Systematic Evaluation of Osimertinib Population Pharmacokinetic Models in a Cohort of Dutch Adults with Non-Small Cell Lung Cancer.

BACKGROUND AND OBJECTIVE: Several population pharmacokinetic (popPK) studies have been reported that can guide the prediction of osimertinib plasma concentrations in individual patients. It is currently unclear which popPK model offers the best predictive performance and which popPK models are most suitable for nonadherence management and model-informed precision dosing. Therefore, the objective of this study was to externally validate all osimertinib popPK models available in the current literature. METHODS: Published popPK models for osimertinib were constructed using NONMEM version 7.4.4. The predictive quality of the identified models was assessed with goodness-of-fit (GoF) plots, conditional weighted residuals (CWRES) plots and a prediction-corrected visual predictive check (pcVPC) for osimertinib and its active metabolite AZ5104. A subset from the Dutch OSIBOOST trial, where 11 patients with low osimertinib exposure were included, was used as evaluation cohort. RESULTS: The population GoF plots for all four models poorly followed the line of identity. For the individual GoF plots, all models performed comparable and were closely distributed among the line of identity. CWRES of the four models were skewed. The pcVPCs of all four models showed a similar trend, where all observed concentrations fell in the simulated shaded areas, but in the lower region of the simulated areas. CONCLUSION: All four popPK models can be used to individually predict osimertinib concentrations in patients with low osimertinib exposure. For population predictions, all four popPK models performed poorly in patients with low osimertinib exposure. A novel popPK model with good predictive performance should be developed for patients with low osimertinib exposure. Ideally, the cause for the relatively low osimertinib exposure in our evaluation cohort should be known. CLINICAL TRIALS REGISTRATION: NCT03858491.

Validation of an LC-MS/MS assay for rapid and simultaneous quantification of 21 kinase inhibitors in human plasma and serum for therapeutic drug monitoring.

Kinase inhibitors have revolutionized cancer treatment in the past 25 years and currently form the cornerstone of many treatments. Due to the increasing evidence for therapeutic drug monitoring (TDM) of kinase inhibitors, the need is growing for new assays to rapidly evaluate kinase inhibitor plasma concentrations. In this study, we developed an LC-MS/MS assay for the rapid and simultaneous quantification of 21 kinase inhibitors. First, a literature search was conducted to ensure that the linear ranges of the analytes were in line with the reported therapeutic windows and/or TDM reference values. Subsequently, the assay was validated according to FDA and EMA guidelines for linearity, selectivity, carry-over, accuracy, precision, dilution integrity, matrix effect, recovery, and stability. The assay was fast, with a short run-time of 2 min per sample. Sample pre-treatment consisted of protein precipitation with methanol enriched with stable isotope-labeled internal standards (SIL-IS), and the mixture was vortexed and centrifuged before sample injection. Separation was achieved using a C18 column (3 µm,50 × 2.1 mm) with a gradient of two mobile phases (ammonium formate buffer pH 3.5 and acetonitrile). Analyte detection was conducted in positive ionization mode using selected reaction monitoring. The assay was accurate and precise in plasma as well as in serum. Extraction recovery ranged between 95.0% and 106.0%, and the matrix effect was 95.7%-105.2%. The stability of the analytes varied at room temperature and in refrigerated conditions. However, all drugs were found to be stable for 7 days in the autosampler. The clinical applicability of the analytical method (486 analyzed samples between 1 July 2022-1 July 2023) as well as external quality control testing results were evaluated. Taken together, the results demonstrate that the analytical method was validated and applicable for routine analyses in clinical practice.

Pharmacokinetic Boosting of Kinase Inhibitors.

(1) Introduction: Pharmacokinetic boosting of kinase inhibitors can be a strategy to enhance drug exposure and to reduce dose and associated treatment costs. Most kinase inhibitors are predominantly metabolized by CYP3A4, enabling boosting using CYP3A4 inhibition. Kinase inhibitors with food enhanced absorption can be boosted using food optimized intake schedules. The aim of this narrative review is to provide answers to the following questions: Which different boosting strategies can be useful in boosting kinase inhibitors? Which kinase inhibitors are potential candidates for either CYP3A4 or food boosting? Which clinical studies on CYP3A4 or food boosting have been published or are ongoing? (2) Methods: PubMed was searched for boosting studies of kinase inhibitors. (3) Results/Discussion: This review describes 13 studies on exposure boosting of kinase inhibitors. Boosting strategies included cobicistat, ritonavir, itraconazole, ketoconazole, posaconazole, grapefruit juice and food. Clinical trial design for conducting pharmacokinetic boosting trials and risk management is discussed. (4) Conclusion: Pharmacokinetic boosting of kinase inhibitors is a promising, rapidly evolving and already partly proven strategy to increase drug exposure and to potentially reduce treatment costs. Therapeutic drug monitoring can be of added value in guiding boosted regimens.

Vancomycin pharmacokinetic model development in patients on intermittent online hemodiafiltration.

BACKGROUND: Vancomycin is frequently used in hemodialysis (HD) and in hemodiafiltration (HDF) patients and is usually administered in the last 30 or 60 minutes of a dialysis session. Vancomycin pharmacokinetics are not well described in HDF patients. The aim of this study is to develop a population pharmacokinetic (PPK) model and dosing regimen for vancomycin in HDF patients and to evaluate its applicability in low-flux (LF-HD) patients. METHODS: Two-compartment PPK models were developed using data from HDF patients (n = 17), and was parameterized as follows: non-renal clearance (CLm), renal clearance as a fraction of creatinine clearance (fr), central volume of distribution (V1), intercompartmental clearance (CL12), peripheral volume of distribution (V2) and extracorporeal extraction ratio (Eec). We evaluated the final model in a cohort of LF-HD patients (n = 21). Dosing schemes were developed for a vancomycin 24-h AUC of 400 mg*h/L. RESULTS: Model parameters (± SD) were: CLm = 0.473 (0.271) L/h, fr = 0.1 (fixed value), V1 = 0.278 (0.092) L/kgLBMc, CL12 = 9.96 L/h (fixed value), V2 = 0.686 (0.335) L/kgLBMc and Eec = 0.212 (0.069). The model reliably predicted serum levels of vancomycin in both HDF and LF-HD patients during and between dialysis sessions. The median of the prediction error (MDPE) as a measure of bias is -0.7% (95% CI: -3.4%-1.7%) and the median of the absolute values of the prediction errors (MDAPE) as a measure of precision is 7.9% (95% CI: 6.0%-9.8%). In both HDF and LF-HD, the optimal vancomycin loading dose for a typical patient weighing 70 kg is 1700 mg when administered during the last 60 minutes of the hemodialysis session. Maintenance dose is 700 mg if administered during the last 30 or 60 minutes of the hemodialysis session. CONCLUSION: The developed PPK model for HDF is also capable of predicting serum levels of vancomycin in patients on LF-HD. A dosing regimen was developed for the use of vancomycin in HDF and LF-HD.