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 Integration of new draft guidance on remote health monitoring with existing regulatory workflows is necessary to reduce uncertainty in trial evaluations.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.

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
Challenges in patient adherence and acceptability of digital endpoints.
Issues with algorithm validation and use in diverse populations.
Barriers due to proprietary software and lack of transparency.
Vast heterogeneity in digital endpoints and lack of standards.
Need for ongoing ethical support and consideration of environmental impact.

Recommendations
Foster multi-stakeholder cooperation and open-forum discussions.
Integrate patient needs into the design of digital health technologies.
Include implementation science expertise in research proposals.
Develop standards for selecting and reporting digital endpoints.
Provide ongoing ethical support throughout the research lifecycle.

Regulatory Considerations
Early engagement with regulators is crucial.
Understanding regulatory requirements for clinical trials versus clinical care.
Need for harmonised terminology and guidelines for digital endpoints.

Findings
Misclassification of wakefulness during sleep periods and issues with tracking outside main sleep bouts.
Bias in performance evaluation studies due to limited representation of diverse populations.
Hidden complexities in consumer-grade devices related to data access, fees, privacy, and security.

Recommendations
Carefully interpret study results based on wearable sleep-tracking technology data.
Address biases in study populations by including diverse cohorts.
Ensure proper preprocessing of data from consumer-grade devices.
Avoid inserting personally identifiable information in device settings.
Evaluate issues related to specific populations like minors.

Regulatory Considerations
Complexity of privacy laws across different countries.
Need for strategies to protect personal information in device settings.
Consideration of specific population issues, such as minors, in regulatory frameworks.

Findings
The DTRA Best Practice Evaluation Rubric uses five dimensions to determine if a DCT practice should be considered a "best practice":
Evidence of Success: Requires measurable and demonstrable success using KPIs and tangible outcomes.
Improving Patient Experience: Must address the needs of patients, caregivers, and therapeutic experts, demonstrating improved experience and engagement.
Site Impact: Must consider the implications of adoption and the practical impact on site burden and working practices.
Operational and Technical Feasibility: Ensures operational and technical aspects (including ongoing support, security, integrity, scaling, and reuse) have been fully considered when deploying new technologies.
Regulatory & Ethical Compliance: Requires appropriate consideration of global and local regulations and guidance (e.g., ICH E6/E8, GDPR, HIPAA), including adherence to privacy, consent, and ethical safeguards.

Recommendations
A practice should demonstrate several key factors across the dimensions:
Patient-Centricity: Reduce patient burden by offering the option to reduce physical visits and enable greater patient empowerment and access to information. It should strive to increase the diversity of recruited patients while mitigating bias toward technologically literate patients.
Site Support: Achieve a net reduction in burden for sites, utilizing simple, intuitive technology with minimal, on-demand training. It must provide clarity of fiduciary responsibility and use technology to increase risk-based monitoring without sacrificing data integrity.
Technical Rigor: Have a clear problem statement and a thoroughly defined strategy to mitigate operational and technical risks. It should take a holistic approach and ensure the solution is fit for use for the specific patient population, aligning with data privacy and security standards.

Regulatory Considerations
Practices must ensure compliance with both global and local regulations and Health Authority guidance. Explicit attention must be given to aligning with ICH E6 (Good Clinical Practice) and privacy laws like GDPR and HIPAA. The design must protect stakeholders providing sensitive or personal data with safeguards to ensure ethical safety.

Findings
FDA requires OUS clinical investigations to comply with GCP, ensuring the credibility and accuracy of data and protecting human subjects.
Statements on GCP compliance and supporting information are mandatory for OUS data submissions.
Waivers are permitted in circumstances where GCP compliance is unattainable or where local regulations differ significantly from FDA requirements.
Investigations must demonstrate that OUS data are applicable to U.S. populations and medical practices.
Sponsors must provide robust documentation, including investigator qualifications, site descriptions, IEC reviews, and informed consent processes.

Recommendations
Ensure clinical investigations adhere to GCP standards, including IEC review and informed consent, for all OUS clinical data submitted to FDA.
Include detailed supporting information in submissions, such as investigator qualifications, facility descriptions, protocols, and data summaries.
Clearly identify any deviations from GCP and justify how data integrity and subject protection were maintained.
Use FDA’s Pre-Submission Program to discuss potential challenges with GCP compliance or data validation before submission.
Retain all required records for at least two years after FDA’s decision on the application or submission.

Regulatory Considerations
FDA evaluates OUS clinical data on a case-by-case basis, considering the adequacy of GCP compliance and supporting documentation.
For significant risk device investigations, sponsors must provide the most comprehensive documentation, while non-significant risk and exempt devices require less detailed information.
Waivers may be granted when justified by public health considerations or when local laws prohibit compliance with specific FDA requirements.
FDA retains the right to inspect clinical sites or review source documents to validate data integrity and compliance with GCP.
Sponsors must ensure that OUS data are valid and relevant to the U.S. population and medical practice.

Findings
Challenges related to data safety, quality, privacy, and regulatory requirements in smart sensor technologies.
Bias in standard RCTs due to exclusion of participants with language or motor barriers.
Need for ICT systems to detect smooth transitions in cognitive abilities and everyday functions.

Recommendations
Develop ICT-based procedures that capture relevant clinical features validly.
Ensure data fidelity and robustness in ICT systems.
Incorporate user needs into ICT solutions.
Address data safety and privacy concerns.
Develop international policies for access, security, and privacy in ICT solutions.

Regulatory Considerations
Need for international efforts to address gaps in policies around access, security, and privacy.
Current laws do not cover health information on mobile apps or the Internet.
Lack of regulation could undermine the credibility of RWE results.

Findings
The FDA's increasing commitment to patient-focused drug development (PFDD) and patient engagement in translational research presents a significant opportunity to improve the clinical trials enterprise and enhance participation by patient groups . Patient groups can play important roles in improving the entire therapeutic development enterprise, from study endpoint selection that reflects outcomes meaningful to patients, to recruitment and retention in clinical trials, and more effective postmarketing safety . However, there is a lack of clarity about how, when, and by whom patients or patient groups should be engaged during the therapy development process, and which patients or patient groups should be engaged . Metrics by which the value of such engagement, in terms of regulatory and market success, might be measured are also lacking .

Recommendations
PFDD and patient engagement in research should be considered an effort to extend the benefits of incorporating patient insight and experiences, as well as desires and preferences, from bench to bedside and back . The therapeutic development process should meaningfully engage patients throughout, though specific guidance on implementation methods is needed .

Regulatory Considerations
The paper does not provide specific regulatory considerations or recommendations. The focus remains on identifying the opportunity and gaps in current patient engagement approaches rather than detailing regulatory pathways or compliance requirements.

Findings
Emphasizes the importance of DMCs in enhancing trial participant safety.
Highlights the need for DMC independence to prevent bias.
Discusses the historical context and evolution of DMCs in clinical trials.
Notes that not all trials require a formal DMC.

Recommendations
Sponsors should consider establishing a DMC for trials with significant safety concerns.
Ensure DMC independence from sponsors to maintain objectivity.
Limit DMC use to trials where they are most beneficial due to added complexity.
Clearly define roles and responsibilities of all parties involved in trial monitoring.
Develop procedures to assess and manage potential conflicts of interest for DMC members.

Regulatory Considerations
Compliance with FDA regulations on adverse event reporting under 21 CFR 312.32 and 812.150.
Adherence to confidentiality protocols for unblinded data as per 21 CFR 314.126(b)(5).
Use of DMC recommendations to inform protocol changes while minimizing potential bias.
Maintenance of detailed records for DMC meetings and interim analyses for regulatory audits.
Engagement with FDA on early termination of trials or significant protocol changes due to safety concerns.