Digital Health Technologies in Clinical Drug Development

Digital Health Technologies in Clinical Drug Development

Digital health technologies have the potential to transform clinical drug development. They can collect continuous, high-resolution data in patients’ real-world environments for extended periods of time, providing researchers with an unprecedented level of insight into patients’ physiological and behavioral states. These types of data may more accurately describe a patient’s experience and enable previously unattainable scientific undertakings.

Technology enthusiasts fully embrace the vision for digital health technologies in clinical drug development. In this relatively new and rapidly advancing field, it can feel like the drive for innovative methods and products trumps the necessity for scientific rigor and clinical meaning. In order to realize their potential in drug development, digital technologies must be deployed within a thoughtful, carefully vetted, and scientifically sound study design.

From the early planning phases through data analytics and interpretation, there are many steps to building a robust study design around digital health technologies.

A recent publication highlights one of these steps, the need to ensure that the outcome measures and endpoints derived from digital health technologies represent aspects of health meaningful to patients.

The authors describe a four-level chronological process for selecting outcome measures that are meaningful to patients:

  1. Meaningful Aspect of Health (MAH) - Desired improvement to the patient and the disease state. Example: increased ambulatory activity
  2. Concept of Interest (COI) - The practical measurement of the MAH. Example: walking capacity
  3. Outcome Measures - The measurable aspect of the COI. Example: steps per day
  4. Endpoints - The clinical benefit to the patient. Example: 25% increase in steps per day1

Selecting appropriate outcome measures and endpoints is perhaps the most challenging and important step to ensuring successful digital trials. As Manta et al. explain, it requires understanding the impact of the treatment on patients and an iterative approach to development directly informed by patients. Not highlighted by Manta, but arguably equally important to success, is an in-depth understanding of the performance characteristics of the viable technologies to measure the selected outcomes.

We love to discuss clinical trial outcome hypotheses and healthcare applications and apply our expertise to measuring meaningful clinical outcomes from wearable technology. Give us a call.

Over the past ten years, we have developed our VivoSense digital outcome measures to be meaningful to both the patient populations while prioritizing technology validity to meet clinical research goals. As technologies advance and the methods around those technologies mature, we continuously innovate, keeping improved patient outcomes and good science as our core goals.

Visit our digital endpoints page for additional insights into our approach and capabilities in developing meaningful digital clinical measures.

Digital Endpoints Validated Sensor Outcome Measures Verification | Analytical Validation | Clinical Validation Learn More

Dudley Tabakin

Dudley Tabakin

Dudley Tabakin, MSc. is Chief Product Officer and co-founder of VivoSense and a fervent believer in “good data” over “big data" in the development of digital endpoints from wearable sensor technology.

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