Biomarker Development and Validation: Establishing Standards of Evidence for their Context of Use in Clinical Trials
Linda Brady, Ph.D.
Division of Neuroscience and Basic Behavioral Science
This initiative is intended to encourage the necessary later stages of development and validation of biomarkers with putative value for use in clinical trials, including multi-sites testing and validation for regulatory ‘context of use’ (e.g., diagnostic, enrichment, stratification). The focus would be on developing biomarkers in priority areas based on unmet medical need, lack of objective endpoints, reasonable development path, and traction/feasibility. Examples of areas of interest include the psychosis prodrome, autism spectrum disorder, and major mood disorders, although validated biomarkers are lacking for all mental disorders and associated domains of dysfunction (e.g., emotion regulation, executive function, impulsivity, social communication, and memory). This initiative would facilitate coordination and/or partnerships with relevant public-private consortia efforts such as those of the Biomarkers Consortium Neuroscience Steering Committee, the Innovative Medicines Initiative, international efforts, foundations, and regulatory agencies.
A biological marker or biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathologic processes, or biological responses to a therapeutic intervention 1. A biomarker can be a physiologic, pathologic, or anatomic characteristic or measurement that is thought to relate to some aspect of normal or abnormal biologic function or process. Examples of biomarkers include genetic alleles, proteins (e.g., in cerebrospinal fluid or serum), imaging or electrophysiological-based measures, physiological measures, cognitive measures (e.g., working memory), or a composite biomarker 2. Diagnostic, prognostic, and predictive biomarkers can be considered for qualification by the Food and Drug Administration (FDA) for use in clinical trials of novel therapeutics.
The Director of the Center for Drug Evaluation and Research at the FDA has commented on the limited development of biomarkers to date, “Although, crucial to product development and medical care, biomarker development has lagged significantly behind therapeutic development. Most biomarkers are discovered in academic labs and are hard to duplicate elsewhere. Just a small number are developed into commercially available laboratory tests. Even fewer are integrated into clinical care. The evidence base for their use often remains slim or controversial. Most are not adopted for regulatory use because of absence of evidence. The FDA has typically waited for widespread community acceptance before accepting a new biomarker. This approach is not ideal for translating new science into practice” (Janet Woodcock, FDA, HHMI Biomarker Workshop, October, 2013).
Early discovery of biomarkers in mental disorders has been supported through NIH research grants, while further development and validation of these exploratory biomarkers has not been a focus of investigator-initiated research due to complexity of the studies, the perceived lack of innovation by investigators and reviewers, and until recently, limited FDA guidance on the regulatory requirements (see Qualification Process for Drug Development Tools (Draft Guidance) and http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/). The private sector has capacity for developing biomarkers for internal decision-making (e.g., for assessing target engagement in brain or impacting biology), but significant challenges exist for identifying and developing brain-based biomarkers or biosensors that identify patient subpopulations.
With the failure of trials for mental disorders to establish whether there is a subpopulation that benefits from novel mechanism of action therapeutics, there is an urgent need for further development and validation of predictive biomarkers (disease subtype, prognostic, outcomes). Biomarkers can help to reduce uncertainty in therapeutic development and evaluation by objectively identifying subjects for inclusion in a trial, contributing to appropriate dose selection, and providing quantifiable predictions about drug performance and clinical outcomes (clinically-meaningful change).
Currently, there are a large number of candidate biomarkers of disease state or treatment response (e.g., genetic, imaging, electrophysiology, biosensor, or functional domain-based biomarkers) identified by investigators which provide a good starting point for further development to validate or invalidate their context of use. Among these, biomarkers of greatest interest are those with putative value for influencing clinical practice because they predict treatment outcome or disease prognosis. The development and validation of biomarker technologies to assess and monitor clinically-meaningful change in real-time outcomes and function are of interest.
Areas of interest include:
- Analytical 3 and clinical 4 validation.
- Understanding sources of technical and biological variability in biomarker measures, including test-retest reliability (intra-subject, inter-site, between site), task-specific brain activation (signal strength), longitudinal evaluation of measurement properties (ability to detect change over time), data quality, and data analyses.
- Multi-site testing to inform reproducibility and create standardization of protocols for the biomarker and its intended use.
- Establishing consensus methods and evidentiary standards to validate biomarkers, or composite biomarkers, for their intended use.
1Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69: 89–95, 2001.
2A composite biomarker consists of several individual biomarkers that are combined in a stated algorithm to reach a single interpretive readout.
3Analytical validation: the ability of an assay to accurately and reliably measure the analyte of interest in the laboratory and in biospecimens that are representative of the population of interest
4Clinical validation: the detection or prediction of an associated disorder/domain of function based on measurements from the targeted patient group