External evaluation of population pharmacokinetic models of imatinib in adults diagnosed with chronic myeloid leukaemia

Predictive performance of population pharmacokinetic models of imatinib in chronic myeloid leukemia patients

BACKGROUND AND AIM

Chronic myeloid leukemia is a myeloproliferative neoplasm associated with the specific chromosomal translocation known as the Philadelphia chromosome. Imatinib is a potent BCR-ABL tyrosine kinase inhibitor, which is approved as the first line therapy for CML patients. There are various population pharmacokinetic studies available in the literature for this population. However, their use in other populations outside of their cohort for the model development has not been evaluated. This study was aimed to perform the predictive performance of the published population pharmacokinetic models for imatinib in CML population and propose a dosing nomogram.

METHODS

A systematic review was conducted through PubMed, and WoS databases to identify PopPK models. Clinical data collected in adult CML patients treated with imatinib was used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions.

RESULTS

Eight imatinib PopPK model were selected for evaluating the model performance. A total of 145 plasma imatinib samples were collected from 43 adult patients diagnosed with CML and treated with imatinib. The PopPK model reported by Menon et al. had better performance than all other PopPK models.

CONCLUSION

Menon et al. model was able to predict well for our clinical data where it had the relative mean prediction error percentage ≤ 20%, relative median absolute prediction error ≤ 30% and relative root mean square error close to zero. Based on this final model, we proposed a dosing nomogram for various weight groups, which could potentially help to maintain the trough concentrations in the therapeutic range.

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.

Assessing Dose-Exposure-Response Relationships of Miltefosine in Adults and Children using Physiologically-Based Pharmacokinetic Modeling Approach

OBJECTIVES

Miltefosine is the first and only oral medication to be successfully utilized as an antileishmanial agent. However, the drug is associated with differences in exposure patterns and cure rates among different population groups e.g. ethnicity and age (i.e., children v adults) in clinical trials. In this work, mechanistic population physiologically-based pharmacokinetic (PBPK) models have been developed to study the dose-exposure-response relationship of miltefosine in in silico clinical trials and evaluate the differences in population groups, particularly children and adults.

METHODS

The Simcyp population pharmacokinetics platform was employed to predict miltefosine exposure in plasma and peripheral blood mononuclear cells (PBMCs) in a virtual population under different dosing regimens. The cure rate of a simulation was based on the percentage of number of the individual virtual subjects with AUCd0-28 > 535 µg⋅day/mL in the virtual population.

RESULTS

It is shown that both adult and paediatric PBPK models of miltefosine can be developed to predict the PK data of the clinical trials accurately. There was no significant difference in the predicted dose-exposure-response of the miltefosine treatment for different simulated ethnicities under the same dose regime and the dose-selection strategies determined the clinical outcome of the miltefosine treatment. A lower cure rate of the miltefosine treatment in paediatrics was predicted because a lower exposure of miltefosine was simulated in virtual paediatric in comparison with adult virtual populations when they received the same dose of the treatment.

CONCLUSIONS

The mechanistic PBPK model suggested that the higher fraction of unbound miltefosine in plasma was responsible for a higher probability of failure in paediatrics because of the difference in the distribution of plasma proteins between adults and paediatrics. The developed PBPK models could be used to determine an optimal miltefosine dose regime in future clinical trials.

Population pharmacokinetics and pharmacogenetics analyses of imatinib in Chinese patients with chronic myeloid leukemia in a real-world situation

BACKGROUND

Imatinib is presently the first-line choice for the treatment of chronic myeloid leukemia. However, there are limited real-world data on Chinese patients to support individualized medicine. This work aims to characterize population pharmacokinetics in Chinese patients with chronic myeloid leukemia, investigate the effects of several covariates on imatinib exposure, and provide support for personalized medicine and dose reduction.

METHODS

A total of 230 patients with chronic myeloid leukemia were enrolled, and 424 steady-state concentration measurements were taken to perform the population pharmacokinetic analysis and Monte Carlo simulations with Phoenix NLME software. The effects of the demographic, biological, and pharmacogenetic (ten SNP corresponding to CYP3A4, CYP3A5, ABCB1, ABCG2, SCL22A1 and POR) covariates on clearance were evaluated.

RESULTS

A one-compartmental model best-described imatinib pharmacokinetics. The hemoglobin and the estimated glomerular filtration rate (< 85 mL⋅min-1⋅1.73 m2) were associated with imatinib clearance. The genetic polymorphisms related to pharmacokinetics were not found to have a significant effect on the clearance of imatinib. The final model estimates of parameters are: ka (h-1) = 0.329; Vd/F (L) = 270; CL/F (L⋅h-1) = 7.60.

CONCLUSIONS

Key covariates in the study population accounting for variability in imatinib exposure are hemoglobin and the estimated glomerular filtration rate. There is some need for caution when treating patients with moderate-to-severe renal impairment and significant hemoglobin changes.

Considering the Oral Bioavailability of Protein Kinase Inhibitors: Essential in Assessing the Extent of Drug-Drug Interaction and Improving Clinical Practice

Protein kinase inhibitors share pharmacokinetic (PK) pathways among themselves. They are all metabolized by several cytochromes P450 (CYP). For most of them, CYP3A4 is the predominant metabolic pathway. However, their oral bioavailability differs. For example, the oral bioavailability of imatinib has been estimated at nearly 100%, but that of ibrutinib averages 3% due to its high hepatic first-pass effect. Overall, the smaller the oral bioavailability, the larger its interindividual PK variability. Indeed, for drugs with low oral bioavailability, the extent of their absorption is an additional cause (along with elimination variability) of differences in drug exposure among patients. The impact of drug-drug interaction (DDI) also differs between drugs with low or high oral bioavailability. We describe and explain why the impact of CYP3A4 inhibitors and inducers is much greater for protein kinase inhibitors with low oral bioavailability. The effect of food on protein kinase inhibitors and DDIs corresponding to plasma protein binding will also be considered. Finally, the benefits of these concepts in clinical practice (including therapeutic drug monitoring) will be discussed. Overall, our main objective was to apply fundamental PK concepts to understanding the main clinical issues of these oral anticancer drugs.

Systemic exposure to hydroxychloroquine and its relationship with outcome in severely ill COVID-19 patients in New York City

AIM

To investigate the relationship between systemic exposure to hydroxychloroquine (HCQ) and its metabolite desethylhydroxychloroquine (DHCQ) and clinical outcome in severely ill patients treated with a standard oral dose regimen of HCQ during the first wave of COVID-19 in New York City.

METHODS

We correlated retrospective clinical data with drug exposure prospectively assessed from convenience samples using population pharmacokinetics and Bayesian estimation. Systemic exposure was assessed in 215 patients admitted to ICU or COVID-ward for whom an interleukin-6 level was requested and who were still alive 24 hours after the last dose of HCQ. Patients received oral HCQ 600 mg twice daily on day 1 followed by 4 days of 400 mg daily.

RESULTS

Fifty-three precent of the patients were intubated at 5.4 ± 6.4 days after admission and 26.5% died at an average of 32.2 ± 19.1 days. QTc at admission was 448 ± 34 ms. Systemic exposure to HCQ and DHCQ demonstrated substantial variability. Cumulative area under the serum concentration-time curve up to infinity for HCQ was 71.4 ± 19.3 h mg/L and for DHCQ 56.5 ± 28.3 h mg/L. Variability in systemic exposure was not clearly explained by renal function, liver function or inflammatory state. In turn, systemic exposure did not correlate with intubation status, survival or QTc prolongation.

CONCLUSION

This study in severely ill patients was not able to find any relationship between systemic exposure to HCQ and DHCQ and clinical outcome at a routine dose regimen and adds to the growing body of evidence that oral HCQ does not alter the course of disease in COVID-19 patients.

Physiologically-based pharmacokinetic modelling and dosing evaluation of gentamicin in neonates using PhysPK

Each year, infections caused around the 25% of neonatal deaths. Early empirical treatments help to reduce this mortality, although optimized dosing regimens are still lacking. The aims were to develop and validate a gentamicin physiologically-based pharmacokinetic (PBPK) model and then potentially explore dosing regimens in neonates using pharmacokinetic and pharmacodynamic criteria. The PBPK model developed consisted of 2 flow-limited tissues: kidney and other tissues. It has been implemented on a new tool called PhysPK, which allows structure reusability and evolution as predictive engine in Model-Informed Precision Dosing (MIPD). Retrospective pharmacokinetic information based on serum levels data from 47 neonates with gestational age between 32 and 39 weeks and younger than one-week postnatal age were used for model validation. The minimal PBPK model developed adequately described the gentamicin serum concentration-time profile with an average fold error nearly 1. Extended interval gentamicin dosing regimens (6 mg/kg q36h and 6 mg/kg q48h for term and preterm neonates, respectively) showed efficacy higher than 99% with toxicity lower than 10% through Monte Carlo simulation evaluations. The gentamicin minimal PBPK model developed in PhysPK from literature information, and validated in preterm and term neonates, presents adequate predictive performance and could be useful for MIPD strategies in neonates.

Role of ADME gene polymorphisms on imatinib disposition: results from a population pharmacokinetic study in chronic myeloid leukaemia

PURPOSE

Imatinib is a substrate of CYP3A4, ABCB1 and ABCG2, and is known to have wide variability in pharmacokinetics (PK). At the same time, a clear relationship between drug levels and response also exists for imatinib in chronic myeloid leukaemia (CML). Therefore, pharmacogenetic-based dosing of imatinib is an attractive proposition. This study aims to characterize the population pharmacokinetics of imatinib in order to identify significant covariates including pharmacogenetic variants.

METHODS

Forty-nine patients with CML were enrolled in the study after being on imatinib for at least 4 consecutive weeks. Steady-state pharmacokinetic sampling was performed either in a sparse (4 samples each, n = 44) or intensive manner (9 samples each, n = 5). An additional pharmacogenetic sample was also collected from all patients. Plasma imatinib levels were estimated using a validated HPLC method. Pharmacogenetic variants were identified using the PharmacoScan array platform. Population pharmacokinetic analysis was carried out using NONMEM v7.2. Seven SNPs within CYP3A4, ABCB1 and ABCG2 genes were evaluated for covariate effect on the clearance of imatinib.

RESULTS

Imatinib PK was well characterized using a one-compartment model with zero-order absorption. The clearance and volume of distribution were found to be 10.2 L/h and 389 L respectively. Only SNP rs1128503 of the ABCB1 gene had a small but insignificant effect on imatinib clearance, with a 25% reduction in clearance observed in patients carrying the polymorphism. Twenty-three out of forty-nine patients (47%) carried the polymorphic allele, of whom 17 were heterozygous and six were homozygous.

CONCLUSION

Our study conclusively proves that genetic polymorphisms in the CYP3A4 and ABC family of transporters do not have any role in the personalized dosing of imatinib in CML.