title: Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia.
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.
  
  
  BACKGROUND
  ClinicalTrials.gov NCT01655680 https://clinicaltrials.gov/ct2/show/NCT01655680?term=NCT01655680.
authors.affiliation: AbbVie Inc., North Chicago, IL, United States.
authors.forename: Earle E
authors.identifier: http://orcid.org/0000-0001-5673-4036
authors.initials: EE
authors.lastname: Bain
authors.affiliation: AiCure, LLC, New York, NY, United States.
authors.forename: Laura
authors.identifier: http://orcid.org/0000-0001-7558-2867
authors.initials: L
authors.lastname: Shafner
authors.affiliation: CNS Network, LLC, Garden Grove, CA, United States.
authors.forename: David P
authors.identifier: http://orcid.org/0000-0001-8638-2086
authors.initials: DP
authors.lastname: Walling
authors.affiliation: AbbVie Inc., North Chicago, IL, United States.
authors.forename: Ahmed A
authors.identifier: http://orcid.org/0000-0002-4937-2775
authors.initials: AA
authors.lastname: Othman
authors.affiliation: Chuang-Stein Consulting, Kalamazoo, MI, United States.
authors.forename: Christy
authors.identifier: http://orcid.org/0000-0002-8087-3439
authors.initials: C
authors.lastname: Chuang-Stein
authors.affiliation: EarlyPhase Sciences, Inc., Cary, NC, United States.
authors.forename: John
authors.identifier: http://orcid.org/0000-0002-7337-6477
authors.initials: J
authors.lastname: Hinkle
authors.affiliation: AiCure, LLC, New York, NY, United States.
authors.forename: Adam
authors.identifier: http://orcid.org/0000-0003-0588-1874
authors.initials: A
authors.lastname: Hanina
keywords: artificial intelligence; clinical trials as topic; medication adherence