Indications of success: Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development

Abstract

Despite large unmet medical needs in the field for several decades, CNS drug discovery and development has been largely unsuccessful. Biomarkers, particularly those utilizing neuroimaging, have played important roles in aiding CNS drug development, including dosing determination of investigational new drugs (INDs). A recent working group was organized jointly by CINP and Japanese Society of Neuropsychopharmacology (JSNP) to discuss the utility of biomarkers as tools to overcome issues of CNS drug development.The consensus statement from the working group aimed at creating more nuanced criteria for employing biomarkers as tools to overcome issues surrounding CNS drug development. To accomplish this, a reverse engineering approach was adopted, in which criteria for the utilization of biomarkers were created in response to current challenges in the processes of drug discovery and development for CNS disorders. Based on this analysis, we propose a new paradigm containing 5 distinct tiers to further clarify the use of biomarkers and establish new strategies for decision-making in the context of CNS drug development. Specifically, we discuss more rational ways to incorporate biomarker data to determine optimal dosing for INDs with novel mechanisms and targets, and propose additional categorization criteria to further the use of biomarkers in patient stratification and clinical efficacy prediction. Finally, we propose validation and development of new neuroimaging biomarkers through public-private partnerships to further facilitate drug discovery and development for CNS disorders.

Tourette syndrome research highlights from 2017

“…Medication. A group of international experts provided a status report and recommendations for using brain imaging for the rational development of novel psychopharmacological interventions ( Suhara et al , 2017 ). As an example, a fascinating study in pediatric ADHD showed that fMRI response to a cognitive task (Go/No-Go) strongly predicted better clinical response to methylphenidate than to atomoxetine ( Schulz et al , 2017 ).…”

Prediction of a clinically effective dose of THY1773, a novel V1Breceptor antagonist, based on preclinical data

“…The development of drugs for central nervous system (CNS) diseases is challenging relative to other therapeutic areas (Harrison, 2016; Suhara et al., 2017). Modeling and simulation technology has been used widely as an initiative to overcome the difficulty and to improve success rates of drug discovery and development (Visser, De Alwis, Kerbusch, Stone, & Allerheiligen, 2014).…”

“…For the efficacy prediction, appropriate translation of preclinical dose‐efficacy findings to human is critical. A target engaging biomarker, such as receptor occupancy (RO), which correlates with efficacy, plays an important role for this translation (Suhara et al., 2017). Establishing an appropriate quantitative model that links PK and target engaging biomarker dynamics is important for the determination of a dose that is predicted to be clinically effective with confidence.…”

Enhancing Clinical Trials Through Synergistic Gamma Power Analysis

“…The critical need for new and more useful biomarkers in neuropsychiatric disorders has also been well documented in the literature (56). The use of evoked gamma for biomarker-based stratification may be useful for a plethora of other neuropsychiatric disorders that display altered evoked gamma.…”