Industry spotlight

Findings
Usability gaps in sDHTs remain a barrier to adoption, with many technologies failing to prioritize ease of use, accessibility, and diverse user needs​
Human-centered design is critical for ensuring that digital health solutions are intuitive, functional, and scalable across different healthcare environments​
Standardized usability metrics for evaluating digital health technologies are lacking, leading to inconsistent reporting and validation of usability outcomes​
Use-related risk analysis is essential to identifying and mitigating risks associated with user errors, ensuring the safety and effectiveness of sDHTs​
The V3+ framework provides a structured approach to integrating usability validation into digital health technology development, aligning with global regulatory expectations​

Recommendations
Developers should incorporate human-centered design principles from the outset, ensuring that usability, accessibility, and user needs are central to sDHT development​
Usability validation should be standardized, with clear methodologies for measuring usability, including satisfaction, ease of use, efficiency, and error mitigation​
Regulatory and clinical stakeholders should collaborate on defining best practices for usability evaluation, ensuring that digital endpoints are both meaningful and scalable​
Risk analysis should be iterative, with developers continuously refining their technologies based on real-world user feedback and testing​
The usability validation component of V3+ should be widely adopted to ensure that digital clinical measures meet patient-centered, regulatory, and technical expectations​

Regulatory Considerations
Regulators are emphasizing the need for usability validation to ensure that digital endpoints are both clinically relevant and patient-friendly​
sDHTs must comply with human factors engineering guidelines, aligning with global regulatory frameworks such as ISO 9241-210 and FDA usability requirements​
Data security, privacy, and interoperability must be ensured, particularly as sDHTs become integrated into remote monitoring and decentralized clinical trials​
Real-world evidence (RWE) should support usability validation, helping to bridge the gap between regulatory approval and real-world adoption​
Regulatory bodies should work toward standardizing usability testing methodologies, ensuring consistency across clinical research, digital endpoints, and medical device evaluations​

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Findings
The lack of standardization in vendor onboarding processes increases operational inefficiencies for sponsors and vendors.
Essential topics such as data security, quality management systems (QMS), and validation studies are under-addressed in ad hoc vendor assessments.
Cybersecurity and patient data privacy, especially compliance with GDPR, HIPAA, and global regulations, require enhanced focus during vendor evaluations.
Tailoring vendor assessments to specific trial requirements and patient populations is critical for effective implementation of digital health tools.
Greater collaboration between sponsors and vendors can improve operational alignment and mitigate risks during trials.

Recommendations
Utilize the 13 vendor assessment categories as a baseline for customizing questionnaires to meet specific project needs.
Establish standardized templates for evaluating data privacy, regulatory compliance, and patient-facing user experience.
Prioritize cybersecurity measures, including penetration testing, access management, and encryption standards, as a core assessment criterion.
Implement continuous feedback loops during vendor selection and onboarding to refine assessment processes and address emerging risks.
Encourage industry collaboration to evolve and expand the open-source framework based on practical implementation experiences.

Regulatory Considerations
Ensure all vendors adhere to relevant global standards, including 21 CFR Part 11, GDPR, and HIPAA, for data security and compliance.
Verify the regulatory status of medical devices and algorithms used in digital health solutions, including certifications such as ISO 13485 and IEC 62304.
Require documentation of informed consent processes and adherence to regional data protection regulations for patient data handling.
Align vendor capabilities with regulatory guidelines for clinical trial endpoints, emphasizing validation studies and clinical relevance.
Maintain transparent and audit-ready documentation for inspections and compliance verifications.

Findings
The selection of DHTs must align with the specific goals of the trial, focusing on unmet patient or scientific needs.
A specification-driven approach, rather than solely relying on a technology’s regulatory status, ensures alignment with trial requirements.
Verification and validation are distinct processes; both are critical to confirm the reliability and clinical relevance of DHTs.
Pre-trial feasibility studies help identify potential issues, such as wear-time compliance or usability concerns, before full implementation.
DHTs can alter participant interactions and trial workflows, necessitating clear communication, training, and management plans.

Recommendations
Define Measurement Goals Before Selection: Ensure that the decision to use a DHT is based on unmet needs or the promise of reducing trial burdens.
Adopt a Specification-Driven Selection Process: Tailor DHT selection to technical performance, participant needs, and study-specific requirements.
Verify and Validate Technologies Thoroughly: Collaborate with manufacturers to ensure DHTs are tested in both controlled and real-world settings and validated for the target population.
Conduct Feasibility Studies: Test DHTs for tolerability, usability, and compliance within the specific trial context to identify and address issues early.
Prepare for Operational Challenges: Develop a robust management plan with standard operating procedures (SOPs) to address potential failures and ensure smooth implementation.

Regulatory Considerations
The regulatory status of a DHT should not solely drive its selection; instead, focus on its ability to meet trial specifications.
Ensure transparent collaboration with manufacturers to document DHT performance characteristics and limitations.
Validate endpoints and DHT data to align with evidentiary standards for regulatory submissions.
Use feasibility studies and SOPs to ensure that DHTs comply with regulatory and operational requirements during trials.

Findings
Key considerations include accuracy, precision, sampling frequency, resolution, and data processing. Metadata and communication protocols must ensure reliable and secure data collection.
Sponsors must assess data access, security, and compliance with regulations like 21 CFR Part 11. Clarity on manufacturer and sponsor responsibilities is essential for maintaining data integrity.
Safety risks should be minimized, especially for vulnerable populations. Specifications should ensure that devices pose minimal risks when used solely for data capture.
Human Factors: Acceptability, tolerability, and usability directly impact participant recruitment and adherence. Feasibility studies can help evaluate these factors in target populations.
Operational Considerations: Firmware updates, failure rates, battery life, and customer support must be planned for to avoid disruptions in data collection and participant experience.
Non-Performance Specifications: Cost and customer service must be accounted for, ensuring smooth implementation and user support.

Recommendations
Tailor DHT selection to trial needs, focusing on measurement accuracy, precision, and reliability.
Engage sponsors, technology manufacturers, and patient groups to align specifications with practical and clinical requirements.
Ensure compliance with regulatory standards and implement robust processes for secure data transfer and storage.
Test DHTs for usability, tolerability, and operational reliability in representative populations before full-scale implementation.
Develop clear protocols for managing firmware updates, device malfunctions, and participant support to ensure trial continuity.

Regulatory Considerations
Ensure all data management processes comply with regulatory requirements like 21 CFR Part 11 and align with FDA guidance.
Validate DHTs within the target population to confirm their reliability and relevance for the specific trial context.
Clearly communicate how data will be used and shared to maintain ethical standards and informed consent compliance.
Minimize participant risks by selecting devices with proven safety profiles and addressing potential vulnerabilities during feasibility testing.

Findings
Sleep disturbances are common across multiple therapeutic areas, making standardized digital measures essential for cross-condition research.
Measurement accuracy varies depending on sensor placement, algorithms, and contextual factors such as sleep environment.
While home-based digital sleep tracking improves accessibility, challenges remain in ensuring consistency with clinical polysomnography.
Digital measures of sleep provide new opportunities for continuous and longitudinal monitoring, but standardization in data collection and interpretation is needed.
Stakeholders, including regulatory agencies, increasingly recognize digital sleep biomarkers, but additional validation is required to ensure widespread adoption.

Recommendations
Researchers and clinicians should integrate core digital sleep measures into study designs to improve data comparability across trials and clinical contexts.
Algorithm transparency and validation protocols should be established to enhance the accuracy of digital sleep monitoring tools.
Regulatory engagement should be prioritized early in the development process to ensure that digital sleep measures meet evidentiary standards.
Multi-stakeholder collaboration, including patient and care partner input, is essential to ensure sleep measures reflect meaningful aspects of health.
Further research is needed to refine wearable and sensor-based technologies to improve real-world applicability and clinical utility of digital sleep biomarkers.

Regulatory Considerations
The FDA and other regulatory bodies increasingly acknowledge sleep measures as potential clinical endpoints, but clear validation frameworks are necessary.
Digital sleep measures should align with industry standards such as HL7 to ensure interoperability and data integrity.
Data privacy and security regulations must be followed, particularly for continuous sleep monitoring in real-world settings.
Post-market validation and real-world evidence generation are critical to support regulatory acceptance of digital sleep biomarkers.
Developers must document the derivation of sleep measures, including algorithmic processing and sensor accuracy, to meet regulatory review requirements.

Findings
Adherence: Participants achieved an overall adherence rate of 90.18%, demonstrating the feasibility of home-based data collection over a 30-day period.
Participant Feedback: Most participants found the technology easy to use, though some reported difficulties with specific devices, such as sleeping with a wearable watch.
Device Selection: Precision, consistency, and participant preferences guided the selection of spirometry devices, with single-blow spirometry favored for ease of use.
Accuracy: Home spirometry measurements underestimated forced vital capacity (FVC) compared to historical in-clinic data, possibly due to device differences or disease progression.
Future Participation: Nine out of ten participants expressed interest in joining longer virtual studies using similar technologies.

Recommendations
Evaluate Adherence and Usability: Conduct feasibility studies to assess adherence rates and identify usability challenges before full-scale implementation.
Incorporate Participant Feedback: Use cross-over designs to gather participant preferences and feedback on device usability, data sharing, and frequency of data collection.
Validate Accuracy and Consistency: Ensure that DHTs provide precise, reliable measurements comparable to in-clinic standards and assess their performance in real-world settings.
Optimize Technology for Long-Term Use: Address issues such as wearability and participant burden to improve device acceptance and compliance.
Refine Training and Communication: Provide clear instructions and training to participants, setting expectations for using and troubleshooting the technologies.

Regulatory Considerations
Validate Home-Based Data Collection: Demonstrate that data collected remotely with DHTs are accurate, reliable, and clinically relevant for trial endpoints.
Pilot Studies for Regulatory Submissions: Use feasibility data to strengthen regulatory submissions, ensuring endpoints are validated for use in pivotal trials.
Address Technology Limitations: Acknowledge and mitigate potential discrepancies between home and clinic data, using feasibility study insights to refine protocols.

Findings
Nocturnal scratch is a clinically relevant behavior that impacts sleep quality, skin integrity, and overall disease burden in conditions like AD.
Traditional clinical outcome assessments (COAs) often fail to adequately measure scratching behavior, making digital measurement an important complement.
Digital health technologies, including wearables and sensor-based monitoring, enable passive and objective measurement of scratch behavior without relying on patient recall.
Regulatory agencies emphasize the importance of validation, ensuring digital measures are fit-for-purpose and aligned with patient needs.
Privacy, security, and compliance considerations must be prioritized, particularly in decentralized clinical trials using real-world data collection methods.

Recommendations
Digital measurement of nocturnal scratch should be integrated as an endpoint in clinical trials to capture patient-relevant outcomes objectively.
Sensor-based tools must undergo validation processes, including analytical and clinical validation, to ensure accuracy and reliability in different populations.
Stakeholders should align terminology and measurement definitions to support consistency across studies and regulatory submissions.
Usability testing with patients is critical to ensuring that wearable devices are practical and minimally burdensome.
Clinical trials should incorporate data privacy protections and clear informed consent processes to safeguard patient information.

Regulatory Considerations
FDA encourages early engagement to discuss digital endpoints, particularly through the Critical Path Innovation Meeting (CPIM) process.
Digital tools used for clinical investigations should align with 21 CFR Part 11 compliance for electronic records and data integrity.
Sponsors should ensure that digital health technologies used in trials meet validation criteria, including fit-for-purpose assessment and clinical relevance.
Privacy regulations, including GDPR and HIPAA, must be considered when handling patient data collected via wearable sensors.
Post-market monitoring and long-term validation studies are recommended to ensure continued accuracy and reliability of nocturnal scratch measurements.

Open source: Core Digital Measures of Nocturnal Scratch