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

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

Scaling factors for the extrapolation of in vivo metabolic drug clearance from in vitro data: reaching a consensus on values of human microsomal protein and hepatocellularity per gram of liver.

Reported predictions of human in vivo hepatic clearance from in vitro data have used a variety of values for the scaling factors human microsomal protein (MPPGL) and hepatocellularity (HPGL) per gram of liver, generally with no consideration of the extent of their inter-individual variability. We have collated and analysed data from a number of sources, to provide weighted meangeo values of human MPPGL and HPGL of 32 mg g-1 (95% Confidence Interval (CI); 29-34 mg.g-1) and 99x10(6) cells.g-1 (95% CI; 74-131 mg.g-1), respectively. Although inter-individual variability in values of MPPGL and HPGL was statistically significant, gender, smoking or alcohol consumption could not be detected as significant covariates by multiple linear regression. However, there was a weak but statistically significant inverse relationship between age and both MPPGL and HPGL. These findings indicate the importance of considering differences between study populations when forecasting in vivo pharmacokinetic behaviour. Typical clinical pharmacology studies, particularly in early drug development, use young, fit, healthy male subjects of around 30 years of age. In contrast, the average age of patients for many diseases is about 60 years of age. The relationship between age and MPPGL observed in this study estimates values of 40 mg.g-1 for a 30 year old individual and 31 mg.g-1 for a 60 year old individual. Investigators may wish to consider the reported covariates in the selection of scaling factors appropriate for the population in which estimates of clearance are being predicted. Further studies are required to clarify the influence of age (especially in paediatric subjects), donor source and ethnicity on values of MPPGL and HPGL. In the meantime, we recommend that the estimates (and their variances) from the current meta-analysis be used when predicting in vivo kinetic parameters from in vitro data.

Differences in cytochrome p450-mediated pharmacokinetics between chinese and caucasian populations predicted by mechanistic physiologically based pharmacokinetic modelling.

BACKGROUND: International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) guidelines emphasize the need for better understanding of the influence of ethnicity on drug response to minimize duplication of clinical studies, thereby expediting drug approval. OBJECTIVES: We have developed a Chinese database for the prediction of differences in the population kinetics of drugs mainly metabolized by cytochromes P450 (CYPs) relative to Caucasian populations. Such predictions should help to inform the need for duplication of in vivo pharmacokinetic studies in the two ethnic groups and the design of such studies. METHODS: Demographic and physiological data for Chinese, along with information on CYP abundances and the frequencies of associated genetic polymorphisms in Chinese, were collated from literature sources and incorporated within the Simcyp Population-based Simulator(®) (v11.1). Default Simcyp parameter values for a virtual Caucasian population and for model compounds metabolized principally by specific CYPs were used as the point of reference. The drugs and the main CYPs involved in their metabolism were phenacetin (CYP1A2), desipramine (CYP2D6), tolbutamide (CYP2C9), omeprazole (CYP2C19), and alprazolam and midazolam (CYP3A). Hydroxy bupropion formation was used as a more sensitive marker of CYP2B6 activity than bupropion kinetics. Observed plasma drug concentration-time profiles and pharmacokinetic parameters after oral and, where possible, intravenous dosing were obtained from published in vivo studies in both Chinese and Caucasian subjects. Virtual subjects generated within Simcyp were matched to the subjects used in the in vivo studies with respect to age, sex, dosage and, where possible, CYP phenotype frequency. Predicted and observed plasma drug concentrations and weight-normalized clearances were compared between the ethnic groups. RESULTS: Significant differences were identified between Chinese and Caucasian populations in the frequency of CYP2C19 poor metabolizers (PMs) [Chinese 13 %; Caucasian 2.4 %], CYP2D6 PMs and intermediate metabolizers (IMs) [Chinese PMs 0.3 %, IMs 39 %; Caucasian PMs 8 %, IMs <1 %], the hepatic abundance of CYP2C19 (mean values: Chinese 8 pmol/mg; Caucasian 14 pmol/mg) and liver weight (mean values: Chinese 1198 g; Caucasian 1603 g). The observed plasma drug concentration-time profiles and weight-normalized clearances were predicted with reasonable accuracy (100 % within twofold; 89 % within 1.5-fold) in both ethnic groups. The predicted phenacetin, tolbutamide, omeprazole, desipramine, midazolam (intravenous), midazolam (oral), alprazolam (intravenous) and alprazolam (oral) clearances were 36, 25, 51, 43, 24, 17, 21 and 22 % lower, respectively, in Chinese than in Caucasians; the observed clearances were 28, 2, 75, 42, 19, 62, 20 and 21 % lower, respectively. Predicted and observed formation of hydroxy bupropion was lower in Caucasians than in Chinese (6 and 20 %, respectively). Differences between ethnic groups were less after normalization for body weight. CONCLUSION: The results of this study indicate the value of simulation based on mechanistic physiologically based pharmacokinetic modelling (PBPK) in anticipating the likely extent of any differences in the kinetics of CYP substrates in Chinese and Caucasian populations arising from demographic, physiological and genetic differences.

Age related changes in fractional elimination pathways for drugs: assessing the impact of variable ontogeny on metabolic drug-drug interactions.

The magnitude of any metabolic drug-drug interactions (DDIs) depends on fractional importance of inhibited pathway which may not necessarily be the same in young children when compared to adults. The ontogeny pattern of cytochrome P450 (CYP) enzymes (CYPs 1A2, 2B6, 2C8, 2C9, 2C18/19, 2D6, 2E1, 3A4) and renal function were analyzed systematically. Bootstrap methodology was used to account for variability, and to define the age range over which statistical differences existed between each pair of specific pathways. A number of DDIs were simulated (Simcyp Pediatric v12) for virtual compounds to highlight effects of age on fractional elimination and consequent magnitude of DDI. For a theoretical drug metabolized 50% by each of CYP2D6 and CYP3A4 pathways at birth, co-administration of ketoconazole (3 mg/kg) resulted in a 1.65-fold difference between inhibited versus uninhibited AUC compared to 2.4-fold in 1 year olds and 3.2-fold in adults. Conversely, neonates could be more sensitive to DDI than adults in certain scenarios. Thus, extrapolation from adult data may not be applicable across all pediatric age groups. The use of pediatric physiologically based pharmacokinetic (p-PBPK) models may offer an interim solution to uncovering potential periods of vulnerability to DDI where there are no existing clinical data derived from children.