.

Reasons for failure of surrogate endpoints. (a) In this situation, the disease affects the putative surrogate endpoint and the true clinical outcome via different mechanisms, so that any correlation between the two is not causal. (b) The intervention affects the putative surrogate endpoint, which has some impact on the true clinical outcome. Unfortunately, the disease affects the true clinical outcome by other mechanisms, which make the change in the putative surrogate an unreliable measure of change in the true clinical outcome. (c)The intervention affects the putative surrogate endpoint through mechanisms independent of its effect on the true clinical outcome. Thus, the change in the surrogate endpoint is not a reliable measure of the change in the true clinical outcome. (d) All of the above issues are in play. Adapted from: Fleming TR, DeMets DL. Surrogate end points in clinical trials: are we being misled? Ann Intern Med 1996;25:605–13.

Figure 3.

Multiple components, biological pathways, and outcomes all contribute to the complexity of using biomarkers and surrogate endpoints in the context of chronic disease. Adapted from: Institute of Medicine. Evaluation of biomarkers and surrogate endpoints in chronic disease. Summary. Washington, D.C.: National Academies Press, 2010.