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Modeling and Simulation of the Time Course of Asenapine Exposure Response and Dropout Patterns in Acute Schizophrenia
Author(s) -
Friberg LE,
Greef R,
Kerbusch T,
Karlsson MO
Publication year - 2009
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1038/clpt.2009.44
Subject(s) - asenapine , placebo , pharmacodynamics , logistic regression , dropout (neural networks) , positive and negative syndrome scale , post hoc analysis , schizophrenia (object oriented programming) , medicine , clinical trial , psychology , pharmacokinetics , psychiatry , antipsychotic , psychosis , computer science , alternative medicine , pathology , machine learning
Modeling and simulation were utilized to characterize the efficacy dose response of sublingual asenapine in patients with schizophrenia and to understand the outcomes of six placebo‐controlled trials in which placebo responses and dropout rates varied. The time course of total Positive and Negative Syndrome Scale (PANSS) scores was characterized for placebo and asenapine treatments in a pharmacokinetic–pharmacodynamic model in which the asenapine effect was described by an E max model, increasing linearly over the 6‐week study period. A logistic regression model described the time course of dropouts, with previous PANSS value being the most important predictor. The last observation carried forward (LOCF) time courses were well described in simulations from the combined PANSS + dropout model. The observed trial outcomes were successfully predicted for all the placebo arms and the majority of the treatment arms. Although simulations indicated that the post hoc probability of success of the performed trials was low to moderate, these analyses demonstrated that 5 and 10 mg twice‐daily (b.i.d.) doses of asenapine have similar efficacy. Clinical Pharmacology & Therapeutics (2009); 86 , 1, 84–91 doi: 10.1038/clpt.2009.44