
Welcome to the sDHT Adoption Library, featuring NaVi
NaVi is a closed-environment AI research assistant that leverages a carefully curated library of more than 300+ vetted documents, including FDA guidance and industry best practices. NaVi helps you search and explore content across the sDHT Adoption Library and Roadmap using natural language questions.
The Library is intended to serve as a living resource. Content is added periodically as new guidance, standards, and peer-reviewed research are released.
Meet NaVi: Your AI-Powered Research Assistant
Library scope and selection
To ensure high-quality, relevant results, the Library follows a predefined scoping approach:
- Inclusions: FDA guidance, non-commercial standards, and peer-reviewed research (2018–Present) focused on sDHTs being used as measurement tools for medical products in U.S.-based clinical trials.
- Exclusions: Materials from single commercial entities, non-U.S. regulatory bodies (except select EMA guidances with direct U.S. cross-relevance), and conference proceedings, and conference proceedings.
Inclusion in the Library does not imply endorsement, completeness, or regulatory acceptability.
Library scope
Resources in the sDHT Adoption Library are identified using a predefined scoping approach and include publicly available FDA guidance, non-commercial standards and guidance, and peer-reviewed research relevant to sDHT use in U.S.-based clinical trials. Materials from single commercial entities, non-U.S. regulatory bodies, conference proceedings, and studies conducted exclusively outside the United States are excluded; inclusion does not imply endorsement or regulatory acceptability.
Last updated 2026: Library content is reviewed and updated on a periodic basis as new eligible materials become available.
Embedded Pragmatic Clinical trials Iniative
Embedded Pragmatic Clinical trials Iniative
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
PFMD Patient Engagement in Digital Health
PFMD Patient Engagement in Digital Health
Developing a step-by-step framework (PE Digital Roadmap) for implementing meaningful patient engagement in digital health
Clarifying the role of patients in designing and developing digital health solutions
Addressing challenges in digital health stakeholder alignment through the Stakeholder Expectations Matrix
Promoting transparency in patient involvement processes for digital health solutions
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Advancing the Integration of Digital Health Technologies in the Drug Development Ecosystem
Advancing the Integration of Digital Health Technologies in the Drug Development Ecosystem
Findings
The rapid advancement of sensor technology and connectivity has enabled high-frequency, longitudinal monitoring of physiological processes, yet the infrastructure for large-scale deployment remains resource-intensive. Current challenges include a lack of standardized terminology for digital decision-making tools and significant variability in environmental factors that affect sensor performance. Proprietary algorithms and device-specific barriers often hinder the verification and validation processes necessary for regulatory approval. Additionally, there is a distinct gap between granular digital features and their clinical relevance or meaningfulness to patients. Ethical concerns are emerging around data management, patient anxiety in psychiatric contexts, and the responsibility for addressing adverse events detected by remote monitoring.
Recommendations
Stakeholders should develop consensus-driven frameworks for standardized device performance reporting and environmental testing to streamline evaluations for specific contexts of use. The community should adopt a modular approach to data standards that bins requirements by concept of interest and disease-specific needs. Collaborative efforts between patients and developers are essential to bridge the gap between technical metrics and meaningful aspects of health. It is recommended to implement ""bring-your-own-device"" (BYOD) frameworks that ensure data reliability while supporting the inevitable evolution of technology during long-term studies. Researchers and clinicians must be trained in the ethical, legal, and social implications of digital health technology use, particularly regarding data privacy and the management of remote-detected safety signals.
Regulatory Considerations
Digital health technologies used to collect endpoints must meet high evidentiary requirements for validation, with complexity increasing when multiple sensors or complex software are bundled. Regulatory agencies like the FDA and EMA have established pathways for the qualification of drug development tools, including biomarkers and clinical outcome assessments. Integration of new draft guidance on remote health monitoring with existing regulatory workflows is necessary to reduce uncertainty in trial evaluations. While many digital health technologies do not qualify as medical devices unless they have a specific medical purpose, synergies between device risk assessments and drug trial data integrity frameworks should be explored. Early engagement with regulators remains a critical step for obtaining feedback on novel digital endpoints and ensuring the suitability of evidentiary support.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Building the business case for digital endpoints
Building the business case for digital endpoints
Digital endpoints must not only support regulatory approval but also provide evidence that meets payer expectations for reimbursement and value-based care. The lack of early engagement with payers and health technology assessment (HTA) agencies is a key barrier to the adoption of digital clinical measures. Digital measures can enhance value-based care models by capturing patient-centered outcomes, reducing healthcare costs, and improving early disease detection. The scalability and generalizability of digital endpoints remain challenges, particularly for diverse populations and real-world healthcare settings. Technical and systematic barriers—such as data heterogeneity, stakeholder knowledge gaps, and inconsistent regulatory-payer alignment—are slowing the adoption of digital endpoint data for reimbursement decisions.
Recommendations
Pharma and medical product developers should engage early with payers and regulators to ensure digital endpoints align with reimbursement expectations. Payers and HTA bodies should establish clear evidence thresholds for digital endpoint validation, ensuring consistency in market access decisions. Digital endpoints should be validated against health-related quality of life (HRQoL) measures and patient-reported outcomes (PROs) to demonstrate clinical relevance. Real-world evidence (RWE) should be incorporated into clinical trials alongside digital endpoints to strengthen reimbursement applications. Stakeholders should prioritize scalable, patient-centered digital measures that capture disease progression over time and across different care settings.
Regulatory Considerations
Integrated Evidence Plans (IEPs) should be developed early to align digital endpoint evidence with regulatory and payer requirements. Digital endpoints should be assessed through multi-stakeholder collaboration, ensuring validation across pharmaceutical, regulatory, and reimbursement frameworks. Payers and regulators should work together to create aligned pathways for digital measure acceptance, reducing delays in market access. Data security, privacy, and interoperability must be addressed to support regulatory approval and patient trust in digital health solutions. The industry should leverage international regulatory-payer collaboration models, such as the HTA-EMA partnership and the FDA Payor Communication Task Force, to accelerate global digital endpoint adoption.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Collaborative Communities: Addressing Health Care Challenges Together
Collaborative Communities: Addressing Health Care Challenges Together
Collaborative Communities are sustained, multi-stakeholder forums (including patients, industry, academia, and the FDA) dedicated to solving shared challenges in the medical device ecosystem. These communities are not intended to replace formal regulatory mechanisms. They are equipped to perform activities such as:
Developing best practices and strategies.
Generating and evaluating evidence to support novel approaches.
Clarifying ill-defined challenges and generating consensus on definitions.
Addressing issues related to product quality and safety.
Recommendations
The FDA/CDRH does not establish or fund these communities. Instead, the FDA recommends that interested stakeholders convene and lead these groups. The FDA reviews opportunities on a case-by-case basis for participation, considering:
The community's potential public health impact.
Alignment with the CDRH mission, priorities, and resources.
The existence of a formal governance structure, a convener, a plan to measure success, and a mechanism for sustained engagement.
Regulatory Considerations
The FDA's participation in these communities is a strategic priority for advancing regulatory science and fostering responsible medical device innovation. Examples of digital health-related collaborations include those focused on AI/ML, Digital Biomarkers, Digital Health Technologies (DHTs), and Real-World Data (RWD). The outcomes developed by these groups can inform and accelerate the development of science-based solutions to policy and scientific challenges.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Condition-Specific Meeting Reports and Other Information Related to Patients’ Experience
Condition-Specific Meeting Reports and Other Information Related to Patients’ Experience
Patient experience data provides critical context for regulatory review by illuminating disease burden, unmet medical needs, and the aspects of a condition that matter most to patients.
A systematic approach is necessary to ensure patient experience data is robust enough for regulatory consideration, moving beyond anecdotal evidence to scientifically rigorous data collection.
Early engagement between sponsors and the FDA is a key factor for successfully incorporating patient perspectives into a drug development program.
The value of patient-reported outcomes (PROs) and other clinical outcome assessments (COAs) is highly context-dependent, varying significantly across different diseases and patient populations.
Recommendations
Drug sponsors should leverage the FDA's meeting process to discuss their strategies for collecting and submitting patient experience data early in the development lifecycle.
Sponsors should utilize the repository of meeting reports as a learning resource to understand best practices and common challenges in patient-focused drug development for specific conditions.
Patient advocacy groups should actively participate in these discussions to ensure the full spectrum of patient experiences is captured and communicated to both regulators and developers.
Researchers should develop and validate novel tools and methodologies for capturing and analyzing patient experience data that are meaningful for both clinical and regulatory purposes.
Regulatory Considerations
Patient experience data is a key component of the benefit-risk assessment, providing evidence that can inform regulatory decisions regarding a drug's approval and labeling.
The FDA's review of patient experience data is guided by a commitment to patient-focused drug development, as mandated by the 21st Century Cures Act and supported by user fee agreements like PDUFA.
The scientific rigor of data collection and analysis is paramount; for patient experience data to be influential, it must meet high standards of validity and reliability.
Transparency is a core principle, and the publication of these meeting reports is intended to provide clear examples of how patient input can be effectively integrated into regulatory submissions.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Delivering regulatory impact from consortium-based projects
Delivering regulatory impact from consortium-based projects
Findings
Establishing cross-sector consortia does not guarantee success without a unified objective and stakeholder buy-in. A neutral, independent facilitator is a key element for successful governance in many collaborative platforms. Many consortia lack consistent methods for storing critical data, meeting minutes, and regulatory briefing packages, which creates barriers after project completion. Regulatory success depends heavily on the early development of a strategy that defines the necessary evidence to validate innovative methodologies. Successful examples include the qualification of biomarkers for polycystic kidney disease and type 1 diabetes, as well as imaging measures for Alzheimer’s disease.
Recommendations
Consortium members should develop an initial regulatory strategy during the project scoping and planning phases. Teams must explicitly define the context of use for any proposed tool to articulate exactly what decisions the output will inform. A robust data strategy should be implemented early, including formal agreements for data use, standardization, and sharing that remain in place in perpetuity. Consortia must prioritize sustainability plans to ensure data and active databases remain available for research and regulatory use after funding expires. Projects should integrate regulatory science expertise from the start to cover both EU and US frameworks.
Regulatory Considerations
Regulators require individual patient-level data that is fully curated, standardized, and presented through formal submissions like qualification applications. Formal regulatory endorsement ensures a tool can be trusted for consistent interpretation in drug development and marketing authorization evaluations. Early engagement with agencies such as the FDA and EMA is essential to gain feedback on novel methodologies and align study designs with regulatory expectations. Specific pathways like the EMA Qualification of Novel Methodologies and the FDA Qualification Process for Drug Development Tools should be utilized. Regulatory qualification may require ongoing access to databases to support the long-term use of the methodology.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Digital Health Technologies (DHTs) for Drug Development
Digital Health Technologies (DHTs) for Drug Development
The central principle of the FDA's program is that Digital Health Technologies (DHTs) offer significant potential to make clinical trials more efficient, patient-centric, and capable of capturing novel data. A key finding is that a collaborative, multifaceted approach is necessary to address the challenges of incorporating DHT-derived data into regulatory decision-making. The program acknowledges that ensuring data quality, validating new endpoints, and establishing clear regulatory expectations are critical for the successful adoption of these technologies in drug development.
Program Activities (Recommendations)
The FDA's activities in this area function as implicit recommendations for the industry. The agency is actively:
Developing a Framework: Creating and publishing a clear framework to guide the use of DHTs in drug and biological product development.
Engaging Stakeholders: Convening public meetings and workshops to foster collaboration and share learning among patients, biopharmaceutical companies, DHT manufacturers, and academia.
Supporting Demonstration Projects: Funding and overseeing research projects to address critical gaps and demonstrate the reliability and validity of specific digital measures.
Building Internal Expertise: Establishing a DHT Steering Committee and enhancing internal knowledge to ensure consistent and expert review of submissions containing DHT-derived data.
Regulatory Considerations
This webpage emphasizes the FDA's commitment to creating a clear regulatory framework for the use of DHTs in drug development. It highlights that while DHTs offer great promise, they also present new regulatory challenges related to data integrity, validation, and analysis. The FDA's approach involves a combination of issuing new regulatory guidance, promoting stakeholder collaboration, and advancing regulatory science. Sponsors are encouraged to engage with the FDA to discuss their use of DHTs in clinical trials to ensure alignment with the agency's expectations. The establishment of the CDRH Digital Health Center of Excellence provides a dedicated resource for such engagement.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Digital Measures: De-risking Cytokine Release Syndrome (CRS)
Digital Measures: De-risking Cytokine Release Syndrome (CRS)
Cytokine Release Syndrome (CRS) is a common and potentially life-threatening adverse event of immunotherapies, particularly in Oncology, complicating patient care and increasing healthcare costs. Standard-of-care inpatient monitoring for CRS is manual, intermittent, costly, and restrictive, providing an incomplete view of the syndrome’s development and progression. The use of Digital Health Technologies (DHTs) for continuous, remote monitoring of vital signs (like heart rate, respiratory rate, skin temperature, SpO2, and activity) can capture early indicators of CRS up to two hours earlier than standard episodic monitoring. This ability to collect multivariate continuous data is valuable for informing robust model development for CRS risk prediction.
Recommendations
Investigators should deploy DHTs available today to monitor vital signs and symptoms currently observed in the hospital setting, but in an outpatient or home environment. The goal is to develop Early Warning Products that assess the probability of developing CRS, providing clinical decision support. Product developers should follow a strategic roadmap that outlines milestones for building products that are clinically relevant and commercially viable. Researchers should use a common set of digital clinical measures to gather high-quality datasets and ensure comparability across studies to build more robust predictive models. Predictive algorithms should be built on a robust reference measure for analytical validation and be clinically validated with sufficient data.
Regulatory Considerations
The resources are designed to help developers build products that are clinically appropriate, regulatory-acceptable, and commercially viable. Future regulatory submissions for CRS de-risking products will benefit from aligning with this industry-wide dialogue that is being built in collaboration with the FDA. Developing a robust CRS safety biomarker could enhance the safety profile of clinical trials, increase trial access, and streamline regulatory decision-making, possibly through a qualification pathway. Products that aim for a higher level of autonomy, such as a Diagnostic that redefines current CRS grading classes, may require very high clinical evidence and likely stringent regulatory review.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Drug Development Tool (DDT) Qualification Programs
Drug Development Tool (DDT) Qualification Programs
The central principle of the DDT Qualification Programs is to create a formal pathway for the FDA to conclude that a specific tool is well-suited for a particular Context of Use (COU) in drug development. A key finding, as reflected in the program's design, is that qualification de-risks drug development by allowing a tool to be used in any regulatory submission for its qualified COU without needing to be re-validated each time. The program is designed to foster stakeholder collaboration, encouraging the development of tools that can benefit the entire research community, thereby reducing the burden on individual sponsors.
Program Activities (Recommendations)
The structure of the DDT programs serves as a series of recommendations for tool developers:
Engage Early and Collaboratively: The programs are designed to provide a framework for early and ongoing scientific collaboration with the FDA to facilitate the development of new tools.
Follow a Staged Process: Developers are guided through a multi-stage process, typically involving a Letter of Intent, a Qualification Plan, and a Full Qualification Package, to systematically build the evidence needed for qualification.
Seek Public Qualification: The ultimate recommendation is to achieve public qualification for a DDT, which makes the tool available for broad use and integrates it into the regulatory review process, expediting future drug development.
Regulatory Considerations
The DDT Qualification Programs are a formal regulatory framework established under the 21st Century Cures Act. A "qualified" DDT has a specific regulatory status; it can be relied upon to have a specific interpretation and application in drug development and regulatory review for its stated Context of Use (COU). This qualification is publicly available and allows the tool to be included in Investigational New Drug (IND), New Drug Application (NDA), or Biologics License Application (BLA) submissions without the FDA needing to reconsider its suitability. This creates a more efficient and predictable regulatory compliance pathway for sponsors who use the qualified tool.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
List of qualified DDTs
List of qualified DDTs
The database provides a transparent and accessible way for the public to track the progress of various Drug Development Tools (DDTs) through the FDA's qualification pipeline. This includes biomarkers, clinical outcome assessments, and animal models. The information available, such as submission status and supporting documentation, offers insight into the types of tools being developed and the evidence required for their qualification. The platform reveals that a wide range of tools are in development across numerous therapeutic areas, highlighting active areas of research and innovation in drug development.
Recommendations
Stakeholders in the drug development ecosystem are encouraged to utilize this database to inform their research and development strategies. By reviewing the status of existing DDT submissions, sponsors can identify opportunities for collaboration, avoid duplicative efforts, and better understand the evidentiary requirements for tool qualification. Prospective tool developers should use the database to learn from successful submissions and to align their own development plans with FDA expectations.
Regulatory Considerations
This database is a direct implementation of the transparency provisions of the 21st Century Cures Act. The public availability of this information is intended to foster trust and collaboration in the DDT qualification process. By providing a clear view of the regulatory journey of various tools, the FDA aims to standardize the qualification process and encourage the development and use of novel, validated tools in drug development. Users of the database should be aware that the information reflects the status of a DDT at a particular point in time and that the qualification process is an iterative one.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Patient Engagement Synapse: Resource Directory
Patient Engagement Synapse: Resource Directory
Traditional, site-based clinical trials often create significant burdens for participants, which can hinder recruitment, retention, and the enrollment of diverse populations.
A lack of early and sustained patient engagement in trial design can lead to research protocols that are misaligned with patient needs and endpoints that are not meaningful to them.
The underrepresentation of diverse racial, ethnic, and other demographic groups in clinical trials limits the generalizability of study results and can perpetuate health disparities.
Emerging digital health technologies (DHTs) and real-world data (RWD) present significant opportunities to make clinical trials more efficient, patient-centric, and inclusive, but their adoption has been inconsistent.
Recommendations
Sponsors and research teams should engage patients and patient advocacy groups as active partners throughout the entire clinical trial lifecycle, from design to dissemination.
Decentralized clinical trial (DCT) elements should be incorporated to reduce patient burden, improve access for diverse populations, and enhance the quality of data collection.
Trial sponsors must develop and implement proactive strategies to enhance the diversity and inclusion of trial participants to ensure results are applicable to all patient populations.
Novel endpoints derived from DHTs should be developed and validated to capture more objective, real-world measures of how patients feel, function, and survive.
Multi-stakeholder collaboration between industry, academia, patient groups, and regulators is essential to address systemic challenges and improve the clinical trial enterprise.
Regulatory Considerations
Early and frequent communication with regulators, such as the FDA, is critical when implementing novel approaches like DCTs or developing new digital endpoints for pivotal trials.
Regulatory frameworks must support the use of innovative technologies and trial models while ensuring data integrity, reliability, and patient safety.
The use of a single Institutional Review Board (IRB) for multi-site trials is a key regulatory-supported mechanism for streamlining ethics review and increasing trial efficiency.
When using DHTs and decentralized methods, robust plans for data quality, privacy, and security are necessary to meet regulatory standards for trial data submission.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.