Physiologically Based Pharmacokinetic Modeling and Dose Adjustment of Teicoplanin in Pediatric Patients With Renal Impairment

A review of physiologically based pharmacokinetic modeling of renal drug disposition

The human kidney is a critical organ for the elimination of numerous drugs and metabolites. The mechanisms of renal drug handling are manifold including unbound filtration, transporter-mediated active secretion, bidirectional passive diffusion, and occasionally active reabsorption and renal metabolism. These mechanisms collectively dictate the fate of drugs at various spatiotemporal points as drug molecules travel through the renal vasculature, tubules, and cells, posing a significant challenge in accurately describing and predicting renal drug disposition. Toward this end, a physiologically based kidney model serves as a promising tool to combine the anatomical and physiological features of the kidney (eg, tubular flow rate, pH, and transporter expression) with the unique properties of drugs (eg, protein binding, lipophilicity, ionization, and transporter substrate) to capture the dynamic system-drug interactions. Despite the exciting progress over the past several decades, physiologically based pharmacokinetic modeling has overall been predominantly used to predict intestinal absorption and hepatic drug-drug interaction. In comparison, pharmacokinetic modeling of renal drug handling has been underappreciated. In this review, we first provide an overview of kidney function and physiology, renal clearance mechanisms, and the evolutionary history of the physiologically based mechanistic kidney model. We then summarize the recent efforts spent in different areas of kidney model application, particularly: (1) renal transporter-mediated drug-drug interaction, (2) disease effect from both renal and hepatic impairment, and (3) model applications across the lifespan (eg, pediatrics and geriatrics). Finally, we identify remaining knowledge gaps, future directions, and potential model utilities. SIGNIFICANCE STATEMENT: This review summarizes pharmacokinetic model case studies that are related to renal drug disposition, illustrating the current framework of modeling renal drug handling, highlighting knowledge gaps in predicting renal transporter-mediated drug-drug interactions, and modeling the effects of disease and age on renal drug handling. A discussion on robust model validation and areas for future directions is also provided.

Investigation of Teicoplanin Trough Concentrations and Safety Following High-Dose Loading in a Pediatric Population

BACKGROUND

Therapeutic drug monitoring-informed teicoplanin dosage adjustments are recommended for safe and effective use. The authors' group previously reported that only half of children reached the recommended blood concentration range at the standard teicoplanin loading dose. It has been suggested that higher loading doses are necessary; however, the usefulness and safety of high-dose loading in pediatric patients in clinical practice are unknown.

METHODS

This retrospective cohort study was conducted between January 2018 and June 2021 using electronic medical records. The analysis included 2- to 16-year-old patients treated with teicoplanin who met the eligibility criteria. We assessed the trough concentration of teicoplanin and its safety after high-dose loading in pediatric patients.

RESULTS

Overall, 86 patients received a high-dose loading regimen (15 mg/kg every 12 hours for 3 doses, followed by 10 mg/kg once daily). Notably, 55 of the 86 patients (64%) achieved the target trough concentration (>15 mg/L) at significantly higher rates without increasing the incidence of organ damage compared with the standard loading regimen. Multivariate analysis revealed significant differences in age and renal function as factors that inhibited the attainment of the target trough concentration. Simulation analysis using a nomogram stratified by age and renal function revealed that the predicted teicoplanin trough levels were within the target trough values in 73% of patients.

CONCLUSIONS

High-dose teicoplanin loading safely increases trough blood concentrations in the pediatric population. For further optimization, the dose selection should be stratified according to age and renal function.

Chronic kidney disease and physiologically based pharmacokinetic modeling: a critical review of existing models

INTRODUCTION

Physiologically based pharmacokinetic (PBPK) modeling is a paradigm shift in this era for determining the exposure of drugs in pediatrics, geriatrics, and patients with chronic diseases where clinical trials are difficult to conduct.

AREAS COVERED

This review has collated data regarding published PBPK models on chronic kidney disease (CKD), including the drug and system-specific input model parameters and model evaluation criteria. Four databases were used from 13th June 2023 to 10th July 2023 for identifying the relevant studies that met the inclusion/exclusion criteria. Alterations in plasma protein (albumin/alpha-1 acid glycoprotein), gastric emptying time, hematocrit, small intestinal transit time, the abundance of cytochrome (CYP) 450 enzymes, glomerular filtration rate, and physicochemical parameters for different drugs were explicitly elaborated from earlier reported studies. Moreover, model evaluation depicted that models in CKD for most of the included drugs were within the allowed two-fold error range.

EXPERT OPINION

This review will provide insights for researchers on applying PBPK models in managing patients with different levels of CKD to prevent undesirable side effects and increase the effectiveness of drug therapy.

Lamivudine and Emtricitabine Dosing Proposal for Children with HIV and Chronic Kidney Disease, Supported by Physiologically Based Pharmacokinetic Modelling

Dose recommendations for lamivudine or emtricitabine in children with HIV and chronic kidney disease (CKD) are absent or not supported by clinical data. Physiologically based pharmacokinetic (PBPK) models have the potential to facilitate dose selection for these drugs in this population. Existing lamivudine and emtricitabine compound models in Simcyp^® (v21) were verified in adult populations with and without CKD and in non-CKD paediatric populations. We developed paediatric CKD population models reflecting subjects with a reduced glomerular filtration and tubular secretion, based on extrapolation from adult CKD population models. These models were verified using ganciclovir as a surrogate compound. Then, lamivudine and emtricitabine dosing strategies were simulated in virtual paediatric CKD populations. The compound and paediatric CKD population models were verified successfully (prediction error within 0.5- to 2-fold). The mean AUC ratios in children (GFR-adjusted dose in CKD population/standard dose in population with normal kidney function) were 1.15 and 1.23 for lamivudine, and 1.20 and 1.30 for emtricitabine, with grade-3- and -4-stage CKD, respectively. With the developed paediatric CKD population PBPK models, GFR-adjusted lamivudine and emtricitabine dosages in children with CKD resulted in adequate drug exposure, supporting paediatric GFR-adjusted dosing. Clinical studies are needed to confirm these findings.

Physiologically Based Pharmacokinetic (PBPK) Model-Informed Dosing Guidelines for Pediatric Clinical Care: A Pragmatic Approach for a Special Population

Physiologically based pharmacokinetic (PBPK) modeling can be an attractive tool to increase the evidence base of pediatric drug dosing recommendations by making optimal use of existing pharmacokinetic (PK) data. A pragmatic approach of combining available compound models with a virtual pediatric physiology model can be a rational solution to predict PK and hence support dosing guidelines for children in real-life clinical care, when it can also be employed by individuals with little experience in PBPK modeling. This comes within reach as user-friendly PBPK modeling platforms exist and, for many drugs and populations, models are ready for use. We have identified a list of drugs that can serve as a starting point for pragmatic PBPK modeling to address current clinical dosing needs.