Cited by 67Mobile Health and mHealth ApplicationsStatistical Methods in Clinical TrialsMedication Adherence and Compliance

Digitally Enabled, Patient‐Centric Clinical Trials: Shifting the Drug Development Paradigm

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Dockendorf, Marissa F., Hansen, Bryan J., Bateman, Kevin P., Moyer, Matthew, Shah, Jyoti K., Shipley, Lisa A.·2021·Clinical and Translational Science

Abstract

The rapidly advancing field of digital health technologies provides a great opportunity to radically transform the way clinical trials are conducted and to shift the clinical trial paradigm from a site‐centric to a patient‐centric model. Merck’s (Kenilworth, NJ) digitally enabled clinical trial initiative is focused on introduction of digital technologies into the clinical trial paradigm to reduce patient burden, improve drug adherence, provide a means of more closely engaging with the patient, and enable higher quality, faster, and more frequent data collection. This paper will describe the following four key areas of focus from Merck’s digitally enabled clinical trials initiative, along with corresponding enabling technologies: (i) use of technologies that can monitor and improve drug adherence (smart dosing), (ii) collection of pharmacokinetic (PK), pharmacodynamic (PD), and biomarker samples in an outpatient setting (patient‐centric sampling), (iii) use of digital devices to collect and measure physiological and behavioral data (digital biomarkers), and (iv) use of data platforms that integrate digital data streams, visualize data in real‐time, and provide a means of greater patient engagement during the trial (digital platform). Furthermore, this paper will discuss the synergistic power in implementation of these approaches jointly within a trial to enable better understanding of adherence, safety, efficacy, PK, PD, and corresponding exposure‐response relationships of investigational therapies as well as reduced patient burden for clinical trial participation. Obstacle and challenges to adoption and full realization of the vision of patient‐centric, digitally enabled trials will also be discussed.

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  • Digital biomarkers and COAs serve purposes similar to those of their conventional counterparts, with roles in diagnosis, monitoring, and prognosis of disease.

    “Digital biomarkers and COAs serve purposes similar to those of their conventional counterparts, 26 with roles in diagnosis, monitoring, and prognosis of disease. 27”

    From Developing digital health technologies for frontotemporal degeneration (2025) · cites this paper as [27]

    The DIGITAL BIOMARKERS section describes digital biomarkers as a class of biomarkers and says existing endpoints can be measured digitally. It also describes electronic patient-reported outcomes as outcomes collected electronically, supporting one type of digital clinical outcome assessment, but it does not establish the comparison for COAs generally. The diagnosis, monitoring, and prognosis clause is attached to citation 27, not this source’s citation 26. (LLM, conf=0.82)

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Research works printed but not linked: 4

  1. [47]Anderson, M., Dockendorf, M.F., Xue, L., Dreyer, D., Xie, I. & Bateman, K.P. Enabling patient centricity in clinical development through at‐home sample collection. Poster presented at 4th FDA/PQRI Conference on Advancing Product Quality: Patient‐Centric Product Design, Drug Development, and Manufacturing. April 9–11, 2019 < https://pqri.org/4th‐pqri‐fda‐conference‐on‐advancing‐product‐quality‐posters/> (2019). Accessed April 21, 2020.
  2. [61]FDA‐NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource [Internet]. Silver Spring (MD): Food and Drug Administration (US); co‐published by National Institutes of Health (US), Bethesda (MD) < https://www.ncbi.nlm.nih.gov/books/NBK326791> (2016). Accessed April 20, 2020. 27010052
  3. [66]Zhao, M., Yue, S., Katabi, D., Jaakkola, T. & Bianchi, M. Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture. Poster presented at 34th International Conference on Machine Learning (ICML). August 7–9, 2017. Sydney, Australia. (2017).
  4. [68]Bellerophon Announces Agreement with FDA on Regulatory Approval Pathway for INOpulse for Treatment of Pulmonary Hypertension Associated with Interstitial Lung Disease. Bellerophon. Press release < http://investors.bellerophon.com/news‐releases/news‐release‐details/bellerophon‐announces‐agreement‐fda‐regulatory‐approval‐pathway> (2019). Accessed April 15, 2020.

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Authors
Dockendorf, M. F., Hansen, B. J., Bateman, K. P., Moyer, M., Shah, J. K., & Shipley, L. A.
Affiliations
Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
Corresponding author
Dockendorf, Marissa F.
Venue
Clinical and Translational Science
Publisher
Wiley
Published
2020-11-30
Volume
14
Issue
2
Pages
445-459
ISSN
  • 1752-8054 (ISSN-L)
  • 1752-8062
OpenAlex
W3091889055
Cited by
67
References
69
Citations by year
2026: 9 · 2025: 8 · 2024: 19 · 2023: 13 · 2022: 13 · 2021: 5
FWCI
1.48
Type
journal article
Language
en
Open access
Locations
  • Clinical and Translational Science (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
Keywords
digital health technologies, medication adherence, digital biomarkers, digital platforms, patient engagement, patient burden, pharmacokinetics, pharmacodynamics, exposure-response relationship, drug development
MeSH terms
Wearable Electronic Devices, Drug Development, Ambulatory Care, Clinical Trials as Topic, Humans, Patient Participation, Telemedicine, Monitoring, Ambulatory, Patient-Centered Care

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