16 October 2026

Why CNS Clinical Trials Fail and How to Adapt

Why CNS Clinical Trials Fail: Addressing High Screen Failure Rates, High Attrition Rates, and Heterogeneity in Neurological Drug Development

Central nervous system (CNS) programs have a reputation problem, and it’s well-earned. Screen failure in CNS clinical trials runs at 57%, compared to 36.3% across other therapeutic areas, and disease heterogeneity often dilutes a treatment signal before a sponsor ever sees it, while attrition drains already-thin patient pools before and after randomization.

We recently led a roundtable on exactly this topic at hubXchange’s CNS Therapeutics Xchange in San Francisco, and this piece unpacks what came out of that conversation: why these three pressures persist, and what a more deliberate, adaptable approach to trial design looks like across neurodegenerative, movement disorders, and psychiatric programs.

Getting the Cutoff Right: Where Screen Failure Starts

Screen failure often starts with the wrong cutoff or the wrong test, not the wrong patient. Take Alzheimer’s disease as an example. Amyloid burden thresholds show the tension clearly:

Set the cutoff too high, and eligible patients become harder to find, screen failure climbs, and enrollment stretches out, without necessarily strengthening the eventual signal, since some elevated amyloid is common even in normal elderly patients.
Set it too low, and patients enter the trial with levels barely registering as pathological, leaving little room to demonstrate an effect.

The same tension shows up wherever any CNS trial relies on a biomarker, diagnostic threshold, or inclusion/exclusion criterion for enrollment. Getting it right takes both a sound patient recruitment strategy and careful biostatistical modeling.

Diagnostic rigor matters just as much. Where an objective marker exists, a practical middle ground has gained traction: a low-cost prescreen to flag likely-positive candidates, reserving the more expensive or invasive confirmatory test, positron emission tomography (PET) or cerebrospinal fluid (CSF) analysis, for those who screen positive. Where no biomarker exists yet, which is often the case in psychiatric trials, consistent screening depends more on rater training and structured diagnostic interviews across sites.

Why Heterogeneity Dilutes the Signal

Diluted signal often starts with diagnosis, not analysis. If the patient in front of you doesn’t actually have the condition a trial is designed to treat, no amount of downstream biomarker or statistical work can recover a clean signal.

That heterogeneity looks different across CNS programs:

In neurodegenerative disease, distinguishing early-stage disease from conditions that present similarly is often harder than clinical diagnosis alone can manage.
In movement disorders, genetic subtypes can carry meaningfully different progression rates and treatment responses.
In psychiatric indications, overlapping symptomatology across diagnoses means two patients meeting identical enrollment criteria can have different underlying conditions and end up with very different outcomes.

Some of that heterogeneity is genetic, some is phenotypic, and some comes down to comorbidities and concomitant medications, none of which show up cleanly on an enrollment form. Either way, a population that isn’t uniform enough dilutes the signal with patients who were never going to respond to a mechanism-specific therapy in the first place.

Stratifying by genetic or biomarker status early means you can plan for population differences instead of discovering them after the fact. This kind of enrichment, selecting or weighting enrollment around a patient’s baseline risk profile, lets your team stratify enrollment or analyze subgroups separately, rather than watching a differently-progressing subgroup quietly skew the results. But there’s a tradeoff. A more tightly stratified population produces a cleaner signal but sacrifices generalizability, saying less about how a drug performs in the broader patient population, so that balance is worth weighing case by case.

Trial design needs room to adapt, especially in CNS, where enrollment moves slowly, and populations are hard to characterize upfront. That means building in prespecified opportunities to adjust a trial once interim data comes in: dropping an underperforming arm, re-estimating sample size, or adjusting randomization ratios.

Two Kinds of CNS Trial Attrition

Attrition shows up in two different ways, and they need different fixes.

Design-driven attrition happens before ever reading the trial result. Common missteps can produce a result that looks like early failure when it’s really a design or measurement gap:

Treating biomarker and stratification strategy as a late addition rather than a workstream that starts at target validation and is progressively de-risked through early clinical development, locking in no later than Investigational New Drug (IND)-enabling and first-in-patient planning
Sizing early trials too small to reliably detect anything but a large effect, so a promising drug can read as “no effect” simply because the trial lacked the power to separate a real signal from noise
Selecting endpoints that move too slowly or too subjectively to show change within a short early-phase window, as cognitive and functional scales in neurodegenerative disease progress gradually, and rater-dependent scales in psychiatric and other CNS indications can vary across sites even when nothing has actually changed
Setting a visit schedule that doesn’t match how fast (or slowly) the disease or endpoint is expected to change, assessments spaced too far apart to catch a real signal, or too tightly packed to be practical for patients

Operational attrition happens after a patient enrolls, driven by friction rather than science.

Neurodegenerative patients often depend on caregivers for transport and support, movement disorder patients face their own mobility challenges getting to sites, and psychiatric and epilepsy trials often demand frequent, intensive visits. Assessment burden adds a second layer. Lengthy cognitive batteries and rating scales wear on patients, and raters need time and skill to administer them consistently. That demand on both sides, compounded by inconsistent training and site preparedness, can quietly undermine data quality, integrity, and retention.

The fixes look similar across indications: decentralized elements, home visits, flexible visit windows, remote or wearable assessment where validated, and structured rater training. Digital and wearable biomarkers are considerably more established in movement disorders, where gait and activity metrics map directly onto disease biology, so matching the right tool to the right indication matters as much as adopting one.

Building Toward a More Adaptable CNS Clinical Trial Strategy

None of this argues for slowing down. It argues that keeping clinical trial momentum means being deliberate earlier and specific to the indication. You need to calibrate patient recruitment thresholds against what the trial needs to prove, confirm diagnoses before assuming, treat biomarker and stratification strategy as an ongoing workstream, and design around the real operational demands of the population you’re studying.

Real-world data is a part of that toolkit too, particularly for rare neurogenetic and neuromuscular conditions where a fully powered, placebo-controlled trial isn’t always realistic. The FDA finalized guidance in 2023 on using real-world data (from registries, natural history studies, medical claims, and routine clinical practice) to inform trial design decisions for drug programs like site selection, enrollment assumptions, disease progression, and external comparison groups.

Well-characterized, well-diagnosed populations make trial data more trustworthy, and that trust compounds across a program. Designing an adaptable clinical trial strategy from the start — one that can calibrate, stratify, and adjust as real data comes in, and still meet the evidentiary standards regulators require for approval — is what actually gets a CNS program to a defensible readout.

If your program is wrestling with screen failure, attrition, or a heterogeneous population diluting your signal, talk to an expert at Avance Clinical. Our CNS Center of Excellence supports biopharmaceutical companies across Alzheimer’s, Parkinson’s, epilepsy, mood and anxiety disorders, psychosis, and rare neurogenetic and neuromuscular conditions, from early protocol design through regulatory preparation, trial execution, and beyond. The CNS team can help you evaluate inclusion and exclusion criteria for feasibility, align regulatory strategy with trial design early where possible, and expand seamlessly into the U.S. and other international markets through Avance Clinical’s GlobalReady framework.

About the Authors

Francesco Bibbiani, MD, CPI

Vice President & Therapeutic Area Head, CNS Center of Excellence

Marty Kraut Ph.D., PMP

Director of Operations, CNS Center of Excellence

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Why CNS Clinical Trials Fail and How to Adapt

Why CNS Clinical Trials Fail: Addressing High Screen Failure Rates, High Attrition Rates, and Heterogeneity in Neurological Drug Development