Findings
The most promising aspects of mental health for digital measurement are sleep, physical activity, stress, and social behavior, which have the strongest scientific evidence. Core barriers to adoption include high cost and limited access, data privacy concerns, poor technological literacy, and a lack of technology adaptation for specific mental health needs. Essential technology characteristics for "fit-for-purpose" sDHTs include usability, reliable performance, strong data privacy and security, and long battery life.

Recommendations
Research and development should prioritize moving promising measures (sleep, activity, stress, social behavior) to large-scale clinical trials. Algorithms must be refined and clinically validated for mental health indications, and new sensor modalities should be explored. Infrastructure must be developed by creating standards and ontologies for mental health sensor data to ensure interoperability and scalability. To improve access and equity, financial support mechanisms and inclusive, culturally tailored design are critical.

Regulatory Considerations
The report does not provide a separate section for "Regulatory Considerations" but emphasizes that future development and funding should prioritize clinical validation across diverse populations. It notes the importance of a clear understanding of the intended measurement claims and the need for rigorous validation studies to move beyond pilot and feasibility stages to demonstrate real-world clinical utility.

Findings
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.

Findings
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.

Findings
Diverse Pathways to Market Exist: The case studies demonstrate there is no single "right" way to approach the FDA; successful strategies are highly varied and include De Novo requests, 510(k) clearances, and leveraging established pathways for new indications.
Early FDA Engagement is Crucial: A consistent theme across the successful case studies is the value of engaging with the FDA early and often. This collaborative approach helps de-risk the development process, clarify evidentiary requirements, and build trust.
"Drug-like" Evidence Can Be a Differentiator: For novel software-based interventions, particularly digital therapeutics, generating a robust body of evidence similar to that of a pharmaceutical (i.e., randomized controlled trials) is a key strategy for gaining regulatory and commercial success.
Platform-Based Approaches are Emerging: Companies are finding success by moving from single-product solutions to integrated platforms that can monitor multiple health aspects, which requires a more holistic regulatory strategy.

Recommendations
Leverage Pre-Submission (Pre-Sub) Meetings: Sponsors are strongly encouraged to use the Q-Submission program to gain valuable, early feedback from the FDA on their validation plans and overall regulatory strategy.
Build a Multi-faceted Commercialization Plan: Regulatory clearance is only one step. The case studies recommend developing a comprehensive strategy that considers market access, reimbursement, and payer engagement from the outset.
Address Underserved Markets: The examples highlight opportunities for innovation in underserved areas, such as pediatrics and behavioral health, where DHTs can fill significant gaps in care.
Innovate on Evidence Generation: Sponsors should be prepared to innovate not just in their technology, but also in their approach to clinical evidence, tailoring their trial designs to best demonstrate the unique value of their digital product.

Regulatory Considerations
Understand the Risk Classification: The regulatory pathway for a DHT is determined by its intended use and associated risk level. Sponsors must correctly classify their device to determine if a 510(k), De Novo, or other pathway is appropriate.
AI/ML Devices Have Unique Needs: For products incorporating artificial intelligence or machine learning, sponsors must address specific regulatory considerations, such as predetermined change control plans (PCCPs), to manage algorithm updates post-market.
Interoperability is a Key Factor: For devices intended to be part of a connected health ecosystem (e.g., automated insulin dosing systems), demonstrating interoperability and cybersecurity is a critical component of the regulatory submission.

Findings
Regulatory inconsistencies across different FDA divisions and international jurisdictions create inefficiencies in the approval process for digital health products.
Lack of alignment between regulatory approval and payer reimbursement requirements poses a significant barrier to commercialization and widespread adoption of digital health innovations.
There are limited regulatory pathways for novel digital health products, including AI-enabled solutions, requiring new frameworks to address iterative software development and real-world data integration.
Existing health technology assessment (HTA) models do not fully accommodate digital health technologies, limiting their inclusion in reimbursement decisions.
Industry stakeholders emphasize the need for clearer guidelines on cloud-based infrastructure, third-party AI model validation, and digital health interoperability.

Recommendations
FDA and international regulatory bodies should improve coordination to establish standardized approval processes and consistent clinical evidence requirements.
New regulatory pathways should be introduced for AI-driven and software-based digital health products, considering their unique lifecycle and iterative development models.
Greater transparency and communication between FDA divisions should be established to ensure consistent decision-making and regulatory interpretations across centers.
Policymakers should prioritize payer alignment strategies, incorporating real-world evidence (RWE) to streamline reimbursement and market access processes.
The digital health industry should collaborate with regulators to create standardized best practices for AI validation, cloud security, and digital biomarker evaluation.

Regulatory Considerations
FDA should clarify the evidentiary standards for AI-enabled medical devices and establish predefined change control plans for software updates.
Digital health products should adhere to globally recognized standards such as HL7 for interoperability and ISO regulations for data security.
Market access pathways must integrate pricing and reimbursement considerations to facilitate the commercial viability of digital health technologies.
The use of real-world data (RWD) should be expanded in regulatory decision-making, supporting the approval and post-market surveillance of digital health innovations.
Regulatory frameworks should be updated to accommodate cloud-based health platforms, addressing issues such as data privacy, operational security, and compliance with HIPAA and GDPR.

Findings
Regulatory inconsistencies across FDA divisions create uncertainty and inefficiencies in the approval process for digital health products.
Misalignment between FDA regulatory requirements and payer expectations hinders the commercialization and adoption of digital health innovations.
The absence of clear alternative regulatory pathways for novel digital health products discourages investment and innovation.
The lack of standardized regulatory frameworks for AI-driven healthcare technologies, including large language models (LLMs), poses challenges for industry adoption.
Limited international harmonization in digital health regulation makes it difficult for companies to scale innovations globally.

Recommendations
FDA should improve communication and coordination across divisions to ensure consistent regulatory interpretations and processes.
Regulatory pathways for novel digital health products should be modernized, including the introduction of alternative approval mechanisms tailored to iterative software development and AI-enabled devices.
A regulatory framework for third-party large language models (LLMs) should be developed to support their integration into digital health applications.
Greater alignment between FDA and payer decision-makers is needed to streamline market access and ensure reimbursement for digital health products.
International regulatory harmonization efforts should be expanded to facilitate global adoption of digital health technologies.

Regulatory Considerations
The FDA should clarify and refine regulatory requirements for AI-driven digital health products, including predefined change control plans for software updates.
Cloud-based health platforms require clear regulatory guidance on security, data ownership, and compliance with HIPAA and international privacy laws.
Real-world evidence (RWE) should be incorporated into regulatory decision-making to facilitate faster approvals and post-market surveillance of digital health products.
Standardized regulatory frameworks for digital biomarkers and digital drug development tools (DDDTs) should be developed to support clinical research applications.
Policymakers should collaborate with industry stakeholders to establish education and training programs on digital health innovation and regulatory science.

Findings
There is widespread confusion among digital health developers regarding the complex and evolving regulatory landscape, with many uncertain about whether their products require regulation or which pathway to pursue. This lack of a clear regulatory strategy acts as a significant barrier to market access, investor confidence, and user trust. The heterogeneity of the digital health sector, coupled with varying international requirements, further complicates the path to market for innovators, hindering the scalability of effective solutions.

Recommendations
Digital health innovators should proactively integrate a tailored regulatory strategy into their core business plan, viewing it as a commercial differentiator rather than a hurdle. Developers are encouraged to utilize resources like DiMe’s regulatory pathway tools to navigate the U.S. and global landscapes effectively. Early and continuous engagement with regulators and collaborative efforts across the industry are essential to ensure products are developed to meet both market needs and regulatory standards, ultimately accelerating the delivery of high-quality digital health solutions to patients.

Regulatory Considerations
A comprehensive policy framework is necessary for the successful integration of digital health technologies, encompassing regulatory authorization, value assessment, and reimbursement. Developers must understand the nuances of different regulatory classifications, such as Software as a Medical Device (SaMD), and their specific evidentiary requirements. Greater international harmonization of regulatory standards is crucial for enabling global scalability. Regulatory bodies should continue to develop agile frameworks that can accommodate the rapid pace of innovation in digital health while ensuring patient safety and product effectiveness.

Findings
Traditional RCTs face high costs, long timelines, recruitment challenges, and lack of diversity.
Recruitment efficiency in stroke trials has decreased over the past 25 years.
Digital tools for stroke prevention often lack quality and interactive functionality.
Decentralized RCTs present challenges in data quality and require validation.
Regulatory and compliance requirements vary significantly across regions.

Recommendations
Adopt decentralized RCTs with a patient-centric approach.
Leverage digital technologies to improve trial efficiency and participant experience.
Ensure participant engagement and education in trial design.
Provide high-quality training and support for decentralized procedures.

Regulatory Considerations
Collaborate with regulatory agencies early in trial design.
Compliance with varying international standards is necessary.
Rapid evolution of technology outpaces regulatory changes.
Cross-border data standards and privacy rules must be observed.

Findings
The use of Intended Use and Indication for Use is crucial for digital health products to ensure the product is used appropriately and effectively to meet the needs of the intended population. This information helps establish clear expectations for a product's performance and safety, facilitates regulatory approval, and ensures compliance. The Intended Use provides a general description of the digital health product's purpose or function. The Indication for Use describes the disease or condition the device will diagnose, treat, prevent, cure, or mitigate, including a description of the patient population. A change in a product's indication for use from general to specific usually results in a narrower indication concerning function, target population, or disease entity. Levels of specificity for diagnostic and therapeutic products can be categorized, ranging from the identification of a physical parameter (most general) to the identification of an effect on the clinical outcome (most specific).

Recommendations
The Intended Use statement should include the name of the product, the medical purpose, and what it is trying to do for the user. The Indication for Use statement should include the name of the product, the specific condition or disease state it is addressing, the patient population being targeted, what the product features do, whether other technology components are used with the product, and whether it is for "prescription" or "over-the-counter" use. Developers should characterize the users (e.g., by age, knowledge, or language) and describe the usage context (e.g., hospital ward, emergency room, web-based app). The Indication for Use statement should clearly state the product's clinical capabilities and what it is not intended for (e.g., not intended to provide a diagnosis or replace traditional methods).

Regulatory Considerations
The information provided in the Intended Use and Indication for Use statements is used to inform the product's design and development, as well as to guide regulatory decisions about its approval and marketing. Defining these statements facilitates the regulatory approval process and helps ensure compliance with relevant regulations and standards. The FDA defines the levels of specificity as a qualitative ranking of the proposed indications for use. The document provides examples of FDA's "Indications for Use" from submissions, such as the use of an Atrial Fibrillation History Feature, illustrating the necessary detail for regulatory submissions like a 510(k).

Findings
1. Challenges related to patient privacy and lack of sufficient validation for digital endpoints.
2. Lack of transparency in endpoint calculations and operational challenges.
3. Added complexities due to software version changes and regulatory unknowns.

Recommendations
1. Increase patient-centricity and reduce patient burden through digital health technologies.
2. Foster collaboration among pharmaceutical companies, regulators, academia, and technology companies.
3. Embrace innovation and ensure senior leadership support for digital health initiatives.
4. Utilize real-time data access to enrich clinical trial data sets.
5. Implement outpatient sampling to augment decision-making processes.

Regulatory Considerations
1. Request feedback from regulatory agencies as part of the development plan for outpatient sampling.
2. Consider the FDA's guidance on bioanalytical method validation for dried blood sampling.
3. Note examples of regulatory acceptance of digital biomarkers as primary or secondary endpoints.

Findings
The COVID-19 pandemic has highlighted the need for decentralized clinical trials (DCTs) due to the closure of traditional trial sites.
There is a lack of a national electronic medical system, which poses a challenge for digital risk minimization.
The current regulatory framework is not fully equipped to handle the rapid advancements in digital health technologies.

Recommendations
Increase the adoption and integration of decentralized clinical trials (DCTs) to ensure continuity of research during disruptions.
Develop a national electronic medical system to support digital health initiatives and improve data integration.
Enhance collaboration between regulatory bodies and technology developers to create flexible and adaptive regulatory frameworks.
Encourage the use of real-world data and digital endpoints in clinical trials to improve efficiency and relevance.
Promote patient engagement and input in the development and implementation of digital health technologies.

Regulatory Considerations
The need for standardization and integration of digital health technologies across different platforms and systems.
The importance of developing regulatory guidelines that can adapt to the rapid pace of technological advancements.
The necessity for collaboration between regulatory bodies and standards development organizations to ensure effective oversight of digital health technologies.