Document Detail


Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice.
MedLine Citation:
PMID:  24773369     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
AIM: To determine optimal sampling strategies to allow the calculation of clinical pharmacokinetic parameters for selected antipsychotic medicines using a pharmacometric approach.
METHODS: This study utilized previous population pharmacokinetic parameters of the antipsychotic medicines aripiprazole, clozapine, olanzapine, perphenazine, quetiapine, risperidone (including 9-OH risperidone) and ziprasidone. d-optimality was utilized to identify time points which accurately predicted the pharmacokinetic parameters (and expected error) of each drug at steady-state. A standard two stage population approach (STS) with MAP-Bayesian estimation was used to compare area under the concentration-time curves (AUC) generated from sparse optimal time points and rich extensive data. Monte Carlo Simulation (MCS) was used to simulate 1000 patients with population variability in pharmacokinetic parameters. Forward stepwise regression analysis was used to determine the most predictive time points of the AUC for each drug at steady-state.
RESULTS: Three optimal sampling times were identified for each antipsychotic medicine. For aripiprazole, clozapine, olanzapine, perphenazine, risperidone, 9-OH risperidone, quetiapine and ziprasidone the CV% of the apparent clearance using optimal sampling strategies were 19.5, 8.6, 9.5, 13.5, 12.9, 10.0, 16.0 and 10.7, respectively. Using the MCS and linear regression approach to predict AUC, the recommended sampling windows were 16.5-17.5 h, 10-11 h, 23-24 h, 19-20 h, 16.5-17.5 h, 22.5-23.5 h, 5-6 h and 5.5-6.5 h, respectively.
CONCLUSION: This analysis provides important sampling information for future population pharmacokinetic studies and clinical studies investigating the pharmacokinetics of antipsychotic medicines.
Authors:
Vidya Perera; Robert R Bies; Gary Mo; Michael J Dolton; Vaughan J Carr; Andrew J McLachlan; Richard O Day; Thomas M Polasek; Alan Forrest
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  British journal of clinical pharmacology     Volume:  78     ISSN:  1365-2125     ISO Abbreviation:  Br J Clin Pharmacol     Publication Date:  2014 Oct 
Date Detail:
Created Date:  2014-09-19     Completed Date:  -     Revised Date:  2014-12-09    
Medline Journal Info:
Nlm Unique ID:  7503323     Medline TA:  Br J Clin Pharmacol     Country:  England    
Other Details:
Languages:  eng     Pagination:  800-14     Citation Subset:  IM    
Copyright Information:
© 2014 The British Pharmacological Society.
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