Exploring the impact of ethnicity on drug pharmacokinetics using PBPK models: A case study with lansoprazole in Japanese subjects

AIMS

The aim of this study is to demonstrate the use of PBPK modelling to explore the impact of ethnic differences on drug PK.

METHODS

A PBPK model developed for lansoprazole was used to predict the clinical PK of lansoprazole in Japanese subjects by incorporating the physiological parameters of a Japanese population into the model. Further verification of the developed Japanese population with clinical studies involving eight other CYP substrates-omeprazole, ticlopidine, alprazolam, midazolam, nifedipine, cinacalcet, paroxetine and dextromethorphan-was also carried out.

RESULTS

The PK of lansoprazole in both Caucasian and Japanese subjects was well predicted by the model as the observed data were within the 5th and 95th percentiles across all the clinical studies. In age- and sex-matched simulations in both the Caucasian and Japanese populations, the predicted PK (mean ± SD) of a single oral dose of 30-mg lansoprazole was higher in the Japanese population in all cases, with more than twofold higher AUC of 5.98 ± 6.43 mg/L.h (95% CI: 4.72, 7.24) vs. 2.46 ± 2.45 mg/L.h (95% CI: 1.98, 2.94) in one scenario. In addition, in two out of the nine clinical DDIs of lansoprazole and the additional CYP substrates simulated using the Japanese population, the predicted DDI in Japanese was more than 1.25-fold that in Caucasians, indicating an increased DDI liability.

CONCLUSIONS

By accounting for various physiological parameters that characterize a population in a PBPK model, the impact of the different identified interethnic differences on the drug's PK can be explored, which can inform the adoption of drugs from one region to another.

Guide to development of compound files for PBPK modeling in the Simcyp population-based simulator

The Simcyp Simulator is a software platform for population physiologically‐based pharmacokinetic (PBPK) modeling and simulation. It links in vitro data to in vivo absorption, distribution, metabolism, excretion and pharmacokinetic/pharmacodynamic outcomes to explore clinical scenarios and support drug development decisions, including regulatory submissions and drug labels. This tutorial describes the different input parameters required, as well as the considerations needed when developing a PBPK model within the Simulator, for a small molecule intended for oral administration. A case study showing the development and application of a PBPK model for ondansetron is herein used to aid the understanding of different PBPK model development concepts.

Quantification of Fetal Renal Function Using Fetal Urine Production Rate and Its Reflection on the Amniotic and Fetal Creatinine Levels During Pregnancy

Adequate prediction of fetal exposure of drugs excreted by the kidney requires the incorporation of time-varying renal function parameters into a pharmacokinetic model. Published data on measurements of fetal urinary production rate (FUPR) and creatinine at various gestational ages were collected and integrated for prediction of the fetal glomerular filtration rate (GFR). The predicted GFR values were then compared to neonatal values recorded at birth. Collected data for FUPR across different gestational ages using both 3D (N = 517) and 2D (N = 845) ultrasound methods showed that 2D techniques yield significantly lower estimates of FUPR than 3D (p < 0.0001). A power law function was shown to best capture the change in FUPR with fetal age (FA) for both 2D ( F U P R 2 D ( m L min ) = 0 . 000169     FA 2 . 19 ); and 3D ( F U P R 3 D   ( m L min ) =   3 . 21 × 1 0 - 7   FA 4 . 21 ) data. The predicted FUPR based on the observed 3D data was shown to be strongly linearly related (R ² = 0.95) to measured values of amniotic creatinine concentration (N = 664). The FUPR_3D data together with creatinine levels in the fetal urine and serum resulted in median predicted fetal GFR values of 0.47, 1.2, 2.5, and 4.9 ml/min at 23, 28, 33, and 38 weeks of fetal age (50% CV), respectively. These values are in good agreement with neonatal values observed immediately at birth. The derived FUPR and creatinine functions can be utilized to assess fetal renal maturation and predict fetal renal clearance.

Risk-Benefit Assessment of Ethinylestradiol Using a Physiologically Based Pharmacokinetic Modeling Approach

Current formulations of combined oral contraceptives (COC) containing ethinylestradiol (EE) have ≤35 μg due to increased risks of cardiovascular diseases (CVD) with higher doses of EE. Low‐dose formulations however, have resulted in increased incidences of breakthrough bleeding and contraceptive failure, particularly when coadministered with inducers of cytochrome P450 enzymes (CYP). The developed physiologically based pharmacokinetic model quantitatively predicted the effect of CYP3A4 inhibition and induction on the pharmacokinetics of EE. The predicted C_max and AUC ratios when coadministered with voriconazole, fluconazole, rifampicin, and carbamazepine were within 1.25 of the observed data. Based on published clinical data, an AUC_ss value of 1,000 pg/ml.h was selected as the threshold for breakthrough bleeding. Prospective application of the model in simulations of different doses of EE (20 μg, 35 μg, and 50 μg) identified percentages of the population at risk of breakthrough bleeding alone and with varying degrees of CYP modulation.

Assessment of Potential Herb-Drug Interactions among Nigerian Adults with Type-2 Diabetes

It is becoming increasingly evident that patients with diabetes do not rely only on prescription drugs for their disease management. The use of herbal medicines is one of the self-management practices adopted by these patients, often without the knowledge of their healthcare practitioners. This study assessed the potential for pharmacokinetic herb-drug interactions (HDIs) amongst Nigerian adult diabetic patients. This was done through a literature analysis of the pharmacokinetic profile of their herbal medicines and prescription drugs, based on information obtained from 112 patients with type-2 diabetes attending two secondary health care facilities in Nigeria. Fifty percent of the informants used herbal medicines alongside their prescription drugs. Worryingly, 60% of the patients taking herbal medicines did not know their identity, thus increasing the risk of unidentified HDIs. By comparing the pharmacokinetic profile of eight identified herbs taken by the patients for the management of diabetes against those of the prescription drugs, several scenarios of potential HDIs were identified and their clinical relevance is discussed. The lack of clinical predictors points toward cultural factors as the influence for herb use, making it more difficult to identify these patients and in turn monitor potential HDIs. In identifying these possible interactions, we have highlighted the need for healthcare professionals to promote a proactive monitoring of patients' use of herbal medicines.