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Bain EE, Shafner L, Walling DP, et al. Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia. JMIR Mhealth Uhealth. 2017;5(2):e18doi: 10.2196/mhealth.7030.
Bain, E. E., Shafner, L., Walling, D. P., Othman, A. A., Chuang-Stein, C., Hinkle, J., & Hanina, A. (2017). Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia. JMIR mHealth and uHealth, 5(2), e18. https://doi.org/10.2196/mhealth.7030
Bain, Earle E, et al. "Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia." JMIR mHealth and uHealth vol. 5,2 (2017): e18. doi: https://doi.org/10.2196/mhealth.7030
Bain EE, Shafner L, Walling DP, Othman AA, Chuang-Stein C, Hinkle J, Hanina A. Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia. JMIR Mhealth Uhealth. 2017 Feb 21;5(2):e18. doi: 10.2196/mhealth.7030. PMID: 28223265; PMCID: PMC5340925.
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JMIR Mhealth Uhealth. 2017 Feb 21;5(2):e18. doi: 10.2196/mhealth.7030.

Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia.

JMIR mHealth and uHealth

Earle E Bain, Laura Shafner, David P Walling, Ahmed A Othman, Christy Chuang-Stein, John Hinkle, Adam Hanina

Affiliations

  1. AbbVie Inc., North Chicago, IL, United States.
  2. AiCure, LLC, New York, NY, United States.
  3. CNS Network, LLC, Garden Grove, CA, United States.
  4. Chuang-Stein Consulting, Kalamazoo, MI, United States.
  5. EarlyPhase Sciences, Inc., Cary, NC, United States.

PMID: 28223265 PMCID: PMC5340925 DOI: 10.2196/mhealth.7030

Abstract

BACKGROUND: Accurately monitoring and collecting drug adherence data can allow for better understanding and interpretation of the outcomes of clinical trials. Most clinical trials use a combination of pill counts and self-reported data to measure drug adherence, despite the drawbacks of relying on these types of indirect measures. It is assumed that doses are taken, but the exact timing of these events is often incomplete and imprecise.

OBJECTIVE: The objective of this pilot study was to evaluate the use of a novel artificial intelligence (AI) platform (AiCure) on mobile devices for measuring medication adherence, compared with modified directly observed therapy (mDOT) in a substudy of a Phase 2 trial of the α7 nicotinic receptor agonist (ABT-126) in subjects with schizophrenia.

METHODS: AI platform generated adherence measures were compared with adherence inferred from drug concentration measurements.

RESULTS: The mean cumulative pharmacokinetic adherence over 24 weeks was 89.7% (standard deviation [SD] 24.92) for subjects receiving ABT-126 who were monitored using the AI platform, compared with 71.9% (SD 39.81) for subjects receiving ABT-126 who were monitored by mDOT. The difference was 17.9% (95% CI -2 to 37.7; P=.08).

CONCLUSIONS: Using drug levels, this substudy demonstrates the potential of AI platforms to increase adherence, rapidly detect nonadherence, and predict future nonadherence. Subjects monitored using the AI platform demonstrated a percentage change in adherence of 25% over the mDOT group. Subjects were able to use the technology successfully for up to 6 months in an ambulatory setting with early termination rates that are comparable to subjects outside of the substudy.

TRIAL REGISTRATION: ClinicalTrials.gov NCT01655680 https://clinicaltrials.gov/ct2/show/NCT01655680?term=NCT01655680.

©Earle E Bain, Laura Shafner, David P Walling, Ahmed A Othman, Christy Chuang-Stein, John Hinkle, Adam Hanina. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 21.02.2017.

Keywords: artificial intelligence; clinical trials as topic; medication adherence

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