Design-driven foresight in CNS Drug Development: Bridging the valley of death

Key Takeaways: 

The Perils of Translation 

The development of new therapeutics for the central nervous system (CNS) remains one of the greatest challenges in pharmacology, with a success rate of less than 25% from Phase I to market (Astute Analytica, 2025). While many failures are attributed to the inherent complexity of the brain, a significant number of high-potential, high-risk drug candidates fail in late-stage trials due to a more subtle issue: inadequate methodological and translational refinement in early-phase protocol design. By effect, this limits the successful extension to later-stage application and successful validation (National Academies of Sciences, Engineering, and Medicine, 2016).  

This report provides a condensed review and analysis of common causes of translational errors, contributing to 85% of CNS trials (Astute Analytica, 2025) never making it to market. Here, we give an example followed by a discussion on how a promising efficacy signal—often derived from a simple standardised neurophysiological biomarker in an early trial—when incorrectly or uncritically integrated into protocol design, can in fact become a costly false positive. 

The same biomarker data that sparks early excitement fails to translate replicability to later phase trials. By then, the “valley of death” has claimed another programme, extinguishing the promise of an otherwise high-potential drug. The good news: these losses are not inevitable. 

Translational Biomarkers 

Given the challenges of CNS drug development—such as the blood–brain barrier and unreliable animal models—translational biomarkers have become indispensable. Tools like pharmaco-EEG and pharmaco-TMS offer non-invasive, real-time insights into how drugs act on brain function (Gefferie et al. 2023). 

In schizophrenia, EEG biomarkers such as Mismatch Negativity (MMN) and Auditory Steady-State Response (ASSR) are frequently used to track cognitive pathway modulation (Schultheis et al. 2022). Similarly, pharmaco-TMS allows direct assessment of drug effects on cortical excitability and connectivity in vivo (Ziemann 2013). 

Yet these tools are often underused in early-phase design, specifically for Phase I - when they are most valuable. A clean, statistically significant signal in a small, tightly controlled trial can easily dissolve into noise when scaled up to a heterogeneous, multi-site later phase trial. 

When early protocols lack careful design exploration and expert oversight, methodological artefacts may masquerade as efficacy. These misleading signals then drive costly later phase programmes destined to collapse once the hidden flaws of earlier protocols surface (Scannelland Bosley 2016). 

When designing the first-in-human study for a novel drug target or mechanism of action, early signals of success beyond animal models can be exhilarating. The natural impulse is to take these results and move quickly to the next phase. Yet when rapid “baton turnover” becomes the priority, thoughtful protocol design may be viewed as an unnecessary delay at a moment when momentum feels essential. Rigorous design processes do not impede progress; rather, they facilitate smoother transitions and enhance the likelihood of successful outcomes or indicate the potential of further investment being unfruitful (Simbec-Orion, 2025). 

Exploring your Trial Design  

A recent study showed how seemingly small, low-effort design choices can prove invaluable when navigating the complex hurdles of later phase approvals (Rocchi et al. 2025). Rocchi et al. applied a novel use of pharmaco-TMS to investigate VGSC-blocking medications. In the crossover study, thirteen healthy adults received single doses of carbamazepine, lacosamide, or placebo. TMS was then used to assess changes in resting motor threshold and strength–duration properties—specifically rheobase and the strength–duration time constant (SDTC)—as indices of VGSC function. 

 The results showed distinct drug effects: 

Without the TMS component, validation at this stage would have relied solely on single motor threshold, which wouldn’t be able to distinguish between the two drugs. Here lies the strategic value of thoughtful, low-effort design: incorporating specific TMS measures provided deeper insights into mechanisms of action in vivo without compromising study integrity. This approach created a more robust foundation for extending the trial. By including additional biomarkers—SDTC, rheobase estimates, and resting motor threshold (RMT)—the research team strengthened the dimensionality of all future analyses, ensuring that subsequentbdata interpretation, whether in MATLAB, ANOVA, or other frameworks, rests on three-dimensional rather than two-dimensional markers. 

These findings not only deepened understanding of VGSC-blocking medication interactions in the human cortex but also highlighted the value of incorporating targeted TMS measures. Often overlooked in single-pulse approaches, such methods provide powerful adjuncts for both drug development and patient monitoring. More broadly, strength–duration metrics offer a valuable way to probe drug-specific VGSC interactions and support their continued use as mechanistic markers in human neurophysiology (Agbo et al. 2023, Bhattacharya et al. 2025). 

Reflections on the Value of Design Adaptability  

The TMS–electromyography (EMG) approach effectively probes axonal excitability in the motor cortex, but its spatial scope is limited. For drugs targeting non-motor systems, the development of equivalent TMS–EEG protocols extend assessments into non-motor regions, enabling the study of region-specific pathophysiology and pharmacological responses—for example, in focal epilepsies (Melus et al. 2025). Prior work demonstrating pulse-width sensitivity of TMS-evoked EEG supports this approach, and such measures should be integrated into Phase I study designs (Helling et al. 2022). 

The Science Behind: Our Role in Smarter Trial Design  

The CNS “valley of death” often happens not because of biology, but because of design choices. By building in better biomarkers, thoughtful protocol adjustments, and flexible trial designs early on, teams can turn that gap into a pathway toward clinical success. 

If you are preparing for an IND-enabling or Phase I trial, now is the time to integrate innovative design strategies. Thoughtful planning at this stage can prevent costly failures later and maximise the chances of long-term success. 

Our services and expert consultancy help bridge these gaps. With extensive experience in supporting high-potential, high-risk drug programmes, we align the three critical elements needed to overcome the valley of death: innovative protocol design, expert guidance, and adaptability in defining target populations. By embedding these elements into IND and proof-of-concept trials, we generate a robust foundation of data. This ensures that when your programme expands into later phases, it has the resilience to cross the valley of death—rather than fall into it. 

This schematic illustrates the process of crossing the “valley of death” in CNS drug development. Academia often begins with a novel drug target and the ambition to move into first-in-human (FIH) trials. However, at this stage, the target population, regulatory approval pathway, and drug mechanism are often misaligned. Without careful integration, these gaps—combined with an over reliance on narrow, two-dimensional measures—can cause promising candidates to fail before they progress through the clinical pipeline.

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