A Q&A with the CEO of the Centre for Human Drug Research on hybrid trial design in early-phase neuroscience research
Decentralised clinical trials, remote assessments, and digital health technologies are reshaping clinical research. In neuroscience, the appeal is obvious. Many CNS trials place a significant burden on participants, particularly when repeated cognitive, behavioural, neurophysiological, or other pharmacodynamic assessments are required. Reducing travel, enabling home-based measurements, and collecting continuous real-world data can make studies more patient-friendly and, in later development, more representative of daily-life functioning.
But in early-phase CNS drug development, convenience is only one side of the equation. These studies are often designed to answer a very specific question: is there an early pharmacological signal, and is it strong enough to justify further development? When participant numbers are small and expected effect sizes may be subtle, noisy measurements can obscure meaningful drug effects. In that setting, decentralisation may undermine the very signal a study is designed to detect.
Clinical Leader spoke with CHDR’s CEO about how to balance patient convenience with signal integrity in early CNS trials, and why technology should enhance, rather than replace, the rigour of a dedicated Phase I research unit.
Why has there been such a strong push toward decentralised and hybrid trial models in CNS research?
The motivation is understandable and, in many ways, positive. CNS trials can be demanding for participants. Travel to a clinical research unit, repeated assessments, long study days, and protocol restrictions all create burden. Where appropriate, reducing unnecessary visits or collecting selected data remotely can help ease that burden for participants.
There is also a broader modernisation trend in clinical development. Digital tools, wearables, smartphone-based assessments, video visits, and remote monitoring platforms make it possible to collect more data, more often, and in environments that may better reflect a participant’s daily life. That is attractive, particularly in conditions where symptoms fluctuate or where real-world functioning is an important outcome.
The important point is that “more convenient” is not automatically “better.” In early CNS development, the central challenge is not simply collecting more data. It is collecting interpretable and accurate data. The trial design has to match the question being asked.
What makes early-phase CNS trials different from later-stage studies?
In early-phase CNS trials, we are often looking for relatively small pharmacodynamic effects in a limited number of study participants. The purpose is not yet to prove broad clinical efficacy in a large population. It is to determine whether the compound engages the CNS in a measurable way, whether the dose range is appropriate, and whether there is a signal worth pursuing.
That requires high-quality, data-dense measurements under controlled conditions. CNS endpoints can be sensitive to many variables: sleep, caffeine, food intake, time of day, stress, concomitant medication, learning effects, device use, environmental distraction, and even the way instructions are given. If those variables are not controlled, noise increases.
With small sample sizes, noise is especially damaging. A noisy outcome variable reduces statistical power. That means a study may fail to detect a real pharmacological effect, not because the drug has no activity, but because the measurement conditions were not precise enough. In early development, that can create a false negative and potentially stop a promising compound too early.
Why is the dedicated research unit still so important?
A Phase I unit provides a level of control that is very difficult to reproduce remotely. Participants can be assessed under standardised conditions, with consistent timing, trained staff, calibrated equipment, controlled meals, monitored sleep or rest periods, and immediate oversight for safety and tolerability.
That control matters in CNS research because the endpoints are often subtle. At CHDR, early CNS studies combine pharmacokinetics with pharmacodynamic measures such as cognitive testing, neurophysiology, pupillometry, sleep assessments, motor function, subjective scales, or other translational biomarkers. The value comes not only from each individual measurement, but from the integration of multiple assessments over time.
When participants are in-unit, we can align those measurements closely with expected drug exposure. We can capture the time course of effect, relate it to concentration, and interpret whether a signal is dose- (or better, drug concentration-) related, time-dependent, or potentially confounded by other factors. That is much harder when assessments are performed in uncontrolled settings.
Does that mean remote technologies have no role in early CNS development?
Not at all. The question is not whether technology should be used. The question is where it adds value.
Technology can be highly useful when it complements the controlled study design. For example, wearables may help characterise sleep-wake patterns, activity, heart rate, or other physiological parameters before or after an in-unit visit. Remote diaries or app-based tools may support symptom tracking, compliance, or safety follow-up. Telemedicine can reduce unnecessary travel for certain check-ins. Digital tools can also help maintain engagement between visits.
The best use of technology in early-phase CNS trials is usually supportive and additive. It can extend the observation window, provide context, improve participant experience, and generate exploratory data. But it should not replace the core controlled measurements needed to make a confident early development decision.
Where do decentralised approaches become risky?
They become risky when unsupervised measurements are treated as if they are equivalent to controlled in-unit assessments. In CNS trials, that assumption can be problematic.
A cognitive test performed at home, for example, may be affected by interruptions, differences in device performance, internet connectivity, background noise, fatigue, or whether the participant fully understands the task. A wearable may generate large volumes of data, but that does not guarantee that the data are meaningful for the pharmacologic question. Remote assessments can also introduce missing data, adherence issues, and variability in timing.
This does not mean the data are useless. It means we need to be honest about what they can and cannot tell us. Remote tools are often very interesting in later Phase II and Phase III trials, where the goal may include understanding how treatment affects patients in daily life and where larger sample sizes can absorb more variability. But in Phase I and early Phase IIa, where participant numbers are small and signal detection is critical, the priority is precision.
How should sponsors think about patient convenience in early CNS trials?
Patient convenience is important, but it should be designed around the scientific objective. The goal is not to make every study as decentralised as possible. The goal is to remove unnecessary burden without compromising the endpoints that drive decision-making.
That may mean keeping the most important pharmacodynamic assessments in-unit, while decentralising selected follow-up procedures. It may mean using remote tools for screening, pre-study stabilisation, safety monitoring, or post-dose observation, while preserving controlled conditions around peak pharmacological effects. It may also mean designing shorter in-unit stays, better visit schedules, or more participant-friendly logistics rather than moving critical measurements into an uncontrolled environment.
A balanced approach asks: which data must be collected under rigorous conditions, and which data can be collected remotely without weakening interpretation?
What is CHDR’s approach to hybrid CNS trial design?
CHDR’s approach is pragmatic. We use digital tools when they improve the study. But we are careful not to confuse innovation with decentralisation alone.
In early CNS development, the unit remains the anchor. It provides the controlled environment needed for precise pharmacodynamic measurements, safety oversight, and high-resolution PK/PD interpretation. Around that anchor, hybrid elements can be added where they reduce burden or enrich the dataset.
A well-designed early trial should give sponsors confidence: confidence that a negative result is truly negative, and confidence that a positive signal is biologically meaningful. That requires both scientific rigour and operational flexibility.
Conclusion
Hybrid CNS trials offer real opportunities to improve participant experience, broaden access, and modernise data collection. But in early-phase CNS drug development, patient convenience must be balanced against the need for signal integrity. Small studies, subtle endpoints, and complex pharmacodynamic questions demand controlled, data-dense environments.
CHDR’s position is that technology enhances early CNS trials when it is used thoughtfully: to support participants, extend observation, and enrich interpretation. It should not replace the rigour of a dedicated Phase I unit when precise signal detection is the central objective.
The key is balance. Patient-centric design matters. So does scientific discipline. In early CNS trials, the most successful hybrid models will be those that make participation easier without making the data less reliable.
