Key Dates

Related Announcements

Issued by

National Institute on Drug Abuse (NIDA)

Purpose

Background

Biomarker identification and implementation into routine clinical care was pioneered for treating cancer. Substantial efforts in implementing BRCA screening is associated with decreased breast and ovarian cancer incidence rates, reduced mortality, improved clinical decision making, and is cost-effective. The journey of BRCA gene discovery to its successful implementation into the cascade of routine health care has illustrated how biomarkers can transform health care delivery.

Substance use disorder (SUD) research scientists have been in pursuit of identifying biomarkers to predict diagnostic severity, disease prognosis, and tailored treatment outcomes for the last 40 years. A large body of evidence, including replication efforts, have uncovered several promising biomarker candidates, largely established in the tobacco field. For example, fast nicotine metabolizers, identified by the nicotine metabolite ratio, may respond better to varenicline whereas slow metabolizers may respond better to nicotine replacement therapy. Behaviorally, high impulsivity (i.e., selection of smaller, sooner over larger, delayed rewards) is associated with nicotine dependence and predictive of unsuccessful quit attempts. Furthermore, geneticists have identified that variants in the CHRNA5 gene is associated with greater risk of developing nicotine dependence, lung cancer, and chronic obstructive pulmonary disorder. However, in contrast to cancer caused by BRCA mutation, tobacco use disorder (TUD) is a polygenic disorder and includes complex gene-environment interactions that may complicate genetic biomarker discovery and implementation.

There are several different types of biomarkers, and NIDA intends to focus on those that can be utilized in routine medical care to personalize health services delivery for TUD. For the purposes of this RFI, NIDA is soliciting comments on the following biomarker types and categories:

Biomarker Type:

• Behavioral/cognitive/affective phenotypes (e.g., delay discounting, reward processing, cue reactivity, negative affect, digital phenotyping)
• Neuroimaging signatures (e.g., fMRI, structural MRI, PET, EEG, fNIRS)
• Genetics
• Biospecimens (physiological indicator, blood, saliva, etc.)

Biomarker Categories:

• Diagnostic biomarker is a biomarker used to detect or confirm presence of a disease or condition of interest or to identify individuals with a subtype of the disease.
• Prognostic biomarker is a biomarker used to identify likelihood of a clinical event, disease recurrence or progression in patients who have the disease or medical condition of interest.
• Predictive biomarker is a biomarker used to identify individuals who are more likely than similar individuals without the biomarker to experience a favorable or unfavorable effect from exposure to a medical product or an environmental agent.
• Safety biomarker is a biomarker measured before or after an exposure to a medical product or an environmental agent to indicate the likelihood, presence, or extent of toxicity as an adverse effect.

Information Requested

Despite the widespread recognition that SUD is a complex chronic condition with biological etiologies that can be objectively measured, TUD service delivery has not evolved at the same pace as clinical research. To date, treatment decisions are largely driven by self-report and service availability, and successful treatments are objectively validated with cotinine or carbon monoxide measurement. Health care providers under-utilize biomarker data points to inform clinical decisions or monitor a patent’s responsiveness to treatment. Until the SUD field can identify and leverage the utility of biomarkers for use in routine clinical practice, TUD treatment services are likely to remain fragmented from general healthcare and slow to innovate.

NIDA recognizes that each biomarker presents its own unique challenges in building the evidence base and readiness for clinical implementation. For example, some biomarkers may still be under development in human laboratory studies but are gaining momentum and may benefit from recommendations from health care providers and health services researchers. Other biomarkers may have accumulated convincing evidence and may be prime to start evaluating its utility in informing clinical care decisions. To address these barriers in biomarker research and implementation, NIDA is requesting information from clinical scientists engaging in biomarker discovery research; health care providers who provide services for TUD; and SUD health services researchers who study the implementation of innovations. TUD is a focus of this RFI due to its advanced position in regard to available treatments among all SUDs. NIDA seeks comments on any or all of, but not limited to, the following topics:

Clinical Researchers/Human laboratory scientists

• Confidence in/evaluation of the evidence for the biomarker, including sample sizes, replication efforts, predictive power, specificity, and explained variance
• Recommended types of data to include in future biomarker research that would facilitate and increase clinical utility (e.g., number needed to treat, test-retest, sensitivity, specificity, comparison against traditional self-reports, frequency of screening)
• Identify research, infrastructure and other types of barriers underlying data replication and reaching larger sample sizes, and provide recommendations towards addressing these challenges
• Identify data sharing/Big Data practices, opportunities, and barriers to facilitate/advance biomarker research and development
• Recommended strategies for coordinated research efforts to build the clinical research evidence base
• Recommended actions to communicate biomarker findings with health care providers/health services researchers

SUD Services Researchers/Health Care Providers

• Preferred biomarker category (i.e., diagnostic, prognostic, predictive, safety) that has potential to optimize clinical decision making and personalize patient treatment
• Level of evidence needed to persuade key health care provision stakeholders to integrate a biomarker into routine cascade of clinical care (e.g., replication success, effect sizes, predictive power, explained variance, FDA approval, specificity, etc.)
• Recommended data to include in future biomarker research that would facilitate and increase clinical utility (i.e., number needed to treat, test-retest, sensitivity, specificity, comparison against traditional self-report questionnaires, frequency of screening, etc.)
• Vision for how to integrate a biomarker into routine clinical care of TUD patient, and how this may alter typical daily operations in a physician’s office or hospital (e.g., triaging patients, care management, tailoring treatment plans, etc.)
• Recommended initial health care setting that could be most amenable for including a behavioral biomarker vs neuroimaging biomarker vs a genetics biomarker vs biospecimen biomarker
• Challenges in implementing biomarker information into clinical care (e.g., effort to collect the biomarker data, cost, reimbursement, regulatory issues and personnel with the appropriate scientific expertise)
• Recommended strategies to facilitate bidirectional communication with human laboratory scientists on scientific advancements in biomarker research in a timely manner

How to Submit a Response

Please state the biomarker type and category and its potential application within the continuum of health care provision. Responses must be received by 11:59:59 pm (ET) on October 1, 2020. All comments must be submitted electronically to NIDAbiomarker@nih.gov.

Responses to this RFI are voluntary and may be submitted anonymously. Please do not include any personally identifiable or other information that you do not wish to make public. Proprietary, classified, confidential, or sensitive information should not be included in responses. The responses will be reviewed by NIH staff, and individual feedback will not be provided to any responder. The Government will use the information submitted in response to this RFI at its discretion. The Government reserves the right to use any submitted information on public websites, in reports, in summaries of the state of the science, in any possible resultant solicitation(s), grant(s), or cooperative agreement(s), or in the development of future funding opportunity announcements. This RFI is for informational and planning purposes only and is not a solicitation for applications or an obligation on the part of the Government to provide support for any ideas identified in response to it. Please note that the Government will not pay for the preparation of any information submitted or for use of that information. No basis for claims against the U.S. Government shall arise because of a response to this request for information or from the Government’s use of such information.

Inquiries

Please direct all inquiries to:

Shelley Su, PhD
National Institute on Drug Abuse
Telephone: 301-402-3869
Email: NIDAbiomarker@nih.gov