Sources of interindividual variability in IVIVE of clearance: an investigation into the prediction of benzodiazepine clearance using a mechanistic population-based pharmacokinetic model

Abstract

1. Prediction of metabolic clearance in extreme individuals rather than the ‘average human’ is becoming an attractive tool within the pharmaceutical industry.

2. The current study involved prediction of variability in metabolic clearance for alprazolam, triazolam and midazolam with emphasis on the following factors: first, evaluation of clearance prediction accuracy using intrinsic clearance (CL_int) data from in vitro metabolic data and back-calculation from in vivo clearance data. Second, the sensitivity of predicted in vivo variability to changes in variability for physiological parameters (e.g. liver weight, haematocrit, CYP3A abundance). Finally, reported estimates of variability in hepatic CYP3A4 abundance (coefficient of variation (CV) 95%) were refined by separating experimental from interindividual variability using a repeat measurement protocol in 52 human liver samples.

3. Using in vitro metabolic data, predicted clearances were within 2-fold of observed for triazolam and midazolam. Clearance of alprazolam was overpredicted by 2.0- to 3.7-fold. Use of in vivo CL_int values improved prediction of intravenous clearance to within 2-fold of observed for all drugs.

4. Initially, the variability in clearance was overestimated for all drugs (by 1.8- to 3.6-fold). Use of a reduced hepatic CYP3A4 CV of 41%, representative of interindividual variability alone improved predictions of variability in clearance for all drugs to within 2-fold of observed.

Keywords::

• CYP3A
• abundance
• MPPGL
• alprazolam
• triazolam
• midazolam

Acknowledgements

We thank James Kay for his assistance with the preparation of this manuscript.

Declaration of interest

The authors report no conflicts of interest.