Population Pharmacokinetics of Imatinib in Nigerians With Chronic Myeloid Leukemia: Clinical Implications for Dosing and Resistance

Kinase Inhibitors FDA Approved 2018-2023: Drug Targets, Metabolic Pathways, and Drug-Induced Toxicities

Small molecule kinase inhibitors are one of the fastest growing classes of drugs, which are approved by the US Food and Drug Administration (FDA) for cancer and noncancer indications. As of September 2023, there were over 70 FDA-approved small molecule kinase inhibitors on the market, 42 of which were approved in the past five years (2018-2023). This minireview discusses recent advances in our understanding of the pharmacology, metabolism, and toxicity profiles of recently approved kinase inhibitors with a central focus on tyrosine kinase inhibitors (TKIs). In this minireview we discuss the most common therapeutic indications and molecular target(s) of kinase inhibitors FDA approved 2018-2023. We also describe unique aspects of the metabolism, bioactivation, and drug-drug interaction (DDI) potential of kinase inhibitors; discuss drug toxicity concerns related to kinase inhibitors, such as drug-induced liver injury; and highlight clinical outcomes and challenges relevant to TKI therapy. Case examples are provided for common TKI targets, metabolism pathways, DDI potential, and risks for serious adverse drug reactions. The minireview concludes with a discussion of perspectives on future research to optimize TKI therapy to maximize efficacy and minimize drug toxicity. SIGNIFICANCE STATEMENT: This minireview highlights important aspects of the clinical pharmacology and toxicology of small molecule kinase inhibitors FDA approved 2018-2023. We describe key advances in the therapeutic indications and molecular targets of TKIs. The major metabolism pathways and toxicity profiles of recently approved TKIs are discussed. Clinically relevant case examples are provided that demonstrate the risk for hepatotoxic drug interactions involving TKIs and coadministered drugs.

Pharmacokinetics of Imatinib Mesylate and Development of Limited Sampling Strategies for Estimating the Area under the Concentration-Time Curve of Imatinib Mesylate in Palestinian Patients with Chronic Myeloid Leukemia

BACKGROUND AND OBJECTIVE

Imatinib is a tyrosine kinase inhibitor used in the treatment of chronic myeloid leukemia (CML). The area under the concentration-time curve (AUC) is a pharmacokinetic parameter that symbolizes overall exposure to a drug, which is correlated with complete cytogenetic and treatment responses to imatinib, as well as its side effects in patients with CML. The limited sampling strategy (LSS) is considered a sufficiently precise and practical method that can be used to estimate pharmacokinetic parameters such as AUC, without the need for frequent, costly, and inconvenient blood sampling. This study aims to investigate the pharmacokinetic parameters of imatinib, develop and validate a reliable and practical LSS for estimating imatinib AUC0-24, and determine the optimum sampling points for predicting the imatinib AUC after the administration of once-daily imatinib in Palestinian patients with CML.

METHOD

Pharmacokinetic profiles, involving six blood samples collected during a 24-h dosing interval, were obtained from 25 Palestinian patients diagnosed with CML who had been receiving imatinib for at least 7 days and had reached a steady-state level. Imatinib AUC0-24 was calculated using the trapezoidal rule, and linear regression analysis was performed to assess the relationship between measured AUC0-24 and concentrations at each sampling time. All developed models were analyzed to determine their effectiveness in predicting AUC0-24 and to identify the optimal sampling time. To evaluate predictive performance, two error indices were employed: the percentage of root mean squared error (% RMSE) and the mean predictive error (% MPE). Bland and Altman plots, along with mountain plots, were utilized to assess the agreement between measured and predicted AUC.

RESULTS

Among the one-timepoint estimations, predicted AUC0-24 based on concentration of imatinib at the eighth hour after administration (C8-predicted AUC0-24) demonstrated the highest correlation with the measured AUC (r2 = 0.97, % RMSE = 6.3). In two-timepoint estimations, the model consisting of C0 and C8 yielded the highest correlation between predicted and measured imatinib AUC (r2 = 0.993 and % RMSE = 3.0). In three-timepoint estimations, the combination of C0, C1, and C8 provided the most robust multilinear regression for predicting imatinib AUC0-24 (r2 = 0.996, % RMSE = 2.2). This combination also outperformed all other models in predicting AUC. The use of a two-timepoint limited sampling strategy (LSS) for predicting AUC was found to be reliable and practical. While C0/C8 exhibited the highest correlation, the use of C0/C4 could be a more practical and equally accurate choice. Therapeutic drug monitoring of imatinib based on C0 can also be employed in routine clinical practice owing to its reliability and practicality.

CONCLUSION

The LSS using one timepoint, especially C0, can effectively predict imatinib AUC. This approach offers practical benefits in optimizing dose regimens and improving adherence. However, for more precise estimation of imatinib AUC, utilizing two- or three-timepoint concentrations is recommended over relying on a single point.

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.

Dose optimization strategy of the tyrosine kinase inhibitors imatinib, dasatinib, and nilotinib for chronic myeloid leukemia: From clinical trials to real-life settings

With the advent of tyrosine kinase inhibitors (TKIs), the treatment prospects of chronic myeloid leukemia (CML) have changed markedly. This innovation can lengthen the long-term survival of patients suffering from CML. However, long-term exposure to TKIs is accompanied by various adverse events (AEs). The latter affect the quality of life and compliance of patients with CML, and may lead to serious disease progression (and even death). Recently, increasing numbers of patients with CML have begun to pursue a dose optimization strategy. Dose optimization may be considered at all stages of the entire treatment, which includes dose reduction and discontinuation of TKIs therapy. In general, reduction of the TKI dose is considered to be an important measure to reduce AEs and improve quality of life on the premise of maintaining molecular responses. Furthermore, discontinuation of TKIs therapy has been demonstrated to be feasible and safe for about half of patients with a stable optimal response and a longer duration of TKI treatment. This review focuses mainly on the latest research of dose optimization of imatinib, dasatinib, and nilotinib in CML clinical trials and real-life settings. We consider dose reduction in newly diagnosed patients, or in optimal response, or for improving AEs, either as a prelude to treatment-free remission (TFR) or as maintenance therapy in those patients unable to discontinue TKIs therapy. In addition, we also focus on discontinuation of TKIs therapy and second attempts to achieve TFR.

Cytochromes P450 2C8 and 3A Catalyze the Metabolic Activation of the Tyrosine Kinase Inhibitor Masitinib

Masitinib is a small molecule tyrosine kinase inhibitor under investigation for the treatment of amyotrophic lateral sclerosis, mastocytosis, and COVID-19. Hepatotoxicity has been reported in some patients while taking masitinib. The liver injury is thought to involve hepatic metabolism of masitinib by cytochrome P450 (P450) enzymes to form chemically reactive, potentially toxic metabolites. The goal of the current investigation was to determine the P450 enzymes involved in the metabolic activation of masitinib in vitro. In initial studies, masitinib (30 μM) was incubated with pooled human liver microsomes in the presence of NADPH and potassium cyanide to trap reactive iminium ion metabolites as cyano adducts. Masitinib metabolites and cyano adducts were analyzed using reversed-phase liquid chromatography-tandem mass spectrometry. The primary active metabolite, N-desmethyl masitinib (M485), and several oxygenated metabolites were detected along with four reactive metabolite cyano adducts (MCN510, MCN524, MCN526, and MCN538). To determine which P450 enzymes were involved in metabolite formation, reaction phenotyping experiments were conducted by incubation of masitinib (2 μM) with a panel of recombinant human P450 enzymes and by incubation of masitinib with human liver microsomes in the presence of P450-selective chemical inhibitors. In addition, enzyme kinetic assays were conducted to determine the relative kinetic parameters (apparent K_m and V_max) of masitinib metabolism and cyano adduct formation. Integrated analysis of the results from these experiments indicates that masitinib metabolic activation is catalyzed primarily by P450 3A4 and 2C8, with minor contributions from P450 3A5 and 2D6. These findings provide further insight into the pathways involved in the generation of reactive, potentially toxic metabolites of masitinib. Future studies are needed to evaluate the impact of masitinib metabolism on the toxicity of the drug in vivo.

Role of Drug Transporters in Elucidating Inter-Individual Variability in Pediatric Chemotherapy-Related Toxicities and Response

Pediatric cancer treatment has evolved significantly in recent decades. The implementation of risk stratification strategies and the selection of evidence-based chemotherapy combinations have improved survival outcomes. However, there is large interindividual variability in terms of chemotherapy-related toxicities and, sometimes, the response among this population. This variability is partly attributed to the functional variability of drug-metabolizing enzymes (DME) and drug transporters (DTS) involved in the process of absorption, distribution, metabolism and excretion (ADME). The DTS, being ubiquitous, affects drug disposition across membranes and has relevance in determining chemotherapy response in pediatric cancer patients. Among the factors affecting DTS function, ontogeny or maturation is important in the pediatric population. In this narrative review, we describe the role of drug uptake/efflux transporters in defining pediatric chemotherapy-treatment-related toxicities and responses. Developmental differences in DTS and the consequent implications are also briefly discussed for the most commonly used chemotherapeutic drugs in the pediatric population.

Population pharmacokinetic modelling of imatinib in healthy subjects receiving a single dose of 400 mg

Purpose

Imatinib is indicated for treatment of CML, GIST, etc. The population pharmacokinetics (popPK) of imatinib in patients under long-term treatment are reported in literature. Data obtained from bioequivalence trials for healthy subjects were used to evaluate the influence of demographic and pharmacogenetic factors on imatinib pharmacokinetics (PK) in a collective without concurrent drugs, organ dysfunction, inflammation etc. In addition, the differences in PK between the healthy subjects and a patient cohort was examined to identify possible disease effects.

Methods

26 volunteers were administered orally with single dose of 400 mg imatinib. 16–19 plasma samples per volunteer were collected from 0.5 up to 72 h post-dose. The popPK was built and post hoc estimates were compared with previously published PK parameters evaluated by non-compartmental analysis in the same cohort. The predictivity of the model for data collected from 40 patients with gastrointestinal stromal tumors at steady state was evaluated.

Results

The popPK was best described by a two-compartment transit model with first-order elimination. No significant covariates were identified, probably due to the small cohort and the narrow range of demographic covariates; CYP3A5 phenotypes appeared to have some influence on the clearance of imatinib. Good agreement between non-compartment and popPK analyses was observed with the differences of the geometric means/ median of PK estimates below 10%. The model indicated lower clearance for patients compared to healthy volunteers (p value < 0.01).

Conclusion

The two-compartment transit model adequately describes the absorption and distribution of imatinib in healthy volunteers. For patients, a lower clearance of imatinib compared to healthy volunteer was estimated by the model. The model can be applied for dose individualization based on trough concentrations assuming no significant differences in absorption between patients and healthy volunteers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-022-04454-y.

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.

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.

Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens

AIMS

This study implements a physiologically-based pharmacokinetic (PBPK) modelling approach to investigate inter-ethnic differences in imatinib pharmacokinetics and dosing regimens.

METHODS

A PBPK model of imatinib was built in the Simcyp Simulator (version 17) integrating in vitro drug metabolism and clinical pharmacokinetic data. The model accounts for ethnic differences in body size and abundance of drug-metabolising enzymes and proteins involved in imatinib disposition. Utility of this model for prediction of imatinib pharmacokinetics was evaluated across different dosing regimens and ethnic groups. The impact of ethnicity on imatinib dosing was then assessed based on the established range of trough concentrations (C_ss,min ).

RESULTS

The PBPK model of imatinib demonstrated excellent predictive performance in describing pharmacokinetics and the attained C_ss,min in patients from different ethnic groups, shown by prediction differences that were within 1.25-fold of the clinically-reported values in published studies. PBPK simulation suggested a similar dose of imatinib (400-600 mg/d) to achieve the desirable range of C_ss,min (1000-3200 ng/mL) in populations of European, Japanese and Chinese ancestry. The simulation indicated that patients of African ancestry may benefit from a higher initial dose (600-800 mg/d) to achieve imatinib target concentrations, due to a higher apparent clearance (CL/F) of imatinib compared to other ethnic groups; however, the clinical data to support this are currently limited.

CONCLUSION

PBPK simulations highlighted a potential ethnic difference in the recommended initial dose of imatinib between populations of European and African ancestry, but not populations of Chinese and Japanese ancestry.

Factors Influencing the Steady-State Plasma Concentration of Imatinib Mesylate in Patients With Gastrointestinal Stromal Tumors and Chronic Myeloid Leukemia

Imatinib mesylate (IM) is the standard treatment for advanced, metastatic gastrointestinal stromal tumors (GISTs) and chronic myeloid leukemia (CML) with a fixed daily standard dosage via the oral route. Interindividual and intraindividual variability in plasma concentrations have been closely linked to the efficacy of IM therapy. Therefore, this review identifies and describes the key factors influencing the plasma concentration of IM in patients with GISTs and CML. We used the following keywords to search the PubMed, EMBASE, Ovid, Wangfang, and CNKI databases to identify published reports: IM, plasma concentration, GISTs, CML, drug combination/interaction, pathology, and genotype/genetic polymorphism, either alone or in combination. This literature review revealed that only 10 countries have reported the mean concentrations of IM in GISTs or CML patients and the clinical outcomes in different ethnic groups and populations. There were totally 24 different gene polymorphisms, which were examined for any potential influence on the steady-state plasma concentration of IM. As a result, some genotype locus made discrepant conclusion. Herein, the more sample capacity, multicenter, long-term study was worthy to carry out. Eleven reports were enumerated on clinical drug interactions with IM, while there is not sufficient information on the pharmacokinetic parameters altered by drug combinations with IM that could help in investigating the actual drug interactions. The drug interaction with IM should be paid more attention in the future research.

Early molecular response in East African Philadelphia chromosome-positive chronic myeloid leukaemia patients treated with Imatinib and barriers to access treatment

Background

Data about haematologic malignancies from Tanzania are sparse. African studies show that chronic myeloid leukaemia (CML) is the most common leukaemia, and registry data display a lower mean age at diagnosis. Prognosis is generally good with tyrosine kinase inhibitors, but the molecular response of Imatinib treatment has never been studied in East Africa, and the outcome remains unknown. This study assessed the early molecular response (MR) as a predictor for long-term outcome and barriers to access treatment.

Methods

A case series of patients with CML from Northern Tanzania documented demographics and laboratory and clinical findings at diagnosis and after 3 months. The regression analysis has been performed on early MR and clinical and demographic variables using the χ2-test. The barriers of potential treatments have been assessed.

Results

A total of 30 patients have been analysed. The mean age was 41 years. All patients had splenomegaly, whereas 16 had hepatomegaly. Complete haematologic response was achieved in 16 and early MR in 9 patients. Hepatomegaly was positively correlated with unfavourable early MR. The average kilometre from home to hospital was 282 km (5-1,158 km). Travel expenses and time investments pose an impediment to treatment.

Conclusion

Patients are younger, and early MR rates are lower compared to other studies. The finding of hepatomegaly as a risk factor for unfavourable early MR was described previously in West Africa. Adherence to therapy is high in the first months of treatment. Furthermore, research is needed to understand the poor MR and the common presentation of hepatomegaly. Outreach clinics might be a solution to reduce impediments to treatment.

Imatinib, sunitinib and pazopanib: From flat-fixed dosing towards a pharmacokinetically guided personalized dose

Tyrosine kinase inhibitors (TKIs) are anti‐cancer drugs that target tyrosine kinases, enzymes that are involved in multiple cellular processes. Currently, multiple oral TKIs have been introduced in the treatment of solid tumours, all administered in a fixed dose, although large interpatient pharmacokinetic (PK) variability is described. For imatinib, sunitinib and pazopanib exposure‐treatment outcome (efficacy and toxicity) relationships have been established and therapeutic windows have been defined, therefore dose optimization based on the measured blood concentration, called therapeutic drug monitoring (TDM), can be valuable in increasing efficacy and reducing the toxicity of these drugs.

In this review, an overview of the current knowledge on TDM guided individualized dosing of imatinib, sunitinib and pazopanib for the treatment of solid tumours is presented. We summarize preclinical and clinical data that have defined thresholds for efficacy and toxicity. Furthermore, PK models and factors that influence the PK of these drugs which partly explain the interpatient PK variability are summarized. Finally, pharmacological interventions that have been performed to optimize plasma concentrations are described. Based on current literature, we advise which methods should be used to optimize exposure to imatinib, sunitinib and pazopanib.

Population pharmacokinetic and pharmacogenetics of imatinib in Chinese patients with chronic myeloid leukemia

Aim: This study aimed to establish a population pharmacokinetic (PPK) model in Chinese patients with chronic myeloid leukemia, and to quantify the effects of pharmacogenetics on pharmacokinetic parameters of imatinib. Methods: A total of 229 plasma concentrations from 170 patients were analyzed. Nonlinear mixed effect model was used to establish the PPK model. Results: A one-compartment model with first-order absorption and first-order elimination adequately describes imatinib pharmacokinetics. Actual bodyweight shows slight effect on the estimated apparent clearance (CL/F) of imatinib in this study population. The final PPK model is: Ka (1/h) = 0.329; CL/F (l/h) = 9.25 × (actual bodyweight/70)0.228; V/F(l) = 222. Conclusion: Actual bodyweight has a slight effect on CL/F. Demographics, physiopathology and pharmacogenetics covariates have no significant effects on imatinib pharmacokinetics.