Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges

Abstract

The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross-disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior.

Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing

“…The CNS drug development pipeline should consider the following factors: quantitative and validated biomarkers, clinical endpoints, complex PK/PD relationships, and the complex interactions of different brain circuits. 225 To address these issues, other approaches such as quantitative systems pharmacology (QSP) are emerging as new computational strategies in CNS drug discovery. QSP, which combines systems biology and PK/PD, offers a mechanism-based computer model of relevant neuronal circuits for CNS diseases.…”

“…QSP, which combines systems biology and PK/PD, offers a mechanism-based computer model of relevant neuronal circuits for CNS diseases. 225,226 It can be used for evaluating drug effects and optimizing the design of clinical trials. Collectively, the computational strategies above show promise in exploiting multi-omics data in pursuit of AD drug repurposing.…”

The Microbiome and the Gut‐Liver‐Brain Axis for Central Nervous System Clinical Pharmacology: Challenges in Specifying and Integrating In Vitro and In Silico Models

“…A systems approach is necessary for understanding and treating CNS diseases, and the merging of pharmacology with systems biology has created the field of quantitative systems pharmacology. 4,5,105 The problems only become harder with the need to incorporate the microbiome. Fritz et al 106 review the current status of in silico models.…”

“…The Microbiome and the Gut-Liver-Brain Axis for Central Nervous System Clinical Pharmacology: Challenges in Specifying and Integrating In Vitro and In Silico Models Kyle G. Hawkins 1 , Caleb Casolaro 2 , Jacquelyn A. Brown 1,3 , David A. Edwards 4 and John P. Wikswo 1,2,3,5, *…”

“…Organson-chips (OoCs), that is, 2D and 3D human tissue constructs typically grown in perfused, microfluidic devices using primary, tissue-resident adult stem cells, or induced pluripotent stem cells (iPSCs) to create microphysiological systems (MPS), 3,4 are one of the newest tool sets being introduced into clinical pharmacology and toxicology. 5,6 Although they are increasingly recognized as being able to recapitulate enough tissue or organ functions to recapitulate a functional unit and serve as useful in vitro human models for quantitative systems pharmacology, 4 their full potential for studying host-microbiome interactions has yet to be realized. This review first examines microbiota-host interactions, exogenously driven microbiota composition perturbations, and treatment outcomes that depend upon microbiota composition, all from the perspective of clinical pharmacology.…”