Use of biomarkers in neuropsychiatric clinical trials: a landscape analysis

Introduction

Biomarkers are increasingly promoted as key enablers of precision neuropsychiatry, with the potential to reduce biological heterogeneity, improve patient stratification, and enhance translational efficiency in clinical development [1]. Major initiatives and biomarker‑informed trials have underscored the limitations of symptom‑based diagnostic categories and the need for biologically grounded trial designs. However, the extent to which biomarkers are meaningfully integrated into interventional neuropsychiatric trials beyond exploratory use remains uncertain. Our hypothesis is that the use of biomarkers is non‑homogeneous across different study phases and neuropsychiatric indications.

Methods

Interventional clinical trials in neuropsychiatric indications registered from 2010 onwards were identified using Citeline|Trialtrove. Observational studies, disease registries, expanded access programmes, and compassionate use protocols were excluded. A curated dataset of 108 biomarker‑enabled interventional trials was analyzed. Trials were characterized by development phase, indication, sponsor type, and geographic region. Biomarkers were classified by functional role (diagnostic, predictive, prognostic, pharmacodynamic/target engagement, safety, exploratory), trial integration (patient selection/enrichment, stratification, endpoint, supportive measure), and modality (neurophysiological, imaging, molecular, genetic, digital, behavioral). Microsoft 365 Copilot was used for text editing and formatting support only.

Results

Biomarkers were incorporated across all development phases, with greatest representation in early and mid‑phase trials. Phase I studies primarily employed pharmacodynamic and target‑engagement biomarkers, commonly using neurophysiological measures, neuroimaging, or circulating molecular markers to support mechanistic validation. Phase II trials showed the broadest diversity of biomarker applications, particularly predictive and enrichment strategies to define biologically informed subpopulations. In contrast, Phase III trials were less frequently biomarker‑enabled and rarely used biomarkers as primary decision‑making endpoints. Across indications, mood disorders and autism spectrum disorder accounted for the largest share of biomarker‑enabled trials. Schizophrenia and post‑traumatic stress disorder trials more frequently incorporated multimodal biomarker strategies combining neurophysiological, cognitive, and molecular or inflammatory measures, whereas autism spectrum disorder studies more commonly relied on peripheral biological and behavioral biomarkers. Neurophysiological, blood‑based molecular, and neuroimaging biomarkers predominated overall, while genetic and digital biomarkers were less consistently integrated and rarely used as sole selection criteria.

Biomarker role / integration	Characteristics observed in trial listings
Pharmacodynamic / target engagement	Predominant in Phase I trials; commonly EEG, neuroimaging, and circulating molecular markers used for mechanistic validation
Predictive / enrichment biomarkers	Most frequently applied in Phase II trials to define biologically informed subpopulations
Diagnostic / prognostic biomarkers	Used variably across phases, mainly for stratification or supportive analyses
Multimodal biomarker strategies	More common in schizophrenia and PTSD trials, combining neurophysiology, cognition, and molecular or inflammatory markers
Late phase implementation	Limited representation in Phase III trials; rarely used as primary decision making or registrational endpoints

Conclusions

Biomarkers are widely applied in exploratory neuropsychiatric drug development, but their integration remains uneven across development phases and indications. These patterns highlight a persistent translational gap between biomarker exploration and late‑stage, registration‑relevant implementation. Greater standardization, prospective validation, and indication‑appropriate biomarker strategies may be required to realize the full promise of precision psychiatry in neuropsychiatric drug development [2].

References

1. Insel TR, Cuthbert BN, Garvey M, Heinssen R, Pine DS, Quinn K, Sanislow C, Wang P. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. American Journal of Psychiatry. 2010;167(7):748–751.
2. Woo CW, Chang LJ, Lindquist MA, Wager TD. Building better biomarkers: brain models in translational neuroimaging. Nature Neuroscience. 2017;20(3):365–377.