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Accelerate the adoption of novel digital clinical measures in clinical research

The challenge

Digital clinical measures that are meaningful to patients are revolutionizing how we evaluate health. Yet, some of the greatest value associated with digital endpoints remains out of reach. This is especially true for novel digital clinical measures that capture symptoms of disease that haven’t been measured before.

The solution

To address this, DATAcc has developed the Validating Novel Digital Clinical Measures resources for DHT developers and biostatisticians.

Adopting these resources in your work will unlock the full potential of novel digital clinical measures for scientific and clinical decision-making, ultimately for new therapies to reach patients. These resources will accelerate the adoption of digital endpoints in clinical research and related regulatory interactions.

Resources designed for you

Use these resources to establish a clear decision process for designing and conducting analytical validation for your digital clinical measure of interest, whether it is for a novel or previously assessed outcome.

DHT developers

Accelerate your analytical validation studies and streamline your interaction with regulators

Biostatisticians

Support your colleagues in developing statistically sound analytical validation studies and access a simulation toolkit to quickly game out more complex reference measure comparisons

Our funder

We are grateful to our funder Arnold Ventures.

Our collaborator

This work was conducted as a Public-Private Partnership (PPP) with the FDA’s Center for Drug Evaluation and Research (CDER).

This work was supported by the PPP CDER liaison and a group of experts in the life sciences who made invaluable contributions.

The Statistical Advisory Committee
Andrew Potter, Andrew Trigg, Berend Terluin, Bohdana Ratitch, Chakib Battioui, Chen Chen, Colleen Russell, David Reasner, Eric Daza, Frank Pétavy, Jakob Bjorner, Joss Langford, Kevin Weinfurt, Leif Simmatis, Libby Floden, Robert Wright, Rolando Acosta, Sachin Shah, Valentin Hamy, Yiorgos Christakis

See how others are using these resources

Eric J. Daza | Founder and Chief Editor, Stats-of-1

Chen Chen | Senior Research Fellow, Lee Kong Chian School of Medicine Singapore

Libby Floden | Biostatistician, Head of Endpoints, Evinova

Leif Simmatis | Postdoctoral Researcher, University of Toronto

Additional resources to support your success

V3+ Framework

DATAcc by DiMe’s V3+ Framework established a robust and widely adopted approach to:

Modularly conduct verification
Analytical validation
Usability validation
Clinical validation of sensor-based digital health technologies (sDHTs)

Analytical validation can be especially complex because it relies on a fit-for-purpose reference measure, which can be difficult to obtain.

For a quick refresher on the V3+ Framework, enroll in the Digital Medicine Academy’s 30-minute course.