Markov model for characterizing neuropsychologic impairment and Monte Carlo simulation for optimizing efavirenz therapy
The study was undertaken to develop a pharmacokinetic‐pharmacodynamic model to characterize efavirenz‐induced neuropsychologic impairment, given preexistent impairment, which can be used for the optimization of efavirenz therapy via Monte Carlo simulations. The modeling was performed with NONMEM 7.2...
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Veröffentlicht in: | Journal of clinical pharmacology 2015-11, Vol.55 (11), p.1229-1235 |
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Sprache: | eng |
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Zusammenfassung: | The study was undertaken to develop a pharmacokinetic‐pharmacodynamic model to characterize efavirenz‐induced neuropsychologic impairment, given preexistent impairment, which can be used for the optimization of efavirenz therapy via Monte Carlo simulations. The modeling was performed with NONMEM 7.2. A 1‐compartment pharmacokinetic model was fitted to efavirenz concentration data from 196 Ugandan patients treated with a 600‐mg daily efavirenz dose. Pharmacokinetic parameters and area under the curve (AUC) were derived. Neuropsychologic evaluation of the patients was done at baseline and in week 2 of antiretroviral therapy. A discrete‐time 2‐state first‐order Markov model was developed to describe neuropsychologic impairment. Efavirenz AUC, day 3 efavirenz trough concentration, and female sex increased the probability (P01) of neuropsychologic impairment. Efavirenz oral clearance (CL/F) increased the probability (P10) of resolution of preexistent neuropsychologic impairment. The predictive performance of the reduced (final) model, given the data, incorporating AUC on P01and CL /F on P10, showed that the model adequately characterized the neuropsychologic impairment observed with efavirenz therapy. Simulations with the developed model predicted a 7% overall reduction in neuropsychologic impairment probability at 450 mg of efavirenz. We recommend a reduction in efavirenz dose from 600 to 450 mg, because the 450‐mg dose has been shown to produce sustained antiretroviral efficacy. |
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ISSN: | 0091-2700 1552-4604 |
DOI: | 10.1002/jcph.533 |