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A Quantitative Systems Pharmacology Computer Model for Schizophrenia Efficacy and Extrapyramidal Side Effects
Author(s) -
Spiros Athan,
Roberts Patrick,
Geerts Hugo
Publication year - 2012
Publication title -
drug development research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.582
H-Index - 60
eISSN - 1098-2299
pISSN - 0272-4391
DOI - 10.1002/ddr.21008
Subject(s) - schizophrenia (object oriented programming) , extrapyramidal symptoms , neuroscience , drug discovery , medicine , disease , psychosis , psychology , pharmacology , psychiatry , bioinformatics , antipsychotic , biology
trategy, Management and Health Policy Enabling Technology, Genomics, Proteomics Preclinical Research Preclinical Development Toxicology, Formulation Drug Delivery, Pharmacokinetics Clinical Development Phases I‐III Regulatory, Quality, Manufacturing Postmarketing Phase IVDespite tremendous advances in understanding the neurobiology of schizophrenia, no real therapeutic breakthrough in terms of novel antipsychotics has been made since the serendipitous discovery of chlorpromazine. We describe a computer‐based mechanistic disease simulation model of biophysically realistic neurons that captures most of the subcortical neuromodulatory processes important in the pathophysiology of schizophrenia and calibrate this with a large retrospective clinical database for Positive and Negative Symptoms Scale in Schizophrenia ( PANSS total) and extrapyramidal symptoms ( EPS ) liability. Additionally we make this platform more actionable for practical use in central nervous system drug discovery by introducing a synaptic receptor competition model that accurately captures clinical target exposures. The model accounts for threefold more variance than the simple dopamine D 2 receptor occupancy rule and is also superior in a number of independent clinical data sets. As such, the model is a first step in a better understanding of the human neurobiology of schizophrenia. Using human pharmacology and a positron emission tomography target engagement study as input, the model can estimate a value for the clinical efficacy on PANSS total and EPS side effect liability for the clinical doses of a new investigative compound. This Quantitative Systems Pharmacology platform, by simulating the effect of co‐medications and genotypes in a clinical setting, represents a useful addition to psychiatric drug discovery efforts.