Blinded prospective evaluation of computer-based mechanistic schizophrenia disease model for predicting drug response

• Published in: PloS one Vol. 7; no. 12; p. e49732
• Main Authors: Geerts, Hugo, Spiros, Athan, Roberts, Patrick, Twyman, Roy, Alphs, Larry, Grace, Anthony A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14-12-2012; Public Library of Science (PLoS)
• Subjects: Acetylcholine; Affinity; Antipsychotic Agents - pharmacology; Antipsychotic Agents - therapeutic use; Antipsychotics; Biology; Central nervous system; Chemistry; Circuits; Clinical trials; Competition; Computer Simulation; Cortex; Diagnostic imaging; Dopamine; Dopamine D2 receptors; Drug discovery; Drug dosages; Drug therapy; Drugs; GABA; Genotypes; Glutamate; Human pathology; Humans; Legal liability; Liability; Mathematical models; Medical imaging; Medical research; Medicine; Mental disorders; Metabolites; Models, Neurological; Neostriatum; Neostriatum - drug effects; Neurophysiology; Norepinephrine; Olanzapine; Pharmacology; Physiological aspects; Physiology; Piperidines - pharmacology; Piperidines - therapeutic use; Positron emission; Positron emission tomography; Prognosis; Prospective Studies; Psychiatry; Psychotropic drugs; Pyridazines - pharmacology; Pyridazines - therapeutic use; Pyrimidinones - pharmacology; Pyrimidinones - therapeutic use; R&D; Research & development; Rodents; Schizophrenia; Schizophrenia - drug therapy; Serotonin; Social and Behavioral Sciences; Tomography; Treatment Outcome; γ-Aminobutyric acid; United States > US; New Jersey; Pennsylvania
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0049732

The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published 'Quantitative Systems Pharmacology' computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA) and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D(2) antagonist and ocaperidone, a very high affinity dopamine D(2) antagonist, using only pharmacology and human positron emission tomography (PET) imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS) total score and the higher extra-pyramidal symptom (EPS) liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development.