A critical moment in a complex field
Despite the surge in scientific interest and investment, neuroscience trials are entering a critical inflection point. Complexity is rising, timelines are stretching, and patient needs are evolving. Sponsors continue to face persistent barriers: slow recruitment, high dropout rates, and escalating costs. Phase II and III neuroscience trials’ metrics over the past ten years reveal a landscape marked by volatility and transformation. Enrollment rates have fluctuated in response to global disruptions such as the COVID-19 pandemic, geopolitical instability, and changes in the standard of care. The exponential growth in neuroscience research has intensified competition for patients, making recruitment increasingly difficult. A new model is needed; one that’s cross-therapeutic, patient-focused, and built for the future.1, 2
What is holding us back?
Scientific, operational, and patient-related constraints uniquely burden neuroscience trials. The heterogeneity of neurological conditions, coupled with delayed diagnosis, social stigma, and problematic access to specialized care, results in small and fragmented patient pools. The lack of reliable biomarkers and the reliance on subjective endpoints, such as cognitive assessments, contribute to high placebo response rates and trial failures. Many patients struggle because of a lack of awareness of available trials or are hesitant to participate in data-intensive studies. Site saturation and high costs further complicate trial execution. These factors make neuroscience trials slower, more expensive, and more prone to failure than those in other therapeutic areas.
Traditional study designs with one-size-fits-all protocols, site-centric models, and passive patient outreach strategies with a lack of personalization are no longer sufficient. To overcome these hurdles, sponsors must embrace a new paradigm- one that draws on the proven successes of oncology and rare disease research to reshape the future of neuroscience trials.
What will carry us forward: Cross-Therapeutic Innovation- A Strategic Blueprint
Oncology trials have pioneered adaptive study designs, such as basket, umbrella, and platform trials, that allow for flexible testing of multiple hypotheses. Biomarker-driven targeting and data-driven recruitment have improved precision and efficiency, enabling faster enrollment and better outcomes. Rare disease trials excel in community involvement, where advocacy drives 2-3 (in our Parexel experience) times faster enrollment in engaged studies. We won’t fix this by scaling yesterday’s playbook- we need to tailor proven cross-therapeutic models to neuroscience and execute with discipline. Embracing cross-therapeutic innovation, here’s how we move forward faster and more confidently:
1) Design with adaptability and evidence
Adaptive and Bayesian approaches help us ask smarter questions earlier, stop sooner when signals aren’t there, and expand only when they are. Adapting other therapeutic areas’ models isn’t copy-paste—it’s tailoring. Hybrid models, blending oncology’s efficiency with rare disease empathy, are needed in neurology and psychiatry. Sponsors can adapt these cross-therapeutic models to the unique demands of neuroscience. For example, the use of Bayesian methods allows for real-time adjustments in response to variable endpoints. Basket trials can accommodate the heterogeneity of conditions, enabling more targeted and efficient testing. Real-world evidence can be used to refine inclusion and exclusion criteria, improving trial efficiency. Adaptation is not a shortcut; it safeguards patients and resources by stopping sooner when the answer is “no,” and expanding thoughtfully when it looks like “yes.”3, 4
2) Make protocols truly patient-guided
Patient-focused protocols aren’t just nice—they’re necessary. By involving patients in trial design, sponsors can create studies that are more convenient and less burdensome, with higher chances of reaching the market. Decentralized elements, flexible visit schedules, and remote monitoring improve both recruitment velocity and retention. Streamlining protocols and selecting high-performing sites can yield significant cost savings. Sponsors should reduce invasive procedures, align assessments with dosing schedules, and consider digital twin approaches to minimize sample size.
Patients aren’t data points—they’re people. Effective engagement goes beyond reminders—it’s about making patients feel seen and valued. Gamification, peer ambassadors, and personalized messaging foster a sense of connection and purpose. Digital platforms, social media outreach, and AI-driven matching tools can enhance engagement by focusing on what motivates patients- ease, education, and empathy. The informed consent process should be enhanced with multimedia tools and lay-language materials that improve comprehension and trust. Sponsors must also recognize the individuality and autonomy of participants. Inclusion criteria should reflect gender diversity, and assent materials should be tailored to different age groups. Regular communication throughout the trial reinforces commitment and transparency.
Patients and caregivers are partners. Involve them early before endpoints and schedules harden. Small shifts have outsized effects: align assessments to dosing windows; cluster procedures to reduce travel; offer hybrid or decentralized options where appropriate; and build caregiver needs into the plan. These choices directly influence retention, data completeness, and confidence in the signal.5, 6, 7, 8
3) Treat recruitment as a system, not a campaign
Overall, recruitment should be treated as an always-on system, not a campaign. Sponsors must invest in multi-channel outreach, AI-powered pre-screening, and real-time analytics. Feedback loops allow for dynamic optimization, ensuring that strategies remain effective and responsive. Hybrid models that combine virtual and in-person elements offer flexibility and scalability. Moreover, early engagement and transparent communication across stakeholders (patients, PIs, sites, sponsor, CRO, regulators) are critical to align around shared goals and incentives. When everyone rows in the same direction, trials move faster.
Site selection should be based on performance metrics, not just geography. And when it comes to geography, being more inclusive and involving ex-Europe and the Americas regions is the way to go now. Experienced investigators, accessible locations, and patient population density are key factors. Investing in site productivity technologies and training enhances operational success. Reducing non-enrolling sites by 50% can save $10–13 million in a Phase III trial.
Compensation and incentives play a vital role in reducing participation barriers. Reimbursing travel expenses, offering tokens of appreciation, and supporting caregivers acknowledge the real-life demands patients face. These measures and an always-on system approach improve retention, data quality, and speed while demonstrating respect for participants’ time and effort.
4) Scale digital measures and biomarkers
Objective digital measures can help us run cleaner, faster neuroscience trials. Digital signals- speech, gait, activity- used with imaging and simple blood tests make screening and follow-up more consistent and less subjective. Decide early how each measure will be used (eligibility, enrichment, endpoint, or safety) and how we will read it. When possible, link digital signals to imaging or blood markers and tie them to changes that matter in daily life. Share a simple validation plan- what is measured, how reliable it is, and what change is meaningful, and keep algorithm versions controlled. Offer device/connection support and include caregiver input so more people can take part. Pair digital measures with clear analytic plans and patient-focused onboarding. Train sites to interpret outputs, define thresholds that trigger action, and make data flows visible to investigators. Digital measures are not replacements for clinical judgment; they are instruments that help us see change earlier and more consistently. Done well, digital measures and biomarkers reduce noise and enable go/no-go decisions without adding burden.9, 10, 11
5) Plan for access from Day 1 with real-world evidence
An approval-only mindset is no longer enough. Payers, clinicians, and patients need to understand who benefits, how quickly, and with what impact on daily function in the long term. Build an evidence plan from Day 1: define the target patient profile early, map endpoints to outcomes that matter to patients and health systems, and use real-world evidence ethically and transparently to complement trial data and address questions randomized studies cannot answer alone.12, 13 Endpoint selection and interpretation remain significant challenges in neurology and psychiatry clinical trials due to subjectivity, self-reporting, heterogeneity, the placebo effect, meaningfulness, sensitivity, comorbidities, and inter-rater variability, among other factors. Establishing the value of a new product requires accurate, sensitive, and validated real-world endpoints, such as clinical outcome assessments (COAs), which, when incorporated into RCTs, can provide holistic, patient- and indication-relevant measurements of disease severity and progression. Regulators have accepted COAs as primary and secondary efficacy endpoints, and payers routinely scrutinize them to assess cost-effectiveness and real-world results.
Choosing optimal COAs—then collecting and analyzing the data with sufficient rigor for regulators and payers—can substantiate an unmet need. For example, schizophrenia’s cognitive symptoms often affect a patient’s ability to work, live independently, and navigate personal relationships. Yet, no schizophrenia therapies are approved to improve patients’ quality of life (QoL) by specifically mitigating cognitive symptoms.
An early practical real-world evidence plan that links trial endpoints to outcomes that matter to patients, clinicians, and payers provides the cornerstone for more efficient and successful neuroscience drug development.
Bottom line
Innovation in neuroscience trials does not require reinvention. It requires repurposing proven strategies. By adapting oncology and rare disease models to neuroscience trials, sponsors can overcome longstanding barriers and deliver better outcomes for patients and shareholders alike. The path forward is clear: design with empathy, execute with precision, and collaborate with purpose. Practically, that means sharper eligibility, staged evidence aligned to access, and recruitment run as a system—not a campaign.
In short, we will move faster by asking better questions earlier and building trials that people can realistically join and complete. The most durable acceleration will come from early alignment among biostatistics, operations, sites, and patient partners so that feasibility, ethics, and statistical power are negotiated together. When that happens, endpoints are practical, recruitment plans are built on real access to patients, and analytic choices anticipate payer questions- reducing protocol amendments and avoidable delays.
Trial success requires patient-guided discipline: stop early when the answer is no, expand only when the signal is credible, and communicate clearly with families and investigators about what the study asks and why it matters. That is how we honour patient time and move the science forward responsibly. It keeps patients at the center and decisions grounded in reproducible signals.
Finally, the future of neuroscience trials needs to be intelligent, inclusive, and interconnected. Artificial intelligence will drive predictive recruitment and protocol optimization. Real-world data will enhance trial design and execution. And global data harmonization and sharing will enable broader access and faster approvals of treatment. We need to stop reinventing the wheel—and start sharing the road. Sponsors who embrace these trends will lead the market in speed, quality, and cost-efficiency.
Contributing Experts