Build Once, Use Everywhere: How the DEEP–EMA Pilot Reimagines Digital Measure Qualification

A recent pilot conducted by DEEP in collaboration with EFPIA and the European Medicines Agency (EMA) explored how Nocturnal Scratch in Atopic Dermatitis can serve as a real‑world test case to optimize the Qualification of Novel Methodologies (QoNM) procedure.

Digital measures are rapidly transforming drug development, yet the field still lacks standardized, technology‑agnostic approaches that enable consistent, reusable, and regulator‑ready evidence. To address this gap, DEEP, EFPIA, and EMA partnered with eight pharmaceutical companies to examine whether the DEEP platform could help structure, streamline, and future‑proof the pathway for qualifying digital endpoints.

Core DEEP Concepts Tested in the Pilot

At the heart of the pilot were several foundational concepts designed to make digital measures more robust, transferable, and scalable across technologies and clinical contexts:

1. Technology‑agnostic measure definitions

Instead of binding a measure to a specific device or algorithm, the DEEP approach defines each measure as a modular, technology‑agnostic block.
This ensures:

• A clear separation between what is being measured and how it is captured
• Easier comparison and evaluation across different technologies
• A stable foundation for evidence generation even as vendors and tools evolve

2. Target Solution Profiles (TSPs) for standardized performance expectations

The pilot tested the use of Target Solution Profiles as a way to:

• Standardize key characteristics of how a measurement should be captured
• Set performance thresholds that multiple technologies can meet
• Enable consistent evidence generation across diverse digital health solutions

This approach helps reduce redundant work across industry, increases comparability of evidence, and supports more efficient regulatory assessment.

3. Extending measures across contexts of use without re‑starting from scratch

A major strength of the DEEP model is the ability to extend an established measure definition into a new clinical context by adding context‑specific information - without needing to rebuild the entire evidence package.
The pilot demonstrated how structured measure definitions and TSPs can support:

• Re‑use of analytical and clinical validation evidence
• Efficient adaptation to new patient populations or disease areas
• Faster iteration and regulatory engagement for expanded contexts of use

4. Re‑using established solution profiles across different measures

The pilot also explored the ability to apply existing solution profiles to entirely new measures, enabling:

• Greater cross‑measure consistency
• Reduced duplication of validation activities
• Faster adoption of digital methodologies across therapeutic areas

This modular, reusable architecture was a highlight for participants and showed strong potential for broader industry application.

Impact and Learnings from the Pilot

Using Nocturnal Scratch as the real‑world test case, the pilot demonstrated how the DEEP Stack Model can support regulatory review by:

• Bringing structure and traceability to evidence generation
• Making it easier to identify what evidence is reusable and what is measure‑specific
• Supporting consistent, transparent dialogue between applicants and regulators
• Revealing opportunities to increase efficiency across the QoNM lifecycle

Early adopters have already begun applying this approach internally — in some cases rapidly adapting the model to new measures by replacing only the core concept while preserving the structure originally tested in the pilot, demonstrating its practicality and scalability.

The pilot reinforced that a structured, technology‑agnostic, and reusable framework for digital measures can improve regulatory interactions, support higher‑quality submissions, and accelerate the adoption of digital endpoints across global development programs.