Yomna Nassar (1,2), Gerd Mikus (3), Franziska Kluwe (1,2), Wilhelm Huisinga (4), Robin Michelet (1), and Charlotte Kloft (1)
(1) Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Germany, (2) Graduate Research Training program PharMetrX, Germany, (3) Department of Clinical Pharmacology and Pharmacoepidemiology University Hospital Heidelberg, Heidelberg, Germany, (4) Institute of Mathematics, University of Potsdam, Germany
Objectives: Cytochrome P450 (CYP) is a family of more than 50 enzymes responsible for the metabolism of the majority of drugs and other xenobiotic compounds. CYP3A, the most abundant subfamily, is mainly expressed in the liver and small intestine, and is responsible for the metabolism of ~50% of marketed drugs. Pathological conditions or concomitant medications known to induce or inhibit CYP3A activity can alter exposure to drugs metabolised by CYP3A [1]. Therefore, to predict the extent of change in exposure of these drugs, it is important to quantify CYP3A activity in healthy individuals.
Midazolam, a short acting sedative and hypnotic agent, is almost completely metabolised by CYP3A [2]. Therefore, its metabolic clearance following intravenous (i.v.) administration can be used to reliably quantify the in vivo activity of hepatic CYP3A with non-pharmacological microgram dosing [3].
The objective of this work was to use the nonlinear mixed-effects modelling approach (NLMEM) to (1) develop a population pharmacokinetic model for midazolam (MDZ) and its metabolite 1-hydroxymidazolam (MDZ_OH) following intravenous administration in healthy individuals and subsequently to (2) quantify hepatic CYP3A activity and other non-CYP3A related clearances to ultimately assess the impact of altered CYP3A activity on drug exposure.
Methods: The dataset included 8 healthy individuals who were administered an i.v. MDZ bolus dose [8280-18700 pmol (2.7-6.1 µg)] followed by an i.v. infusion [6140-1350 pmol/h (2-4.4 µg/h)] for a total duration of 10-36 hours to achieve a target concentration of 100 pg/mL (EudraCT No: 2013-004869-14). Durations of infusion were truncated to 10 h for a uniform and closer look at the densely sampled period. A total of 516 observations [average: 32 observations/individual/analyte, range: 9-40 observations] were equally divided between MDZ and MDZ_OH. MDZ concentrations ranged from 87 to 437 pM while MDZ_OH concentrations ranged from 1.6 to 70.8 pM. Plasma MDZ and MDZ_OH were quantified by a validated method [3], with lower limits of quantification of 0.285 and 0.822 pM, respectively [3].
Model development was performed using NLMEM approach in NONMEM®7.4.3 [4] together with PsN 2.9.4 [5]. First-order conditional estimation with interaction was employed for parameter estimation. Model adequacy was assessed considering plausibility and precision of parameter estimates, and standard goodness-of-fit plots. Model evaluation was performed using visual predictive checks (VPC) (n = 200) and bootstrap (n = 1000). Graphical and exploratory analyses were performed in R® 3.5.3 [6] and RStudio 1.1.463 [7], using the Xpose 4.6.1. package [5].
Results: The pharmacokinetics of MDZ and MDZ_OH were well described using a 1-compartment pharmacokinetic model for each analyte, which was parameterised in terms of clearance and volume of distribution. Based on the quantified total MDZ clearance and the fixed value of the fraction of MDZ metabolised (FMET=0.44) [3], different clearances could be derived. CYP3A clearance for MDZ was calculated to be 20.7 L/h [CL·FMET], other (non-CYP3A) clearances were 26.32 L/h [CL·(1-FMET)] summing up to a total MDZ clearance (CL) of 47 L/h. MDZ volume of distribution (V1) was 48 L and its calculated half-life was 0.707 h (~42 min). Whereas for MDZ_OH, total clearance (CL_met) and volume of distribution (V2) were 176 L/h and 99.2 L, respectively and the calculated half-life was 0.3906 h (~23 min).
Interindividual variability was 9.2% and 31.6% CV for CL and CL_met, respectively. Residual variability was best described with a proportional component and was quantified to be 16.6% for MDZ and 20.5% for MDZ_OH. All parameters were estimated with good precision [relative standard error (RSE) <21%]. The VPC well captured the observed concentrations of the 10th, 50th, and 90th percentiles for both MDZ and MDZ_OH. Bootstrap-estimated RSE values (Range: 0.04-35.7%) supported the parameter estimates’ precision and accuracy.
Conclusions: A NLME model of microdosed MDZ was successfully developed to characterise the pharmacokinetics of MDZ and MDZ_OH in healthy individuals. Hepatic CYP3A activity and other non-CYP3A related clearances were successfully quantified and contributed to 44% and 56% of MDZ clearances, respectively. This model will be further used to quantify hepatic CYP3A activities under different perpetrator conditions, hence assessing the time dependent effects on CYP3A activities.
References:
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Reference: PAGE () Abstr 9288 [www.page-meeting.org/?abstract=9288]
Poster: Drug/Disease Modelling - Other Topics