Reprogramming Chronic Care: AI-Driven Digital Therapeutics for a Connected, Personalized and Equitable Health Future  

Abstract

Background: Non-communicable diseases such as diabetes, cardiovascular disease, and mental disorders contribute to 74% of global annual deaths, creating a major strain on healthcare systems. Conventional episodic care models are inadequate for continuous management, highlighting the need for innovative solutions.

Purpose: This review systematically evaluates the role of AI-powered Digital Therapeutics (DTx) in chronic disease management, examining clinical evidence, therapeutic outcomes, regulatory frameworks, and future integration with multidisciplinary healthcare systems, with a focus on low- and middle-income settings such as India.

Methods: A comprehensive literature search of clinical trials, meta-analyses, and real-world studies was conducted. Regulatory frameworks like the FDA’s Software as a Medical Device (SaMD) and India’s Ayushman Bharat Digital Mission (ABDM) were analyzed to assess the positioning of Digital Therapeutics (DTx) in healthcare systems.

Results: Digital therapeutics (DTx) showed significant advantages in chronic disease management: HbA1c reduction of 0.67% in Type 2 Diabetes patients, improved hypertension control with 84% of patients maintaining sustained blood pressure control over three years, and PHQ-9 score reductions by 7.3 points in depression. The AI-driven DTx platform provided real-time adaptive interventions using digital biomarkers and phenotyping. Despite these outcomes, widespread adoption faces challenges from low digital literacy, regulatory uncertainty, and inadequate reimbursement structures, especially in India.

Conclusion: AI-powered Digital Therapeutics (DTx) offer transformative solutions for chronic disease management by enabling personalized, adaptive care. Integrating DTx with Electronic Health Records (EHRs) enhances clinical decision-making and preventive care, but implementation is hampered by regulatory fragmentation and technological gaps.

  • Page Number : 36-57
  • Published Date : 2025-10-20
  • Keywords
    Digital therapeutics (DTx), Chronic disease management, Artificial intelligence (AI) in healthcare, Personalized medicine, Digital phenotyping
  • DOI Number
    10.15415/jptrm.2025.131004
  • Authors
    Soumarshi Das and Ravinder Singh

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