Findings
Digitally-derived endpoints must align with trial goals, reflect the concept of interest (COI), and demonstrate clinical relevance.
Validation involves both verification of the digital tool’s performance and ensuring the endpoint measures what it claims to measure.
Early-phase trials should assess usability, tolerability, and data privacy to ensure tools are operationally feasible for the intended population.
Regulatory alignment on endpoints, including their ability to demonstrate meaningful change, is critical before pivotal trials.
Statistical analysis plans must account for the unique aspects of digital endpoints, such as data quality and missing data considerations.

Recommendations
Define target populations and meaningful aspects of health (MAH) early in development to guide endpoint selection.
Conduct gap assessments of existing endpoints and propose clinically meaningful differences for patient outcomes.
Validate digital tools through verification (e.g., accuracy, reliability) and usability studies specific to the intended population.
Engage with regulators to align endpoints with evidentiary requirements for pivotal trials and label claims.
Prepare statistical plans and supporting evidence to justify the inclusion of digitally-derived endpoints in pivotal trials.

Regulatory Considerations
Verification and validation of DHTs should meet FDA and EMA standards, ensuring endpoints are fit-for-purpose and clinically relevant.
Align endpoints with regulatory requirements, demonstrating meaningful change that reflects treatment benefit.
Compile evidence of clinical validation, including how endpoints detect meaningful changes during treatment.
Address privacy, scalability, and operational feasibility to meet regulatory expectations for pivotal trials.
Consult regulatory guidance documents, such as FDA’s draft guidance on DHTs for remote data acquisition and EMA’s methodologies for drug development.