New FDA guidance cites our framework. Here's what that means for digital endpoint strategy

The FDA’s recent publication, Key Considerations for the Development and Use of Digitally Derived Measures for Clinical Investigations, provides one of the clearest summaries to date of regulatory expectations for digitally derived measures (DDMs) and the digital health technologies (DHTs) that generate them.

In recent years, FDA’s four-part PFDD series has provided clarity and guidance on how to refocus patient voices at the center of drug development. By now it is clear that early and often engagement of patients is imperative to ensure that the most meaningful aspects of health are captured in a clinical trial.

But increasingly, researchers are faced with growing choices for how to measure those meaningful aspects of health. For those looking to navigate the tradeoffs and complementarity of Clinical Outcome Assessments (COAs) and digitally-derived measures from digital health technologies (DHTs), the FDA’s newest document offers important insight and validation of current thinking: that successful digital measurement begins with patients, meaningful outcomes, and rigorous evidence generation. All elements that are also true for a robust COA strategy. Notably, the FDA cites the publication Digital Measures That Matter to Patients: A Framework to Guide the Selection and Development of Digital Measures of Health, a publication that was co-authored by MRT’s managing director Christine (Manta) Campbell and in the six years since its publication, has helped shape thinking across the industry. This framework is deeply embedded in the work we do at Mapi Research Trust, and reflects many of the principles we’ve championed for years.

A regulatory endorsement of patient-centered digital measurement

One of the strongest themes throughout the FDA publication is that digitally derived measures (DDMs) should capture outcomes that are meaningful to patients. The agency reiterates that a meaningful aspect of health (MAH) is a specific aspect of feeling or functioning in daily life that matters to patients and should be identified early in development through qualitative interviews, direct patient input and feedback, and clinical expertise. This is the foundation of incorporating patient voices. The FDA further emphasizes the importance of understanding the nuances within the target population as well as developing disease conceptual models.

This philosophy closely aligns with the framework presented in the FDA-cited publication by Manta et al. which advocates beginning with what matters to patients and then identifying the most appropriate digital measures to capture those experiences. The FDA specifically references that publication when discussing the use of conceptual models to identify and communicate concepts of interest that link directly back to the MAH.

For our team, this citation is particularly meaningful. It demonstrates that the principles we have incorporated into our services, methodologies, and technology platforms are not merely industry best practices but are increasingly reflected in regulatory thinking.

From "what can we measure?" to "what should we measure?"

In a world of ever developing AI and technological advancements, it can be tempting to see a novel digital measure or technological capability and try to back our way into the justification. But the FDA's messaging is clear: the starting point should not be the sensor or algorithm. Instead, sponsors should begin with a deep knowledge and understanding of what matters to patients, defining the concept of interest, and establishing the context of use before ever selecting a DHT or DDM.

This mirrors the approach our team applies in outcome strategies. Whether supporting sponsors in neurology, rare disease, oncology, or other therapeutic areas, we begin with a review of the literature, disease conceptual modeling, and identification of meaningful aspects of health before recommending digital endpoints. This methodology helps ensure that technology serves the clinical question rather than the reverse.

Fit-for-purpose requires more than innovative technology

The FDA also reinforces the importance of fit-for-purpose evaluation. A DHT and the resulting DDM should have sufficient evidence of validity and be appropriate for the intended context of use, including the target population, study design, measurement schedule, and disease characteristics. For AI-enabled measures, the FDA notes that credibility assessments may also be warranted.

This is an area where having deep expertise becomes essential. Our team regularly supports sponsors with:

Context-of-use definition
Endpoint strategy and endpoint selection
Gap analyses of existing evidence
Evaluation of available DHTs and digital measures
Regulatory-aligned evidence generation plans
Validation roadmaps for novel endpoints

By connecting scientific rationale, patient relevance, and regulatory expectations, we help sponsors establish the evidence required to support fit-for-purpose determination.

Verification, validation, and the expanding importance of V3

A major focus of the FDA publication is the need for rigorous verification and validation. The agency reiterates that DHTs should undergo verification to demonstrate accurate sensor performance, and that DDMs require both analytical and clinical validation. Analytical validation demonstrates that algorithms accurately derive physiological characteristics from raw data, while clinical validation demonstrates that the resulting measure captures the intended concept and reflects meaningful aspects of health.

The publication also references the evolving V3+ framework as an important resource for digital health technologies.

This area represents another natural intersection with our expertise, as the original V3 publication was also co-authored by MRT’s managing director, Christine. MRT, in collaboration with ICON, is home to Atlas Network, the insights and evidence platform that routinely evaluates evidence from DHTs, anchoring our quality bar with the criteria outlined by V3 and the Evidence Checklist. Leveraging Atlas, our team supports sponsors to understand areas of well-validated, mature DDMs, as well as opportunities for innovation and novel measurement – and what evidence is needed for a robust justification in regulatory submissions.

Importantly, we view validation as extending beyond technical performance to include demonstrating that a measure captures experiences that are relevant and meaningful to patients.

Utility and usability by design

The FDA publication includes an entire section relating to usability, emphasizing that users must understand and be able to follow instructions for use. The agency highlights the importance of accommodating sensory, cognitive, motor, and language differences while evaluating adherence, burden, fatigue, and tolerability.

This emphasis reflects a growing recognition that a technically valid measurement may still fail if patients cannot use the technology consistently or comfortably.

Our patient-centered research approach directly supports this requirement with thorough review of interviews, qualitative studies, usability testing, patient experience research, and evaluation of device burden. These activities help sponsors ensure that digital measures are both scientifically robust and practical for real-world implementation.

Looking ahead

Perhaps the most important takeaway from the FDA publication is not any single recommendation, but the overarching message: successful digitally derived measures require a patient-centered, evidence-based, and multidisciplinary approach. The agency highlights stakeholder engagement, meaningful health outcomes, fit-for-purpose evidence, verification and validation, usability, and careful management of sources of error as foundational elements of digital measurement development, the same way they are foundational to traditional outcomes such as Patient-Reported Outcomes (PROs).

The fact that the FDA explicitly cites the “Digital Measures That Matter” publication within this framework is a strong signal that the field continues to move toward approaches grounded in patient meaningfulness and conceptual rigor.

For our team at Mapi Research Trust, it is encouraging to see regulatory guidance increasingly align with the principles that have informed our work for years. As sponsors continue to integrate wearable sensors, digital biomarkers, and digitally derived measures into clinical development programs, there is an opportunity in front of us: to generate evidence that reflects outcomes that truly matter to patients while meeting the scientific and regulatory standards needed to support medical product development.

Thank you to Caprice Sassano, Sr. Outcomes Researcher, for their contribution to this article.