Literature DB >> 19387434

Modeling and simulation of the time course of asenapine exposure response and dropout patterns in acute schizophrenia.

L E Friberg1, R de Greef, T Kerbusch, M O Karlsson.   

Abstract

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.

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Year:  2009        PMID: 19387434     DOI: 10.1038/clpt.2009.44

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  28 in total

1.  Modelling of pain intensity and informative dropout in a dental pain model after naproxcinod, naproxen and placebo administration.

Authors:  Marcus A Björnsson; Ulrika S H Simonsson
Journal:  Br J Clin Pharmacol       Date:  2011-06       Impact factor: 4.335

2.  Dopamine D2 occupancy as a biomarker for antipsychotics: quantifying the relationship with efficacy and extrapyramidal symptoms.

Authors:  Rik de Greef; Alan Maloney; Per Olsson-Gisleskog; Joep Schoemaker; John Panagides
Journal:  AAPS J       Date:  2010-12-24       Impact factor: 4.009

3.  Disease progress and response to treatment as predictors of survival, disability, cognitive impairment and depression in Parkinson's disease.

Authors:  Thuy C Vu; John G Nutt; Nicholas H G Holford
Journal:  Br J Clin Pharmacol       Date:  2012-08       Impact factor: 4.335

Review 4.  Evaluation of the clinical efficacy of asenapine in schizophrenia.

Authors:  Arpi Minassian; Jared W Young
Journal:  Expert Opin Pharmacother       Date:  2010-08       Impact factor: 3.889

5.  Application of a hazard-based visual predictive check to evaluate parametric hazard models.

Authors:  Yeamin Huh; Matthew M Hutmacher
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-11-13       Impact factor: 2.745

Review 6.  Asenapine: A Review in Schizophrenia.

Authors:  Greg L Plosker; Emma D Deeks
Journal:  CNS Drugs       Date:  2016-07       Impact factor: 5.749

7.  Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models.

Authors:  Martin Bergstrand; Andrew C Hooker; Johan E Wallin; Mats O Karlsson
Journal:  AAPS J       Date:  2011-02-08       Impact factor: 4.009

8.  Structural models describing placebo treatment effects in schizophrenia and other neuropsychiatric disorders.

Authors:  Venkatesh Pilla Reddy; Magdalena Kozielska; Martin Johnson; An Vermeulen; Rik de Greef; Jing Liu; Geny M M Groothuis; Meindert Danhof; Johannes H Proost
Journal:  Clin Pharmacokinet       Date:  2011-07       Impact factor: 6.447

9.  Performance of nonlinear mixed effects models in the presence of informative dropout.

Authors:  Marcus A Björnsson; Lena E Friberg; Ulrika S H Simonsson
Journal:  AAPS J       Date:  2014-11-25       Impact factor: 4.009

10.  Development of a placebo effect model combined with a dropout model for bipolar disorder.

Authors:  Wan Sun; Thomas P Laughren; Hao Zhu; Guenther Hochhaus; Yaning Wang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-03-02       Impact factor: 2.745

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