Pharmacokinetic interactions among imatinib, bosentan and sildenafil, and their clinical implications in severe pulmonary arterial hypertension

Selecting the Best Pharmacokinetic Models for a Priori Model-Informed Precision Dosing with Model Ensembling

BACKGROUND AND OBJECTIVE

When utilizing population pharmacokinetic (popPK) models for a priori dosage individualization, selecting the best model is crucial to obtain adequate doses. We developed and evaluated several model-selection and ensembling methods, using external evaluation on the basis of therapeutic drug monitoring (TDM) samples to identify the best (set of) models per patient for a priori dosage individualization.

METHODS

PK data and models describing both hospitalized patients (n = 134) receiving continuous vancomycin (26 models) and patients (n = 92) receiving imatinib in an outpatient setting (12 models) are included. Target attainment of four model-selection methods was compared with standard dosing: the best model based on external validation, uninformed model ensembling, model ensembling using a weighting scheme on the basis of covariate-stratified external evaluation, and model selection using covariates in decision trees that were subsequently ensembled.

RESULTS

Overall, the use of PK models improved the proportion of patients exposed to concentrations within the therapeutic window for both cohorts. Relative improvement of proportion on target for best model, unweighted, weighted, and decision trees were - 7.0%, 2.3%, 11.4%, and 37.0% (vancomycin method-development); 23.2%, 7.9%, 15.6%, and, 77.2% (vancomycin validation); 40.7%, 50.0%, 59.5%, and 59.5% (imatinib method-development); and 19.0%, 28.5%, 38.0%, and 23.8% (imatinib validation), respectively.

CONCLUSIONS

The best (set of) models per patient for a priori dosage individualization can be identified using a relatively small set of TDM samples as external evaluation. Adequately performing popPK models were identified while also excluding poor-performing models. Dose recommendations resulted in more patients within the therapeutic range for both vancomycin and imatinib. Prospective validation is necessary before clinical implementation.

Clinical pharmacokinetics and drug-drug interactions of tyrosine-kinase inhibitors in chronic myeloid leukemia: A clinical perspective

In the past decade, numerous tyrosine kinase inhibitors (TKIs) have been introduced in the treatment of chronic myeloid leukemia. Given the significant interpatient variability in TKIs pharmacokinetics, potential drug-drug interactions (DDIs) can greatly impact patient therapy. This review aims to discuss the pharmacokinetic characteristics of TKIs, specifically focusing on their absorption, distribution, metabolism, and excretion profiles. Additionally, it provides a comprehensive overview of the utilization of TKIs in special populations such as the elderly, children, and patients with liver or kidney dysfunction. We also highlight known or suspected DDIs between TKIs and other drugs, highlighting various clinically relevant interactions. Moreover, specific recommendations are provided to guide haemato-oncologists, oncologists, and clinical pharmacists in managing DDIs during TKI treatment in daily clinical practice.

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.

The Application of Virtual Therapeutic Drug Monitoring to Assess the Pharmacokinetics of Imatinib in a Chinese Cancer Population Group

PURPOSE

Imatinib is used in gastrointestinal stromal tumours (GIST) and chronic myeloid leukaemia (CML). Oncology patients demonstrate altered physiology compared to healthy adults, e.g. reduced haematocrit, increased α-1 acid glycoprotein, decreased albumin and reduced glomerular filtration rate (GFR), which may influence imatinib pharmacokinetics. Given that Chinese cancer patients often report raised imatinib plasma concentrations and wider inter-individual variability reported in trough concentration when compared to Caucasian cancer patients, therapeutic drug monitoring (TDM) has been advocated.

METHOD

This study utilised a previously validated a Chinese cancer population and assessed the impact of imatinib virtual-TDM in Chinese and Caucasian cancer populations across a dosing range from 200-800 mg daily.

RESULTS

Staged dose titration to 800 mg daily, resulted in recapitulation to within the target therapeutic range for 50 % (Chinese) and 42.1% (Caucasian) subjects possessing plasma concentration < 550 ng/mL when dosed at 400 mg daily. For subjects with plasma concentrations >1500 ng/mL when dosed at 400 mg daily, a dose reduction to 200 mg once daily was able to recover 67 % (Chinese) and 87.4 % (Caucasian) patients to the target therapeutic range.

CONCLUSION

Virtual TDM highlights the benefit of pharmacokinetic modelling to optimising treatments in challenging oncology population groups.

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

AIMS

Imatinib is considered the standard first-line treatment in newly diagnosed patients with chronic-phase myeloid leukaemia (CML). Several imatinib population pharmacokinetic (popPK) models have been developed. However, their predictive performance has not been well established when extrapolated to different populations. Therefore, this study aimed to perform an external evaluation of available imatinib popPK models developed mainly in adult patients, and to evaluate the improvement in individual model-based predictions through Bayesian forecasting computed by each model at different treatment occasions.

METHODS

A literature review was conducted through PubMed and Scopus to identify popPK models. Therapeutic drug monitoring data collected in adult CML patients treated with imatinib was used for external evaluation, including prediction- and simulated-based diagnostics together with Bayesian forecasting analysis.

RESULTS

Fourteen imatinib popPK studies were included for model-performance evaluation. A total of 99 imatinib samples were collected from 48 adult CML patients undergoing imatinib treatment with a minimum of one plasma concentration measured at steady-state between January 2016 and December 2020. The model proposed by Petain et al showed the best performance concerning prediction-based diagnostics in the studied population. Bayesian forecasting demonstrated a significant improvement in predictive performance at the second visit. Inter-occasion variability contributed to reducing bias and improving individual model-based predictions.

CONCLUSIONS

Imatinib popPK studies developed in Caucasian subjects including α1-acid glycoprotein showed the best model performance in terms of overall bias and precision. Moreover, two imatinib samples from different visits appear sufficient to reach an adequate model-based individual prediction performance trough Bayesian forecasting.

Positioning imatinib for pulmonary arterial hypertension: A phase I/II design comprising dose finding and single-arm efficacy

Pulmonary arterial hypertension is an unmet clinical need. Imatinib, a tyrosine kinase inhibitor, 200 to 400 mg daily reduces pulmonary artery pressure and increases functional capacity in this patient group, but is generally poorly tolerated at the higher dose. We have designed an open-label, single-arm clinical study to investigate whether there is a tolerated dose of imatinib that can be better targeted to patients who will benefit. The study consists of two parts. Part 1 seeks to identify the best tolerated dose of Imatinib in the range from 100 and up to 400 mg using a Bayesian Continuous Reassessment Method. Part 2 will measure efficacy after 24 weeks treatment with the best tolerated dose using a Simon's two-stage design. The primary efficacy endpoint is a binary variable. For patients with a baseline pulmonary vascular resistance (PVR) >1000 dynes · s · cm-5, success is defined by an absolute reduction in PVR of ≥300 dynes · s · cm-5 at 24 weeks. For patients with a baseline PVR ≤1000 dynes · s · cm-5, success is a 30% reduction in PVR at 24 weeks. PVR will also be evaluated as a continuous variable by genotype as an exploratory analysis. Evaluating the response to that dose by genotype may inform a prospective biomarker-driven study.

Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics

Long-term use of imatinib is effective and well-tolerated in children with chronic myeloid leukaemia (CML) yet defining an optimal dosing regimen for imatinib in younger patients is a challenge. The potential interactions between imatinib and coadministered drugs in this "special" population also remains largely unexplored. This study implements a physiologically based pharmacokinetic (PBPK) modeling approach to investigate optimal dosing regimens and potential drug interactions with imatinib in the paediatric population. A PBPK model for imatinib was developed in the Simcyp Simulator (version 17) utilizing in silico, in vitro drug metabolism, and in vivo pharmacokinetic data and verified using an independent set of published clinical pharmacokinetic data. The model was then extrapolated to children and adolescents (aged 2-18 years) by incorporating developmental changes in organ size and maturation of drug-metabolising enzymes and plasma protein responsible for imatinib disposition. The PBPK model described imatinib pharmacokinetics in adult and paediatric populations and predicted drug interaction with carbamazepine, a cytochrome P450 (CYP)3A4 and 2C8 inducer, with a good accuracy (evaluated by visual inspections of the simulation results and predicted pharmacokinetic parameters that were within 1.25-fold of the clinically observed values). The PBPK simulation suggests that the optimal dosing regimen range for imatinib is 230-340 mg/m2/d in paediatrics, which is supported by the recommended initial dose for treatment of childhood CML. The simulations also highlighted that children and adults being treated with imatinib have similar vulnerability to CYP modulations. A PBPK model for imatinib was successfully developed with an excellent performance in predicting imatinib pharmacokinetics across age groups. This PBPK model is beneficial to guide optimal dosing regimens for imatinib and predict drug interactions with CYP modulators in the paediatric population.

Inadequate response to imatinib treatment in chronic myeloid leukemia due to a drug interaction with phenytoin

Imatinib mesylate and the newer BCR-ABL tyrosine kinase inhibitors are the standard therapy for chronic myeloid leukemia. Although these are remarkably effective drugs, some mechanisms of resistance have been identified including drug-to-drug interactions. Here we present the case of a chronic myeloid leukemia patient with an inadequate response to imatinib due to concurrent phenytoin administration. Conspicuously low imatinib plasma trough levels were documented. Imatinib dose was increased from 400 to 800 mg with good response. In conclusion, drug-to-drug interactions should be ruled out in cases of resistance to tyrosine kinase inhibitor treatment. Potent inducers of cytochrome P450 isoenzyme CYP3A4, as phenytoin, could induce inadequate responses due to increased imatinib clearance and low imatinib trough plasma levels. Thus, this interaction should be avoided. When this is not possible, dose escalation of imatinib and measurement of plasma levels, if available, is recommended.

Reducing Interstitial Fluid Pressure and Inhibiting Pulmonary Metastasis of Breast Cancer by Gelatin Modified Cationic Lipid Nanoparticles

Interstitial fluid pressure (IFP) in tumor is much higher than that in normal tissue, and it constitutes a great obstacle for the delivery of antitumor drugs, thus becoming a potential target for cancer therapy. In this study, cationic nanostructured lipid carriers (NLCs) were modified by low molecular weight gelatin to achieve the desirable reduction of tumor IFP and improve the drug delivery. In this way, the chemotherapy of formulations on tumor proliferation and pulmonary metastasis was further improved. The nanoparticles were used to load three drugs, docetaxel (DTX), quercetin (Qu), and imatinib (IMA), with high encapsulation efficiency of 89.54%, 96.45%, and 60.13%, respectively. GNP-DTX/Qu/IMA nanoparticles exhibited an enzyme-sensitive drug release behavior, and the release rate could be mediated by matrix metalloproteinases (MMP-9). Cellular uptake and MTT assays showed that the obtained GNP-DTX/Qu/IMA could be internalized into human breast 4T1 cells effectively and exhibited the strongest cytotoxicity. Moreover, GNP-DTX/Qu/IMA demonstrated obvious advantages in inducing apoptosis and mediating the expression of apoptosis-related proteins (Caspase 3, Caspase 9, and bcl-2). In the wound-healing assay, GNP-DTX/Qu/IMA exhibited evidently inhibition of cell migration. The benefits of tumor IFP reduction induced by GNP-DTX/Qu/IMA were further proved after a continuous administration to 4T1 tumor-bearing mice. Finally, in the in vivo antitumor assays, GNP-DTX/Qu/IMA displayed stronger antitumor efficiency as well as suppression on pulmonary metastasis. In conclusion, the GNP-DTX/Qu/IMA system might be a promising strategy for metastatic breast cancer treatment.

Methods and strategies for assessing uncontrolled drug-drug interactions in population pharmacokinetic analyses: results from the International Society of Pharmacometrics (ISOP) Working Group

The purpose of this work was to present a consolidated set of guidelines for the analysis of uncontrolled concomitant medications (ConMed) as a covariate and potential perpetrator in population pharmacokinetic (PopPK) analyses. This white paper is the result of an industry-academia-regulatory collaboration. It is the recommendation of the working group that greater focus be given to the analysis of uncontrolled ConMeds as part of a PopPK analysis of Phase 2/3 data to ensure that the resulting outcome in the PopPK analysis can be viewed as reliable. Other recommendations include: (1) collection of start and stop date and clock time, as well as dose and frequency, in Case Report Forms regarding ConMed administration schedule; (2) prespecification of goals and the methods of analysis, (3) consideration of alternate models, other than the binary covariate model, that might more fully characterize the interaction between perpetrator and victim drug, (4) analysts should consider whether the sample size, not the percent of subjects taking a ConMed, is sufficient to detect a ConMed effect if one is present and to consider the correlation with other covariates when the analysis is conducted, (5) grouping of ConMeds should be based on mechanism (e.g., PGP-inhibitor) and not drug class (e.g., beta-blocker), and (6) when reporting the results in a publication, all details related to the ConMed analysis should be presented allowing the reader to understand the methods and be able to appropriately interpret the results.