Digital therapeutics (DTx) play a role in improving medication adherence and behavioral change. DTx solutions that have undergone clinical trials and were approved by the FDA have been applied in care related to diabetes, obesity, cardiovascular, mental and behavioral health, hypertension, and insomnia. According to the Digital Therapeutics Alliance (DTA), DTx deliver “evidence-based interventions driven by high-quality software programs to treat, manage, or prevent a disease or disorder.” DTx interventions are administered independently or with medications, devices, or other therapies.
The rising prevalence and burden of chronic disease worldwide have necessitated the development of comprehensive disease management solutions. Due to the demonstrated impact of digital solutions, e.g., reduction in rehospitalizations and emergency department visits for patients after acute myocardial infarction (AMI), DTx solutions are receiving increasing attention backed by funding for DTx clinical trials. The Digital Therapeutics market in North America is projected to grow at a compound annual growth rate (CAGR) of 30.7% between 2023 and 2032. Growth drivers include the increase in chronic care expenditure, venture funding for novel startups, and favorable initiatives, e.g., government initiatives to improve personalized care for chronic health conditions.
This article explores key trends and predictions in the field of DTx clinical research, including evidentiary standards, DTx trial design considerations, the role of artificial intelligence, patient adoption, and the generation of evidence for essential elements of DTx solutions.
The Future of Digital Therapeutics Clinical Trials
To be accepted by patients, physicians, providers, payers, and policymakers, DTx must demonstrate their value and impact by generating clinical evidence through rigorous clinical trials complemented by real-world data. Some recent developments in this space and considerations for the future are described below.
1. Evidentiary standard
DTx solutions are assessed and cleared by regulatory bodies, e.g., the U.S. Food and Drug Administration (FDA), to support product claims regarding risk, efficacy, and intended use. In 2022, the DTA published a document with foundational principles outlining the clinical evidence necessary for the appropriate and efficient assessment of DTx interventions.
2. Drugs vs. DTx clinical trials
Similarities and differences that need to be considered when planning for DTx clinical trials. Like pharmaceuticals, the therapeutic effect of DTx for specific conditions must be clinically verified, and a prescription is needed. Unlike pharmaceuticals, DTx have lower development costs (less than 1%) and approximately half the development period required. Further, rapid updates to DTx software to align with best-practice clinical guidelines or adaptive algorithms result in challenges in predicting outcomes. DTx solutions do not require the complex distribution channels that drugs need, instead reaching patients through developers and platform providers. Drug efficacy is affected by physiological characteristics; however, DTx efficacy is affected by demographic and sociocultural factors and cognitive abilities. On a related point, access to DTx may need to be improved due to a digital literacy barrier, the need for prerequisites (e.g., smartphones), and data security issues. Patient engagement is a significant factor in ensuring the success of DTx solutions.
3. DTx clinical trial design
Companies developing DTx products encounter the same challenges as those in drug discovery and development, including clinical trial patient recruitment and retention, data quality, timelines, and costs. In addition, there are technical security concerns related to all-digital therapeutic interventions. DTx differs from drugs because it requires no physical logistics, and its endpoints can be captured in the app itself, making it well-suited for decentralized clinical trials (DCT).
4. Artificial intelligence (AI) and machine learning (ML)
Evaluating the safety and efficacy of algorithms in AI/ML-based DTx is challenging as training datasets may not capture social determinants of health or other biases in diverse patient populations.
5. Integrated offerings
Intending to offer a combined product, some companies develop their DTx and other therapies in parallel, e.g., Orexo’s sublingual combination of buprenorphine/naloxone for opioid use disorder (OUD) and its digital web-based treatment for OUD. Joint development of combined offerings may complicate the regulatory process.
6. Patient adoption
A recent study analyzed patient acceptance of DTx and established a framework to measure the interplay between rational and institutional factors. The authors found a relationship between perceived usefulness (PU) and intention to use (ITU), as well as perceived ease of use and PU. Future clinical trials for new DTx may study this aspect as well.
Evidence Generation for Key Elements of DTx Solutions
Adatia et al. (2023) believe the following elements are essential to impactful DTx solutions.
Clinical research for future DTx needs to consider:
- Regular monitoring, measurement, and feedback are conducted through connected medical devices.
- Role of payers and providers who, in DTx like Livongo, reward good behavior and penalize poor adherence to care.
- Impact of personalized coaching and support on health outcomes
- Behavioral modification through gamified challenges and incentives
- Contribution of an active virtual community
- Patient preference for an integrated journey in digital health ecosystems
- Effectiveness of patient education
- Role of advanced analytics to identify and predict triggers to prevent health events
Emerging challenges. In addition to developing evidence to address the lack of funding, regulatory requirements, and poor adoption, DTx developers recognize the need to conduct clinical trials to prove efficacy and secure proper reimbursement.
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