Successful clinical development of therapeutics in neurology and psychiatry is challenging due to the complexity of the brain, the lack of validated surrogate markers and the nature of clinical assessments. On the other hand, tremendous advances have been made in unraveling the neurophysiology of the human brain thanks to technical developments in noninvasive biomarkers in both healthy and pathological conditions.Quantitative systems pharmacology (QSP) aims to integrate this increasing knowledge into a mechanistic model of key biological processes that drive clinical phenotypes with the objective to support research and development of successful therapies. This chapter describes both modeling of molecular pathways resulting in measurable biomarker changes, similar to modeling in other indications, as well as extrapolating in a mechanistic way these biomarker outcomes to predict changes in relevant functional clinical scales.Simulating the effect of therapeutic interventions on clinical scales uses the modeling methodology of computational neurosciences, which is based on the premise that human behavior is driven by firing activity of specific neuronal networks. While driven by pathology, the clinical behavior can also be influenced by various medications and common genotype variants. To address this occurrence, computational neuropharmacology QSP models can be developed and, in principle, applied as virtual twins, which are in silico clones of real patients.Overall, central nervous system (CNS) QSP is an important additional tool for supporting research and development from the preclinical stage to post-marketing studies and clinical practice. Overall, CNS QSP is an important additional tool for supporting research and development from the preclinical stage to post-marketing studies and clinical practice.