Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies

Abstract

The development and application of quantitative systems pharmacology models in neuroscience have been modest relative to other fields, such as oncology and immunology, which may reflect the complexity of the brain. Technological and methodological advancements have enhanced the quantitative understanding of brain physiology and pathophysiology and the effects of pharmacological interventions. To maximize the knowledge gained from these novel data types, pharmacometrics modelers may need to expand their toolbox to include additional mathematical and statistical frameworks. A session was held at the 10th annual American Conference on Pharmacometrics (ACoP10) to highlight several recent advancements in quantitative and systems neuroscience. In this mini-review, we provide a brief overview of technological and methodological advancements in the neuroscience therapeutic area that were discussed during the session and how these can be leveraged with quantitative systems pharmacology modeling to enhance our understanding of neurological diseases. Microphysiological systems using human induced pluripotent stem cells (IPSCs), digital biomarkers, and large-scale imaging offer more clinically relevant experimental datasets, enhanced granularity, and a plethora of data to potentially improve the preclinical-to-clinical translation of therapeutics. Network neuroscience methodologies combined with quantitative systems models of neurodegenerative disease could help bridge the gap between cellular and molecular alterations and clinical end points through the integration of information on neural connectomics. Additional topics, such as the neuroimmune system, microbiome, single-cell transcriptomic technologies, and digital device biomarkers, are discussed in brief.

FIGURE 1

Select methodologies, technologies, and areas of research in neuroscience that can be leveraged and incorporated in Quantitative Systems Pharmacology modeling workflows to enhance the quantitative understanding of pathophysiological processes in neurological disease and therapeutic effects of pharmacological treatment strategies

FIGURE 2

Select methodologies and technologies that provides pharmacological and pathophysiological information across various levels of neurobiological organization and can be implemented across several stages of the drug discovery and development process. Each level contains select modeling approaches that are appropriately suited to describe data obtained from the experimental methodologies listed in parentheses. ABM, agent‐based modeling; EEG, electroencephalography; fMRI, functional magnetic resonance imaging; ML, machine learning; MPS, microphysiological system; ODEs, ordinary differential equations