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.

Regulatory Considerations
The Premarket Notification (510(k)) database is a critical component of the FDA's regulatory framework for medical devices. Its primary function is to house information on devices that have been cleared through the 510(k) pathway, which is the most common route to market for medical devices in the U.S.

A 510(k) submission's central requirement is to demonstrate "substantial equivalence" to a legally marketed predicate device. This means the new device is as safe and effective as a device already on the market. Clearance of a 510(k) does not denote "approval" in the same way as a Premarket Approval (PMA) application but rather confirms that the device meets the necessary criteria for marketing.

The database provides transparency and serves as an essential resource for manufacturers to identify potential predicate devices for their own submissions. For healthcare providers, patients, and researchers, it offers a way to verify the regulatory status and clearance basis for a specific device.

Findings
The quality of evidence for the analytical validation of sensor-based digital health technologies (sDHTs), which is the evaluation of algorithms converting sensor data into a clinically interpretable measure, is often inconsistent and insufficient. The existing V3+ framework codifies the overall evaluation process, which includes verification, usability validation, analytical validation, and clinical validation. To improve the scientific rigor of analytical validation, a hierarchical framework for selecting reference measures is needed because not all potential reference measures are of equal quality. The framework classifies reference measures based on attributes that contribute to reduced measurement variability, with defining and principal measures being the most rigorous due to objective data acquisition and the ability to retain source data.

Recommendations
The proposed framework sequentially moves the investigator through four steps: (1) Compile preliminary information, including the digital clinical measure, context of use (COU), algorithm requirements, and sensor verification evidence . (2) Select an existing reference measure, develop a novel comparator, or identify a set of anchor measures, prioritizing measures with the highest scientific rigor (defining → principal → manual → reported) . (3) Consider the impact of the data collection environment to determine if the analytical validation study can be conducted in the intended use environment with the highest-order measure, or if in-lab validation is necessary, ensuring the results are generalizable . (4) Describe the rationale for key study design decisions to encourage transparency for evaluators, regulators, and payers . Investigators must justify passing over a higher-ranked reference measure, generally only acceptable if the higher-ranked measure poses unacceptable risk or is not applicable to the context of use.

Regulatory Considerations
The principles of the framework for analytical validation apply regardless of the regulatory status of the sDHT (regulated medical device, low-risk general wellness apps, or research product) or its intended use (clinical care or clinical research). The framework is intended to help investigators support the most rigorous claims regarding sDHT performance, which is important for acceptance by evaluators, peer-reviewers, regulators, and payers. The categorization of the digital clinical measure as a digital biomarker or an electronic clinical outcome assessment also does not change the framework's applicability.

Findings
Existing guidelines lack pragmatic application and systematic approach for device selection.
Device choice is dependent on measurement objectives, user population, and available resources.
Current frameworks do not systematically consider verification, validation, feasibility, and protocol design.
Rapid obsolescence of digital devices due to technological advancements.
Need to incorporate social/psychological factors into device selection.

Recommendations
Develop a practical guide with a systematic approach for selecting wearable devices.
Use five core criteria: continuous monitoring capability, device suitability and availability, technical performance, feasibility of use, and cost evaluation.
Prioritize feasibility of use to ensure user needs are incorporated into the selection process.
Adapt guide criteria to accommodate novel innovations.
Foster clarity and transparency in decision-making among researchers, HCPs, and device users.

Regulatory Considerations
Follow FDA guidance for digital health technology usage in clinical investigations.
Consider CTTI recommendations for improving clinical trial quality and efficiency.
Use ePRO Consortium's factors for device suitability in regulatory trials.
Apply international guidelines for specific measurements when available.

Findings
A proactive risk assessment is essential for optimizing study quality by identifying and mitigating risks to human subject protection and data integrity before and during a trial. Monitoring should be comprehensive, addressing not only likely risks identified initially but also less probable, high-impact risks and unanticipated issues that emerge. The effectiveness of a monitoring strategy depends on tailoring its timing, frequency, and methods to study-specific factors like complexity and site experience. Centralized monitoring, as part of a risk-based approach, can detect systemic issues like data omissions or protocol deviations more rapidly than traditional on-site visits alone.

Recommendations
Sponsors should formally document their risk assessment methodologies and ensure these assessments directly inform the creation and revision of monitoring plans. Monitoring plans must be detailed, outlining the study design, specific data sampling strategies, and clear protocols for escalating significant issues. When significant problems are identified, sponsors must conduct a timely root cause analysis and implement corrective and preventive actions. All monitoring activities, findings, and subsequent actions should be thoroughly documented and communicated to sponsor management, clinical site staff, and other relevant parties.

Regulatory Considerations
FDA regulations mandate sponsor oversight and proper monitoring but do not prescribe specific methods, providing the flexibility for sponsors to adopt a risk-based approach. The FDA may request a sponsor's risk assessment and monitoring plan documentation during an inspection. This guidance represents the Agency's current thinking and is nonbinding, allowing sponsors to use alternative approaches if they satisfy regulatory requirements. A key focus of monitoring should be to ensure critical trial processes, such as the maintenance of blinding, are protected to maintain overall data and trial integrity.

Findings
Lack of consensus on the type and scope of digital outcome measures.
Partial integration of mobile health technologies into clinical practice.
Challenges in data presentation and interpretation.
Poorly addressed patient compliance and technology illiteracy.
Validation challenges for mobile health technologies.

Recommendations
Target deficits confirmed to be relevant to patients.
Use a combination of devices with an acceptable benefit-to-burden ratio.
Integrate data into patient management platform standards.
Ensure regulatory approval and adoption by healthcare organizations.
Consider pilot use of competing platforms for better integration.

Regulatory Considerations
Understand and overcome regulatory hurdles.
Ensure sustainable financial models.
Consider pilot use of platforms for regulatory integration.

Findings
Lack of widely accepted tools for digital mobility assessment.
Challenges in technical and clinical validation due to multiple expertise requirements.
Inconsistent testing procedures and variations in norms.
Limitations of current mobility measurement methods.
Need for real-world mobility assessment.

Recommendations
Adopt best practices and innovate with standards and open access tools.
Ensure transparency through regular interaction with stakeholders.
Develop algorithms in an agnostic and fully documented manner.
Make data accessible through a digital data biobank.
Aim for regulatory approval with accurate real-world mobility measurement.

Regulatory Considerations:
Engage in early dialogue with regulatory authorities.
Understand different regulatory requirements based on context of use.
Focus on qualification of new methodologies for safety and efficacy.
Use DMOs to monitor disease progression and as surrogates for secondary endpoints.
Adopt a staged approach to regulatory qualification.

Findings
Patient technologies were used across 55 countries, with mobile applications (53%) and wearable devices (33%) being the most common technologies.
Common data issues included data transmission failures, duplicate or missing data, and integration challenges with other datasets.
Factors like technical literacy, device usability, and preferences for paper-based alternatives affected adoption rates, particularly in elderly populations.
Varying broadband connectivity, importation hurdles, and compliance with regulations like GDPR posed significant challenges.
Most sponsors (54%) were willing to reuse technologies, citing improved retention, compliance, and remote monitoring capabilities as key benefits.

Recommendations
Consider patient demographics, such as age and technical literacy, when selecting and implementing technologies.
Offer multi-format training for sites, patients, and monitors, and provide robust support systems to address technical and compliance issues.
Risk Mitigation: Anticipate potential issues like data loss, non-compliance, and technical failures by incorporating backup processes into protocols.
Conduct feasibility assessments for site infrastructure and regulatory compliance in target regions to minimize delays.
Regularly gather experiential feedback from patients to refine technologies and improve future trial designs.

Regulatory Considerations
Seek advice from regulators to ensure patient technologies align with clinical trial protocols and data submission requirements.
Ensure Compliance with GDPR and Local Regulations: Address privacy concerns and adapt technologies to meet country-specific requirements.
Prepare Documentation for Importation: Account for additional time and costs related to import licenses and customs requirements.
Plan for the impact of technical updates on clinical data reliability and regulatory submissions.

Findings
The review includes 275 studies, with neurology, musculoskeletal disorders, and cardiology as the most common therapeutic areas.
The studies focused on sensor performance (48%), algorithm development (86%), operational feasibility (46%), and software development (9%).
Gaps in reporting included insufficient details on software used (27%), comparator measures (17%), and participant demographics (e.g., age and gender were missing in 9% and 15% of studies, respectively).
Sixty-seven percent of the studies used wearable sensors, while others incorporated smartphones, tablets, cameras, and implantable devices.
The lack of methodological and reporting standards across studies hinders reproducibility and broader applicability.

Recommendations
Develop methodological and reporting standards to improve consistency across feasibility studies.
Include comprehensive participant demographic data, including sociodemographics and health indicators, to ensure inclusivity and generalizability.
Conduct small feasibility studies to validate sensors, optimize algorithms, and identify operational challenges before launching full-scale trials. Use the database created from this review to inform trial design and technology selection, ensuring alignment with specific research goals.
Encourage collaboration among investigators, sponsors, and regulators to standardize methods and share insights to avoid redundant studies.

Regulatory Considerations
Align sensor verification and algorithm validation processes with regulatory requirements for reliable clinical endpoints.
Ensure secure and ethical data transfer, storage, and sharing practices for compliance with privacy regulations.
Address barriers to participation for underrepresented populations by assessing and reporting equity-related data during feasibility studies.

Findings
Organizational challenges such as risk-averse corporate culture and lack of strategy hinder PT adoption.
Business-related challenges include unclear ROI and limited willingness to invest.
External challenges involve regulatory implications and technology landscape issues.
Internal disconnections within companies lead to inefficiencies in PT initiatives.

Recommendations
Improve understanding and communication between all clinical trial stakeholders.
Engage with sites and patients to inform trial design.
Address internal disconnections within companies to facilitate PT adoption.
Develop a clear business case for PT to encourage investment.
Enhance training and support for technology use in clinical trials.

Regulatory Considerations
Lack of specific guidance for PT use in clinical trials.
Geographic variability in regulations and interpretations.
Privacy and security concerns related to data management.

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
Widespread use of mobile technologies in clinical trials is impeded by perceived challenges.
Scientific and technical challenges affect decision-making around using mobile technology for data capture.
Concerns include choosing appropriate technology, data collection and analysis, ensuring data authenticity, and designing protocols.

Recommendations
Use CTTI's framework for mobile technology selection to assist sponsors.
Conduct feasibility studies prior to launching trials.
Engage with regulatory authorities early to discuss endpoint appropriateness and validation processes.
Secure data generated by mobile technologies using recommended practical approaches.
Optimize data quality to minimize variability and ensure robust conclusions.

Regulatory Considerations
Engage with the FDA early in the trial design process.
Ensure data integrity and security throughout the data life cycle.
Maintain open dialogue with regulatory authorities regarding trial-specific strategies for data collection and sharing.