“In-House” Data on the Outside-A Mobile Health Approach

Bringing Clinic-Grade Cardiovascular Data Into Real-World Settings

Mobile health (mHealth) technologies promise something traditional clinical measures can’t: dense, continuous patient data captured against the backdrop of everyday, real-life behavior. But that promise only holds if the mHealth data actually agrees with the clinic-grade measures sponsors already trust. A study published in Clinical Pharmacology & Therapeutics, a Phase I trial conducted by Merck & Co., Inc. in collaboration with Koneksa Health, set out to test exactly that concordance.

How the Study Was Designed

• Study population and structure: The two-part Phase I trial enrolled 18 healthy male subjects to validate cardiovascular mHealth technologies against traditional clinical approaches.
• Part I: concordance testing: Over a 5-day period, the study compared mHealth-derived measures of heart rate (HR) and blood pressure (BP) to those obtained through traditional methods, testing hypotheses of similarity between in-clinic and at-home measurements.
• Built-in pharmacological challenge: The trial design also assessed whether continuous mHealth monitoring could detect the expected physiological effects of a pharmacological intervention, testing sensitivity, not just baseline agreement.
• Purpose beyond validation: Rather than treating mHealth data as a novelty, the study was designed to determine whether continuous, real-world data streams could stand in for, or meaningfully supplement,  traditional in-clinic vital sign collection in drug development.

The Bigger Picture for Sponsors

This study speaks directly to a question every sponsor evaluating decentralized or hybrid trial designs eventually asks: can mHealth data be trusted to the same degree as data collected in a clinical setting? Demonstrating concordance between mHealth and traditional measures, and showing that mHealth monitoring is sensitive enough to detect real pharmacological effects, is a prerequisite for using these technologies as trial endpoints, not just supplementary color.

This is the exact kind of concordance and sensitivity testing Koneksa Health builds into digital measurement strategy for sponsors: proving that data collected outside the clinic holds up to the standard required inside it.

Reference: Huang Q, Crumley T, Walters C, et al. “In-House” Data on the Outside A Mobile Health Approach. Clin Pharmacol Ther. 2020;107(4):948-956. doi:10.1002/cpt.1790. PMID: 31955410.