Original Research ARTICLE
Application of physiologically based pharmacokinetic (PBPK) modelling within a Bayesian framework to identify poor metabolizers of efavirenz (PM), using a test dose of efavirenz.
- 1Simcyp (United Kingdom), United Kingdom
- 2Pharmacy School, University of Manchester, United Kingdom
Poor metabolisers of CYP2B6 (PM) require a lower dose of efavirenz because of serious adverse reactions resulting from the higher plasma concentrations associated with a standard dose. Treatment discontinuation is a common consequence in patients experiencing these adverse reactions. Such patients benefit from appropriate dose reduction, where efficacy can be achieved without the serious adverse reactions. PMs are usually identified by genotyping. However, in countries with limited resources genotyping is unaffordable. Alternative cost-effective methods of identifying a PM will be highly beneficial. This study was designed to determine whether a plasma concentration corresponding to a 600mg test dose of efavirenz can be used to identify a PM. A physiologically based pharmacokinetic (PBPK) model was used to simulate the concentration-time profiles of a 600 mg dose of efavirenz in extensive metabolizers (EM), intermediate metabolizers (IM) and PM of CYP2B6. Simulated concentration-time data were used in a Bayesian framework to determine the probability of identifying a PM, based on plasma concentrations of efavirenz at a specific collection time. Results indicated that there was a high likelihood of differentiating a PM from other phenotypes by using a 24 hr plasma concentration. The probability of correctly identifying a PM phenotype was 0.82 (true positive), while the probability of not identifying any other phenotype as a PM (false positive) was 0.87. A plasma concentration >1000 ng/mL at 24 hours post-dose is likely to be from a PM. Further verification of these findings using clinical studies is recommended.
Keywords: slow metabolisers of efavirenz, adverse effects of efavirenz, identifying CYP2B6 PMs, PBPK modelling within a Bayesian Framework, test dose of efavirenz
Received: 22 Jan 2018;
Accepted: 06 Mar 2018.
Edited by:José Das Neves, i3S, Instituto de Investigação e Inovação em Saúde, Portugal
Reviewed by:Kathrin Klein, Dr. Margarete Fischer-Bosch Institut für Klinische Pharmakologie (IKP), Germany
Bernd Rosenkranz, Stellenbosch University, South Africa
Copyright: © 2018 Chetty, Cain, Wedagedera, Jamei and Rostami-Hodjegan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Manoranjenni Chetty, Simcyp (United Kingdom), Blades Enterprise Centre, John Street, Sheffield, United Kingdom, email@example.com