Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing.

Journal: The Lancet. Digital health
Published Date: Mar 1, 2024

Abstract

Digital therapeutics (DTx) are a somewhat novel class of US Food and Drug Administration-regulated software that help patients prevent, manage, or treat disease. Here, we use natural language processing to characterise registered DTx clinical trials and provide insights into the clinical development landscape for these novel therapeutics. We identified 449 DTx clinical trials, initiated or expected to be initiated between 2010 and 2030, from ClinicalTrials.gov using 27 search terms, and available data were analysed, including trial durations, locations, MeSH categories, enrolment, and sponsor types. Topic modelling of eligibility criteria, done with BERTopic, showed that DTx trials frequently exclude patients on the basis of age, comorbidities, pregnancy, language barriers, and digital determinants of health, including smartphone or data plan access. Our comprehensive overview of the DTx development landscape highlights challenges in designing inclusive DTx clinical trials and presents opportunities for clinicians and researchers to address these challenges. Finally, we provide an interactive dashboard for readers to conduct their own analyses.

Authors

  • Brenda Y Miao
    Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA. miao.brenda1@gmail.com.
  • Madhumita Sushil
    Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
  • Ava Xu
    Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA.
  • Michelle Wang
    Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
  • Douglas Arneson
    Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
  • Ellen Berkley
    Department of Clinical Pharmacy, School of Pharmacy, University of California, San Francisco, CA, USA; UC Davis Health, University of California, Sacramento, CA, USA.
  • Meera Subash
    Division of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA; School of Biomedical Informatics, UTHealth Houston, Houston, TX, USA.
  • Rohit Vashisht
    Center for Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA, United States.
  • Vivek Rudrapatna
    Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA; Division of Gastroenterology and Hepatology, Department of Medicine, University of California, San Francisco, CA, USA.
  • Atul J Butte
    Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA.

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