Background A biomarker is a defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions. Biomarker modalities are diverse, and can include ‘omics, imaging, behavioral, digital and physiologic endpoints, as well as composite biomarkers or biomarker signatures. Biomarkers are critical to the discovery and development of therapeutics and can serve a variety of functions including the verification of therapeutic target engagement, improving trial design by patient stratification, and facilitating clinical care decisions. Despite the active pace of discovery of novel biomarker candidates, few biomarkers progress beyond discovery to analytical validation and clinical practice, and robust, well-validated biomarkers for use in Phase II and Phase III clinical trials remain scant. Thus, there is a critical need to advance validation of biomarkers to improve therapeutic development and clinical care, particularly for disorders of the nervous system where advancing therapeutics from discovery to the market are notoriously challenging. This PAR is intended to address the gap in biomarker validation by encouraging rigorous clinical validation of a candidate biomarker or biomarker signature. Clinical Validation is defined as establishing that the biomarker acceptably identifies, measures or predicts the concept of interest within a defined context of use. The level of experimental rigor that is necessary depends upon the characteristics of the biomarker, the detection technology, and the intended category of biomarker (diagnostic, prognostic, predictive, pharmacodynamic/response, monitoring, safety, or susceptibility/risk) within the proposed context of use(s). Clinical validation establishes the biomarker’s relationship with the clinical outcome of interest and determines the statistical thresholds for decision making within a given context of use. The application should clearly describe how the proposed study plans to ensure broad and reliable clinical use across multiple sites. If analytical validation of the detection method is still needed, applicants are encouraged to apply for the companion PAR, “Analytical Validation of a Candidate Biomarker for Neurological or Neuromuscular Disorders (U01 - Clinical Trial Optional)”. Research Objectives Applications to this PAR must propose to conduct clinical validation of a biomarker or biomarker signature that already has strong proof of concept and biological rationale with evidence that the biomarker measures the concept of interest. Premise and proof of concept must include preliminary evidence that the biomarker/biomarker signature has been tested in an appropriate clinical population, using either prospective or retrospective data or samples and shows sufficient sensitivity and specificity to warrant additional investment. In addition, applications to this PAR must include evidence that the detection method for the biomarker has been analytically validated, with known performance parameters and evidence that the it can be reliably used in multiple sites using a standardized protocol. This funding opportunity uses a cooperative agreement, milestone driven mechanism that enables significant input from NIH staff to assist investigators with preparing and evaluating their clinical validation strategy. This PAR is designed to enable the collection of the package of evidence needed for FDA Biomarker Qualification Submission, which is encouraged, but not required, as part of the application process. For more information on the Biomarker Qualification program see: https://www.fda.gov/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/BiomarkerQualificationProgram/default.htm Entry Criteria Entry Criteria should include the following: Within NINDS mission: The project should focus on validation of a biomarker to be used as a tool in the diagnosis, treatment, or prevention of diseases and conditions within the NINDS mission. Context of Use: The intended Context of Use (COU) should be identified and applications should include a statement with the heading "Context of Use" that fully and clearly describes the way the biomarker is expected to be used. Considerations involved in defining the COU should include the biomarker category (susceptibility/risk, diagnostic, monitoring, prognostic, predictive, pharmacodynamic/response, or safety), the biomarker modality, the method of detection and the clinical population characteristics. The Context of Use is critical for determining the experimental design and level of validation required, therefore it should be carefully considered and clearly defined. Context of Use statements are discussed extensively in the Framework for Defining Evidentiary Criteria for Biomarker Qualification developed by the Biomarkers Consortium: https://fnih.org/sites/default/files/final/pdf/Evidentiary%20Criteria%20Framework%20Final%20Version%20Oct%2020%202016.pdf. Evidence of preliminary validation of the biomarker: Preliminary data illustrating that the biomarker reflects the intended pathophysiology and/or clinical endpoint appropriate for the Context of Use are required. Evidence should include a preliminary estimate of the clinical sensitivity and specificity, as defined by Receiver Operator Characteristic Analysis (ROC). Established detection method: Evidence demonstrating that the detection method has been analytically validated should be included in a subsection and/or table along with a description of the performance characteristics of the detection method. Supporting evidence should be consistent with FDA standards and include information regarding control and understanding of pre-analytic variables, along with the accuracy, precision, analytical sensitivity/specificity, effects of known interfering substances/signals, dynamic range, and any quality control metrics included in the standardized technical protocol. Application Characteristics A strong justification for the clinical and/or research need of the biomarker should be included. The feasibility, including potential added clinical burden and cost, of incorporating the biomarker into clinical practice and/or research protocols should be addressed. The study design should definitively test the clinical sensitivity and specificity of the biomarker within the population(s) of interest. The outcome(s) used to validate the biomarker/biomarker signature must be clearly stated and justified. Multi-site study designs to ensure the robustness of the biomarker validation and inclusion of the appropriate representative clinical population is expected. Use of a single site design should be scientifically justified. Milestones describing the metrics for evaluating project progress to assess success in achieving each of the research plan’s objectives must be included. The Biomarker or biomarker signature should be described using the FDA-NIH Biomarker Working Group BEST (Biomarkers, EndpointS, and other Tools) Resource, available from: https://www.ncbi.nlm.nih.gov/books/NBK326791/. Biomarker categories include: monitoring biomarkers to track the success of a therapeutic intervention or disease progression diagnostic biomarkers for detecting clinical manifestation of disease prognostic biomarkers for predicting outcomes predictive biomarkers for determining responders and non-responders to a therapeutic intervention pharmacodynamic/response biomarkers for demonstrating therapeutic target engagement safety biomarkers to indicate the likelihood, presence, or extent of an adverse effect susceptibility/risk biomarkers that indicate the potential for developing a disease or medical condition in an individual who does not currently have a clinically apparent disease Although an individual indicator may be useful as more than one category of biomarker (i.e. both diagnostic and monitoring) the type of evidence required to validate it depends on the biomarker category specified; for example, a monitoring biomarker would need to demonstrate robustness in a longitudinal study design whereas a diagnostic may be a cross sectional design. Thus, defining the biomarker category(ies) is essential to developing the experimental design and performance characteristics necessary to validate it. The research strategy should clearly describe how the application will utilize a rigorous design, execution, and interpretation of the proposed studies. NINDS encourages investigators, whenever possible, to address these elements directly in their applications. Clinical validation can include the following metrics with use of FDA guidance standards appropriate for the context of use: Sensitivity and specificity of the biomarker within the Context of Use, including methods for binary and/or continuous analysis. Area Under the Curve (AUC) as determined by Receiver Operator Characteristic (ROC) Analysis Estimation of the prevalence of the marker within subjects or patients for the intended clinical context. Establishing the appropriate cut-off or threshold for the biomarker for decision making within the context of use. Positive Predictive Value Negative Predictive Value Data obtained after completing the project from this PAR should be appropriate for use as a component of the package required for FDA qualification of the biomarker, or for other methods of integrating the biomarker and its detection method into the processes of therapeutic development or clinical practice Definitions of Clinical Validation Metrics Sensitivity: The proportion of true (actual) positive findings that are correctly identified, also known as the true positive rate or probability of detection Specificity: The proportion of true (actual) negative findings that are correctly identified, also known as the true negative rate Receiver Operator Characteristic (ROC) Area under the Curve: Illustrates discrimination ability measured as the area under the curve of a graph where sensitivity is plotted against specificity Positive predictive value (PPV): The probability that a positive screening test result is true, taking into account the prevalence of the disease or condition in the population being measured; Negative predictive value (NPV): The probability that a negative screening test result is true, taking into account the prevalence of the disease or condition in the population being measured. Responsiveness criteria Responsive studies include clinical validation of biomarkers that indicate pharmacodynamic responses to therapeutics, predict efficacy or safety response as well as those for diagnostic, prognostic and disease progression or risk/susceptibility detection. Applications Not Responsive to this FOA Non-responsive studies include those seeking to develop therapeutic agents or devices as a primary intent, as well as those seeking to answer specific questions about, clinical efficacy, effectiveness, and/or clinical management as a primary intent. Studies using animal models or in vitro cellular models are non-responsive. Studies that fail to include milestones are also considered non-responsive. Non-responsive applications will be administratively withdrawn without review. Collaborations Multi-disciplinary collaboration among scientific investigators, developers, clinicians, statisticians, consultants, and clinical laboratory staff must be an integral part of the application. Projects proposed for this PAR should utilize multi-site design as applicable, with standardized data stewardship to ensure that data are reusable and accessible. Foreign collaborations that can increase the biomarker utility or uptake are encouraged, but must be clearly justified. Investigators are encouraged to form collaborations with individuals knowledgeable in the FDA qualification process as well as those familiar with the process of biomarker validation, including statistical design and analysis experts. Leveraging Existing Resources Applicants are encouraged to leverage existing research resources if appropriate for their studies. Such resources may include clinical biospecimen samples from the NINDS BioSEND (https://biosend.org/) or other existing biospecimen, imaging and data repositories or ongoing clinical trials. Leveraging the research resources and support from advocacy groups, private research foundations, academic institutions, other government agencies and the NIH Intramural program are also encouraged. Project Milestones A project timeline with annual milestones must be included in the application (see Section IV). Milestones should describe project decision points with quantitative metrics for go/no-go decision making throughout the funding period. The NIH Program Official will contact the applicant to discuss the proposed milestones prior to the award. The Program Officer and Scientist Officer will discuss with the Program Director(s)/Principal Investigator(s) any recommended changes to the research plan or suggestions from peer reviewers, and the plan will be revised as appropriate prior to the award. Reproducibility and Data Sharing To improve reproducibility and community uptake, investigators are expected to share code/scripts, analytic tools/statistical models, protocols/processes and metadata before the end of the project’s period of performance. The resource sharing plan should describe where information and data will be shared, including where the original controlled datasets exist and how to request access to them. Investigators should incorporate plans for sharing and dissemination of the data, protocols, and any analytical methods in their research sharing plan and project timeline. Applicants should ensure their consent forms include language that allows sharing data and bio-samples for broad future research goals. Budgets should reflect any costs associated with these efforts. Information on many of the available NIH supported, or frequently used, repositories is available at: https://www.nlm.nih.gov/NIHbmic/nih_data_sharing_repositories.html Applicants collecting biofluid samples from prospectively enrolled study participants are expected to share samples through the NINDS biomarker repository, BioSEND (https://biosend.org/) to provide the broader scientific community with a data resource for hypothesis generation and test validation. Applicants should contact BioSEND to incorporate sharing plans and cost in their application. Pre-Application Consultation Under this Cooperative Agreement mechanism, NINDS Program Staff will have substantial communication and involvement with researchers in decision making prior to award and during the conduct of the study to provide oversight of data and safety monitoring, ensure the timely completion of the proposed studies and to maximize the positive impact of the studies on upcoming clinical trials. Applicants are strongly encouraged to consult with NINDS Program Staff early on during the planning for an application. This early contact will provide an opportunity to discuss and clarify NINDS policies and guidelines, including the scope of project relative to the NINDS mission and intent of this PAR. These discussions can also provide any needed clarification development of an appropriate timeline and milestone plan. Funding Considerations Applications within the top scoring meritorious range will be considered for funding. Within that range, priority may be placed on applications that fill a critical program gap to ensure biomarker development that is reflective of the breadth of disorders and conditions within NINDS’s mission. Additionally, priority will be given to biomarkers that: 1) address an unmet medical need, 2) are supported by a strong biological rationale, 3) include a carefully designed plan for performance evaluation, 4) include a plan for standardization of samples and data collection for use in validation and 5) provide a strong justification for the utility of the biomarker in the clinical setting or the added value in a clinical research design.