Decentralized trials expand and diversify the recruitable population, align trial conditions with home use, and tighten endpoint quality by reducing rater and site variability. [Photo courtesy of Lindus]
The path to market for central nervous system (CNS) treatments and devices is brutal. Recruitment is slow, and patient burden is high, while multisite structures introduce rater and protocol variability that adds noise to endpoints.
On top of that, regulatory expectations for novel technologies keep shifting. CNS drugs face a 5.9% likelihood of FDA approval, and device trials run into most of the same problems.
Decentralized clinical trials (DCTs) target those structural issues directly, while the conventional, site-heavy model leaves them unaddressed. Given how much weight regulators now place on trial design, the distance between what reviewers expect to see and what a traditional model can deliver is a real problem for CNS device sponsors.
Decentralization closes that distance in three specific ways, and each one reinforces the case sponsors are trying to make to regulators.
1. A bigger, more representative patient pool
CNS trial enrollment has always been hard. The eligible population is small, and the cognitive, logistical, and emotional burden of visiting trial sites filters out a meaningful share of people who could otherwise participate. Recent Tufts CSDD research shows CNS trials face higher screen failure and dropout rates of any therapeutic area.
DCTs remove the geographic gate, making national recruitment feasible. Trials can pull from online health communities, consented patient databases, and digital medical records without being constrained by who lives near a major academic site.
This matters twice over for CNS devices intended for home use. The trial conditions match the use conditions, which strengthens external validity. That is important for any benefit-risk assessment, especially when there is no equivalent approved device to anchor against.
There is also a representation problem. CNS trials have a documented record of underreporting race and ethnicity data and the FDA is paying closer attention to it. Reaching beyond traditional sites is one of the few credible ways to close that gap.
2. Trial design that fits the patient
For people living with neuropsychiatric conditions, the demands of trial participation can become confounding variables on their own. Fatigue, anxiety, stigma, and caregiver dependence influence who enrolls, who stays, who attends visits, who adheres to treatment, and how complete the data is.
The FDA has increased its scrutiny of how de novo submissions account for adherence. For example, in its late 2025 authorization of the first home-use brain stimulation device for major depressive disorder, the agency treated compliance as a core component of the evidentiary package, not merely an operational consideration.
Remote monitoring, digital adherence tracking, and structured virtual check-ins build an evidence environment that maps to how a device is used at home. For home-use devices, that is the only credible way to capture the outcomes regulators care about.
3. Less endpoint noise from rater and site variability
Site-to-site variability is the other structural problem. CNS endpoints typically rely on clinician- and performance-based measures that require consistency across raters, sites, and time points. Most multisite protocols allow each site to run a slightly different version of the same study, which makes it hard to maintain consistency.
Decentralized models reduce that variability. A single controlled digital setting for remote evaluations, centralized rater training, and real-time protocol monitoring all reduce deviations. For neuromodulation devices with subjective endpoints like sleep or mood, consistency drives data quality.
These improvements do not solve neuromodulation’s hardest methodological problem: blinding integrity. Studies of repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and related modalities consistently show that patients can detect sensory cues such as tingling, warmth, or sound and determine which arm they are in. Decentralized administration cannot fix that. What it can do is strip out the rater-level variability that compounds the problem.
In its review of the first home-use tDCS device authorized for major depression, the FDA explicitly noted that blinding was inadequate, with most actively treated patients correctly guessing their assignment. For de novo CNS submissions, validating a sham condition that mimics the active device is now an expectation reviewers will press hard on.
Designing for the reviewer from day one
For sponsors going through the de novo pathway with no predicate to lean on, the trial design is the regulatory argument. Reviewers cannot anchor benefit-risk evaluation on a comparable approved device, so the credibility of the evidence rests almost entirely on how the study was built: who it enrolled, how representative they were, how the device was used, and how cleanly the endpoints were measured.
Decentralized approaches strengthen the answer to each of those questions. They expand and diversify the recruitable population, align trial conditions with home use, and tighten endpoint quality by reducing rater and site variability. As CNS device development accelerates, particularly for noninvasive home-use products, the trial model has to reflect how the device is actually used.
A predictable path to approval depends on building that argument from the start, inside a single integrated operating model, rather than retrofitting it across fragmented sites and vendors after problems surface. Sponsors who treat decentralization as the default give reviewers the cleanest version of that argument to evaluate.
Michael Young is co-founder and co-CEO of Lindus Health. [Photo courtesy of Lindus]
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The opinions expressed in this blog post are the author’s only and do not necessarily reflect those of Medical Design & Outsourcing or its employees.
