Mental and behavioral health disorders, including depression, anxiety, and addiction, affect about half of all Americans, with treatment costs nearing $200 billion annually. Yet, traditional diagnostics still rely heavily on subjective endpoints that fail to capture the complexity and immediacy of treatment response. To confront this challenge, the Advanced Research Projects Agency for Health (ARPA-H) released the Evidence-Based Validation and Innovation for Rapid Therapeutics in Behavioral Health (EVIDENT) Request for Solutions (RFS). This RSF aims to create objective measures that accelerate the development and deployment of rapid-acting behavioral health interventions.
EVIDENT TAs 1-3: Measuring and Predicting Therapeutic Response
Through EVIDENT, ARPA-H is seeking innovative approaches that leverage multimodal data, including biological, physiological, digital, and behavioral signals, to validate objective clinical endpoints for validation of emerging rapid-acting behavioral health interventions. The behavioral health interventions to be evaluated are broad, including neuroplastogens, neuromodulation modalities, and digital therapeutics such as virtual reality. Although these therapies show promise for reducing symptoms within hours or days, the field continues to rely on subjective assessments that limit scientific progress and regulatory acceptance. To revolutionize the way we evaluate behavioral health innovations, the first EVIDENT solicitation is structured around three Technical Areas (TAs), wherein each TA is designed to address a critical knowledge gap in behavioral health research:
Technical Area 1 (TA1): Objective Measurement of Clinical Change
The long-term goal is the ability to measure a patient’s indicator(s) of behavioral health continuously, with minimally invasive and scalable technology; therefore, the goal of TA1 is to identify likely biomarkers for continuous behavioral health monitoring. Modalities such as neuroimaging, wearables, and digital phenotyping are sought, for biomarkers that reliably monitor neuroplastic and clinical changes on a timescale of hours to days.
Technical Area 2 (TA2): Mechanisms of Rapid and In-Session Change
Given the importance of treatment sessions between a patient and facilitator in both immediate and long-term mental health outcomes, TA2 focuses on unobtrusive and multimodal data collection during treatment sessions. The goal is to discover interpersonal and therapy dynamics that increase effectiveness of interventions. TA2 Performers will capture in-session data from patients, facilitators, and the environment to identify real-time predictors of clinical effectiveness.
Technical Area 3 (TA3): Personal Risk and Durability Profiles
As personalized behavioral health interventions require prediction of both risk and long-term efficacy of rapid-acting interventions, TA3 aims to generate predictive models for clinical efficacy and risk. These models will link clinical history, biomarkers, and genetic factors to predict individual risk for an adverse event and likelihood of immediate and durable response to treatment post-intervention.
To achieve these TAs, Proposers may analyze existing data or collect and analyze new data supplementary to existing protocols. Across all TAs, ARPA-H emphasizes the delivery of deidentified multimodal datasets and biospecimens to an ARPA-H designated Data Repository to accelerate downstream research. Performers may propose to one or multiple TAs; a separate Solution Summary submission is required for each TA. A subset of proposers will be invited back to provide a Solution Pitch.
Program Structure
The first EVIDENT program operates as a milestone-based effort with a maximum 24-month period of performance. Awards are designed to supplement existing IRB-approved studies rather than fund original trial recruitment.
Funding Information
ARPA-H anticipates awarding fixed-price, milestone-based awards with the following characteristics:
- Award Size: Each award is expected to be fixed at $4 million total
- Period of Performance: Up to 24 months
Note: Cost Proposals are not required, because award amounts are fixed
EVIDENT TA4: Multimodal Data Collection
The second EVIDENT solicitation seeks Performers to collect multimodal, longitudinal data and biological samples for registered, interventional clinical trials testing any emerging, rapid-acting treatment. Behavioral health conditions of interest include anxiety, depression, substance use disorder, and posttraumatic stress disorder (PTSD), but others may be considered. Performers will collect psychological, social, and digital health data before treatment, one week after treatment, and roughly three months after treatment, with the option to extend follow-up data collection to six and twelve months.
All teams are expected to follow standardized operating procedures (to be released in an amendment) and must submit deidentified data for FDA-approved clinical endpoints. In addition to the essential data collection, Performers may add biological sample collection (saliva, blood, stool, etc) to their protocols. Awardees will collect and deliver deidentified data and biological samples to an ARPA-H-designated Rapid Response Data Repository, which will support future biomarker discovery, enable validation of objective measures of clinical response, and accelerate regulatory acceptance of future behavioral health therapies.
The expected Period of Performance is up to 24 months. This single-phase EVIDENT TA will grant awards on a rolling basis to support rapid mobilization of data collection activities.
Key Dates for EVIDENT (TAs 1-4):
- Proposers’ Day: December 10, 2025, from 8:00 a.m. to 4:30 p.m. ET
- Submission Portal Opens: December 11, 2025 for TAs 1-3, November 24 for TA 4
- Questions Deadline: December 12, 2025
- Solution Summary Due: December 22, 2025 at 1:00 p.m. ET for TAs 1-3; TA 4 accepts Solution Summaries on a rolling basis until funding is expended.
Driving Better Outcomes in Behavioral Health
The EVIDENT program will reshape behavioral health care by developing validated and objective clinical endpoints, integrating multimodal biomarker data, and improving the identification of rapid treatment effects. These capabilities will allow clinicians to track therapeutic change in real time, match patients to the most effective interventions, and forecast long-term outcomes. Ultimately, this will help reduce the burden of mental health problems like depression, anxiety, PTSD, and substance use disorder for millions of Americans.
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