Digital therapeutics (DTx) are evidence-based, clinically evaluated software and medical devices used to manage and treat a vast array of medical disorders and illnesses. The COVID-19 pandemic brought unique challenges to therapeutic delivery, accelerating the use of DTx and the acceptance of remote care models. As a result, there is ample opportunity for DTx to be used in other areas of healthcare, particularly in regard to central nervous system (CNS) disorders, with the potential of resolving various healthcare delivery obstacles – including accessibility, provider/patient burden, provider shortages, and cost overruns.

With CNS disorders, DTx can be used as (1) a standalone treatment; (2) a treatment augmentation, or, more specifically, as a supportive treatment applied with another intervention; or (3) a diagnostic. As such, DTx can offer more flexibility in therapeutic intervention, and can be useful when the complexity of the therapeutic intervention exceeds what could be performed in a healthcare setting. What’s more, they can offer many advantages, including real-time assessment and passive monitoring of patients. As the demand for DTx grows, sponsors will benefit from monitoring the evolving regulatory landscape, which will give them the ability to take a more strategic approach to clinical development.

In regards to CNS disorders, DTx may target (1) instances of low disease burden with a focus on the subjective patient experience; (2) severe illness with the goal of improving daily functioning; or (3) treatment refractoriness. DTx may be used for neurologic or psychiatric disorders, with a focus on making psychotherapeutic modalities, including principles of cognitive behavioral therapy, accessible to patients. These modalities might include symptom logs, learning and exercise modules on cognitive restructuring, mindfulness exercises, motivational enhancement techniques, training exercises, and contingency management.

This blog will explore the role of DTx in CNS clinical trials, namely in the regulatory landscape of DTx, clinical trial considerations such as data management and endpoint selection, payer coverage, and, finally, the future of DTx.

Regulatory landscape of digital therapeutics

It is very important to understand where a DTx lies in the regulatory landscape, since its classification often guides a sponsor’s clinical trial decisions. In the United States, DTx is classified under “software as a medical device” within the U.S. Food and Drug Administration’s (FDA) Center for Devices and Radiological Health. DTx can also be classified as an FDA Class I, II, or III medical device. Their definitions are as follows:

  • Class I medical devices are not used to sustain life or prevent impairment to an individual’s health, and, as a result, do not have much impact on the patient
  • Class II medical devices have an increased chance of sustained contact with a patient, posing a moderate risk to a patient’s safety
  • Class III medical devices often describe permanent implants that support life, posing a high risk to a patient’s safety.

Clinical trial considerations

When it comes to clinical trial considerations, DTx capabilities are flexible, and can be used in hybrid and fully decentralized clinical trials (DCT). This has the potential to ease costs and enhance participant recruitment, in addition to decreasing the sampling and data collection burden on study sites and participants.

Data considerations

Data strategies are vital when designing a clinical trial with digital devices. The use of DTx in DCTs often produces larger datasets than traditional trials, requiring a data infrastructure that is robust, adaptable and scalable. In fact, in CNS trials, data from a few dozen patients can easily approach one billion data points per day. The complexity of datasets in CNS trials is multilayered, since data are often combined with electronic patient-reported outcome software. Therefore, data will need to be integrated from a variety of different sources, making it necessary for companies to implement a strong cybersecurity plan to ensure that data coming from disparate sources are equally protected.

Both participants and study staff will require training on DTx device usage and how data will be shared. To ensure that data is not lost, real-time compliance data is recommended. Study staff should have plans to catch and address non-compliance in the context of when, where and how a DTx is utilized, in addition to both device loss and malfunction.

Participant recruitment and retention

Without a sufficient number of willing participants, a clinical trial cannot run. In fact, an average of 30 percent of participants eventually drop out of clinical trials. DTx can potentially increase participant recruitment and retention with its remote options, introducing flexibility in trial participation, and removing location as a limiting factor.

Although DTx may increase participant engagement, they have the potential of adding to participant burden. Sponsors may lower participant burden by (1) adopting a maximum passiveness approach to data collection; (2) selecting easy to use devices; (3) creating a unified interface between the participant and the clinical trial; (4) including reminders and compliance monitoring; and (5) providing staff contact information within the DTx.

Safety considerations

Of course, safety should be paramount when conducting any clinical trial. This is magnified in DTx clinical trials, where participants will have far more interaction with the therapeutic than with investigators and healthcare providers, imposing further safety considerations. As such, when designing a CNS trial using DTx, it is important to consider safety monitoring, which should influence the type of data collected, frequency of data collection, and the review of these data. Additionally, in these trials, symptom severity should be assessed, enabling appropriate monitoring for decompensation. Both criteria and steps for intervention should be included in the protocol, in the event that a participant’s symptoms worsen. Furthermore, suicidality assessment should be assessed at baseline and regular intervals, giving sponsors insight to a participant’s risk.

Endpoint selection and study objectives

Primary, secondary and exploratory endpoints measure the positive or negative impacts that a therapeutic, such as DTx, may have on a participant of a clinical trial. When assessing these endpoints in CNS clinical trials for DTx, it is important for healthcare professionals to consider patient reported outcomes (PROs), performance outcomes, clinician reported outcomes (ClinROs), observer-reported outcomes, and even ecological momentary assessments.

Taking into consideration the need for evidence generation for regulatory review and payer reimbursement decisions, the specific type of data used to quantify endpoints should be carefully selected. For example, ClinROs should be used with primary endpoints, which are generally efficacy measures that address the main research question. ClinROs are verified by trial staff trained in the clinical trial protocol, making them appropriate qualifiers for primary endpoints, which require streamlined review and efficacy assessments during regulatory submission.

PROs, on the other hand, should be considered only for secondary endpoints, which are typically not sufficient to influence decision-making by themselves, but may support the claim of efficacy by demonstrating additional effects. PROs face less pressure for standardization, giving them the possibility of being conducted remotely at specified intervals.

Tokenisation and real-world evidence

Participant tokenisation links different sources of patient-level, real world evidence – while, at the same time, protecting patient privacy – thereby giving researchers invaluable insights into new data trends. Tokenisation may offer a deeper understanding of the patient journey, providing past and current data on a participant’s medical history, medical events, concomitant medications, and ongoing endpoint evaluation. These insights will provide a robust variety of data sources to be used when transitioning from the clinical to commercialisation phase. As such, tokenisation may offer unique insights regarding the effects of clinical trials over a longer period of time. Furthermore, tokenisation can integrate wider populations into the dataset, improving sample diversity and overall comparative accuracy. In the context of CNS clinical trials, tokenisation has the potential to improve data gathered through DTx by removing unnecessary signals gathered by the DTx using noise filtering. 

Payer coverage

Payer coverage of DTx interventions can pose unique challenges as a result of contrasting evidence standards between the Centers for Medicare and Medicaid (CMS) and the FDA. For example, the CMS requires that intervention be “reasonable and necessary,” whereas the FDA demands that products be “safe and effective.” Oftentimes payers follow CMS decisions because of their exacting formulary guidelines, which, at the same time, can pose many obstacles.

For example, there have been situations where CMS provided coverage during evidence development, in which coverage was only for participants of an additional clinical trial, usually with a longer follow-up period than was initially required under FDA review. Therefore, when designing clinical studies, it is important to take into account the type of evidence that should be generated to ensure CMS and payer coverage. This often requires more granular or specific information, such as pinpointing exactly which populations might benefit from the intervention, and the long-lasting effects of a therapeutic.

Even though reimbursement is minimal, DTx may lessen payer burden due to reduced patient-provider interaction. That said, the NIH recommends that coverage of prescription DTx focus on products that have been developed to treat, manage, and prevent illness; in addition to those cleared through the FDA.

The future of DTx

To ensure their widespread use moving forward, DTx will have to demonstrate their usefulness, namely through improvements to clinical outcomes and healthcare savings. For example, DTx must show measurable decreases in hospitalizations, enhanced patient engagement, and improved compliance. Moreover, they must address the underserved needs in healthcare, including insufficient access to care. This is of the utmost importance in the CNS space, where it is often harder to find success in clinical trials. As such, showing the usefulness of DTx in CNS clinical trials will prove critical to its future viability.

Explore more about the role of DTx in CNS clinical trials in our whitepaper, ‘A mind for digital therapeutics: Considerations for DTx clinical trials in CNS indications’.