Therapeutic Drug Monitoring of Kinase Inhibitors in Oncology

Although kinase inhibitors (KI) frequently portray large interpatient variability, a ‘one size fits all’ regimen is still often used. In the meantime, relationships between exposure-response and exposure-toxicity have been established for several KIs, so this regimen could lead to unnecessary toxicity and suboptimal efficacy. Dose adjustments based on measured systemic pharmacokinetic levels—i.e., therapeutic drug monitoring (TDM)—could therefore improve treatment efficacy and reduce the incidence of toxicities. Therefore, the aim of this comprehensive review is to give an overview of the available evidence for TDM for the 77 FDA/EMA kinase inhibitors currently approved (as of July 1st, 2023) used in hematology and oncology. We elaborate on exposure-response and exposure-toxicity relationships for these kinase inhibitors and provide practical recommendations for TDM and discuss corresponding pharmacokinetic targets when possible.</p

Feasibility of therapeutic drug monitoring of sorafenib in patients with liver or thyroid cancer

Introduction: Sorafenib is a tyrosine-kinase inhibitor approved for the treatment of renal cell carcinoma, hepatocellular carcinoma, thyroid carcinoma, and desmoid fibromatosis. As high inter-individual variability exists in exposure, there is a scientific rationale to pursue therapeutic drug monitoring (TDM). We investigated the feasibility of TDM in patients on sorafenib and tried to identify sub-groups in whom pharmacokinetically (PK) guided-dosing might be of added value. Methods: We included patients who started on sorafenib (between October 2017 and June 2020) at the recommended dose of 400 mg BID or with a step-up dosing schedule. Plasma trough levels (Ctrough) were measured at pre-specified time-points. Increasing the dose was advised if Ctrough was below the target of 3750 ng/mL and toxicity was manageable. Results: A total of 150 samples from 36 patients were collected. Thirty patients (83 %) had a Ctrough below the prespecified target concentration at a certain time point during treatment. Toxicity from sorafenib hampered dosing according to target Ctrough in almost half of the patients. In 11 patients, dosing was adjusted based on Ctrough. In three patients, this resulted in an adequate Ctrough without additional toxicity four weeks after the dose increase. In the remaining eight patients, dose adjustment based on Ctrough did not result in a Ctrough above the target or caused excessive toxicity. Conclusions: TDM for sorafenib is not of added value in daily clinical practice. In most cases, toxicity restricts the possibility of dose escalations.</p

Pharmacokinetic boosting of olaparib:A randomised, cross-over study (PROACTIVE-study)

Background: Pharmacokinetic (PK) boosting is the intentional use of a drug-drug interaction to enhance systemic drug exposure. PK boosting of olaparib, a CYP3A-substrate, has the potential to reduce PK variability and financial burden. The aim of this study was to investigate equivalence of a boosted, reduced dose of olaparib compared to the non-boosted standard dose. Methods: This cross-over, multicentre trial compared olaparib 300 mg twice daily (BID) with olaparib 100 mg BID boosted with the strong CYP3A-inhibitor cobicistat 150 mg BID. Patients were randomised to the standard therapy followed by the boosted therapy, or vice versa. After seven days of each therapy, dense PK sampling was performed for noncompartmental PK analysis. Equivalence was defined as a 90% Confidence Interval (CI) of the geometric mean ratio (GMR) of the boosted versus standard therapy area under the plasma concentration-time curve (AUC0–12 h) within no-effect boundaries. These boundaries were set at 0.57–1.25, based on previous pharmacokinetic studies with olaparib capsules and tablets. Results: Of 15 included patients, 12 were eligible for PK analysis. The GMR of the AUC0–12 h was 1.45 (90% CI 1.27–1.65). No grade ≥3 adverse events were reported during the study. Conclusions: Boosting a 100 mg BID olaparib dose with cobicistat increases olaparib exposure 1.45-fold, compared to the standard dose of 300 mg BID. Equivalence of the boosted olaparib was thus not established. Boosting remains a promising strategy to reduce the olaparib dose as cobicistat increases olaparib exposure Adequate tolerability of the boosted therapy with higher exposure should be established.</p

Hot flashes are not predictive for serum concentrations of tamoxifen and its metabolites

Background: Tamoxifen has dramatically reduced the recurrence and mortality rate of estrogen receptor positive breast cancer. However, the efficacy of tamoxifen varies between individuals and 40% of patients will have a recurrence despite adjuvant tamoxifen treatment. Factors that predict tamoxifen efficacy would be helpful for optimizing treatment. Serum concentrations of the active metabolite, endoxifen, may be positively related to treatment outcome. In addition, hot flashes are suggested to be positively associated with tamoxifen treatment outcome. Methods: We investigated in a series of 109 patients whether the frequency and severity of hot flashes were related to concentrations of tamoxifen and its metabolites. A serum sample of all patients was analyzed for the concentration of tamoxifen, N-desmethyltamoxifen, endoxifen and 4-hydroxytamoxifen, as well as for estradiol concentrations and several single nucleotide polymorphisms in CYP2D6. Additionally, these patients completed a questionnaire concerning biometric data and treatment side effects. Results: We found no evidence supporting an association between concentrations of tamoxifen or metabolites and either the frequency or severity of hot flashes in the covariate unadjusted analyses. However, including interactions with menopausal status and pre-treatment hot flash (PTHF) history indicated that post-menopausal women with PTHF experienced an increasing frequency of hot flashes with increasing serum concentrations of tamoxifen and its metabolites. This finding was not altered when adjusting for potential confounding factors (duration of tamoxifen treatment, CYP2D6 phenotype, estradiol serum concentration, age and body mass index). In addition we observed a positive association between body mass index and both hot flash frequency (p = 0.04) and severity (p < 0.0001). We also observed that patients with lower estradiol levels reported more severe hot flashes (p = 0.02). Conclusions: No univariate associations were observed between concentrations of active tamoxifen metabolites and either the frequency or severity of hot flashes during treatment. However, the frequency of hot flashes may be exacerbated by higher serum concentrations of tamoxifen and its metabolites in post-menopausal women with a history of hot flashes prior to tamoxifen treatment

Nonlinear protein binding of phenytoin in clinical practice: Development and validation of a mechanistic prediction model

Item does not contain fulltextAIMS: To individualize treatment, phenytoin doses are adjusted based on free concentrations, either measured or calculated from total concentrations. As a mechanistic protein binding model may more accurately reflect the protein binding of phenytoin than the empirical Winter-Tozer equation that is routinely used for calculation of free concentrations, we aimed to develop and validate a mechanistic phenytoin protein binding model. METHODS: Data were extracted from routine clinical practice. A mechanistic drug protein binding model was developed using nonlinear mixed effects modelling in a development dataset. The predictive performance of the mechanistic model was then compared with the performance of the Winter-Tozer equation in 5 external datasets. RESULTS: We found that in the clinically relevant concentration range, phenytoin protein binding is not only affected by serum albumin concentrations and presence of severe renal dysfunction, but is also concentration dependent. Furthermore, the developed mechanistic model outperformed the Winter-Tozer equation in 4 out of 5 datasets in predicting free concentrations in various populations. CONCLUSIONS: Clinicians should be aware that the free fraction changes when phenytoin exposure changes. A mechanistic binding model may facilitate prediction of free phenytoin concentrations from total concentrations, for example for dose individualization in the clinic

Family care among elderly Chinese immigrants in Australia : a quality of life study

BACKGROUND: The objectives of this study were to evaluate the plasma concentrations of the tyrosine kinase inhibitors (TKIs), imatinib, erlotinib, and sunitinib, in a cohort of patients with cancer in routine clinical practice and to find the possible factors related to plasma concentrations below the target level. METHODS: An observational study was performed in an unselected cohort of patients using TKIs for cancer treatment. Randomly timed plasma samples were drawn together with regular laboratory investigations during routine outpatient clinic visits. The plasma concentrations of TKIs were determined using a validated high-performance liquid chromatography coupled with tandem mass spectrometry detection method. Trough concentrations were estimated using the interval between the last dose intake and blood sampling and the mean elimination half-life of the TKIs and were compared with target trough concentrations. Outpatient medical records were reviewed to collect data on patient- and medication-related factors that could have contributed to the variation in TKI plasma concentrations. RESULTS: Only 26.8%, 88.9%, and 51.4% of the calculated trough plasma concentrations of imatinib, erlotinib, and sunitinib samples, respectively, reached the predefined target concentration (imatinib: 1100 ng/mL, erlotinib: 500 ng/mL, and sunitinib: 50 ng/mL). Interpatient variability was high with coefficients of variation of 39.1%, 40.1%, and 29.2% for imatinib, erlotinib, and sunitinib, respectively. High variation in plasma concentrations could only partly be explained by patient- or medication related factors. CONCLUSIONS: Almost half of the plasma concentrations in the outpatient population seemed to be below the target level with a risk of treatment failure. It is not possible to predict which patients are at a risk of plasma concentrations below the target level based on patient- or medication-related factors. Thus, therapeutic drug monitoring could play a crucial role in routine cancer care to identify patients that are in need of individual adjusted dosages. Further research is required to investigate the safety and efficacy of therapeutic drug monitoring

Quantification of sunitinib and N-desethyl sunitinib in human EDTA plasma by liquid chromatography coupled with electrospray ionization tandem mass spectrometry: validation and application in routine therapeutic drug monitoring

Item does not contain fulltextBACKGROUND: Given the low therapeutic index, the large interindividual variability in systemic exposure and the positive exposure-efficacy relationship of sunitinib, there is a rationale for therapeutic drug monitoring (TDM) of sunitinib. To support TDM, a method for determination of sunitinib and its active metabolite (N-desethyl sunitinib) has been developed and validated. METHODS: For determination of sunitinib and N-desethyl sunitinib in human EDTA plasma samples, high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) was used. Validation experiments according to Food and Drug Administration guidelines were performed. In addition, the results of 25 analytical runs with 58 patient samples using 8 calibrators and 3 levels of quality control (QC) samples per analysis were compared with the results of analyses using only 3 calibrators and 1 QC sample to accelerate sample turnaround time. The method comparison experiment was performed according to international guidelines. RESULTS: The HPLC-MS/MS method was validated over a linear range from 2.5 to 500 ng/mL using 50 muL plasma volumes, with good intra- and interassay accuracy and precision. In addition, the mean of the absolute differences between the compared methods was only -0.66 ng/mL (mean of relative differences, -0.85%), which is not a clinically relevant difference. CONCLUSIONS: This method has been applied successfully for routine TDM purposes for patients treated with sunitinib. Moreover, reliable results with a rapid turnaround time were obtained when performing a short analytical run containing only 3 calibrators and 1 QC sample

Method development and validation for the quantification of dasatinib, erlotinib, gefitinib, imatinib, lapatinib, nilotinib, sorafenib and sunitinib in human plasma by liquid chromatography coupled with tandem mass spectrometry

To support pharmacokinetic-guided dosing in individual patients, a fast and accurate method for simultaneous determination of anticancer tyrosine kinase inhibitors (TKIs) dasatinib, erlotinib, gefitinib, imatinib, lapatinib, nilotinib, sorafenib and sunitinib in human plasma was developed using high-performance liquid chromatography and detection with tandem mass spectrometry (HPLC-MS/MS). Stable isotopically labeled compounds of the eight different TKIs were used as internal standards. Plasma proteins were precipitated and an aliquot of supernatant was directly injected onto a reversed phase chromatography system consisting of a Gemini C18 column (50 x 2.0 mm i.d., 5.0 microm particle size) and then compounds were eluted with a gradient. The outlet of the column was connected to a triple quadrupole mass spectrometer with electrospray interface. Ions were detected in the positive multiple reaction monitoring mode. This method was validated over a linear range from 20.0 to 10,000 ng/mL for erlotinib, gefitinib, imatinib, lapatinib, nilotinib and sorafenib, and from 5.00 to 2500 ng/mL for dasatinib and sunitinib. Results from the validation study demonstrated good intra- and inter-assay accuracy (<13.1%) and precision (10.0%) for all analytes. This method was successfully applied for routine therapeutic drug monitoring purposes in patients treated with the investigated TKIs. Copyright (c) 2012 John Wiley & Sons, Ltd

Impact of CYP3A4*22 on Pazopanib Pharmacokinetics in Cancer Patients

Contains fulltext : 203020.pdf (publisher's version ) (Open Access

Is age just a number? A population pharmacokinetic study of gemcitabine

PURPOSE: Pharmacokinetic exposure to gemcitabine and its metabolite, 2',2'-difluorodeoxyuridine (dFdU), might be altered in elderly compared to their younger counterparts. It is unknown if age-based dose adjustments are necessary to reduce the development of treatment-induced adverse events. The aim of this study was to assess the impact of age on the pharmacokinetics of gemcitabine and dFdU. METHODS: Pharmacokinetic sampling following a flexible limited sampling strategy was performed in patients ≥ 70 years after gemcitabine infusion. The data were supplemented with pharmacokinetic data in patients included in four previously conducted clinical trials. Nonlinear mixed effects modelling was performed on the pooled dataset to assess the impact of age on the pharmacokinetics of gemcitabine and dFdU. RESULTS: In total, pharmacokinetic data were available of 197 patients, of whom 83 patients were aged ≥ 70 years (42%). A two-compartment model for both gemcitabine and dFdU with linear clearances from the central compartments described the data best. Age, tested as continuous and categorical (< 70 years versus ≥ 70 years) covariate, did not statistically affect the pharmacokinetics of gemcitabine and dFdU. CONCLUSION: Age was not of influence on the pharmacokinetics of gemcitabine or its metabolite, dFdU. Age-related dose adjustments for gemcitabine based on pharmacokinetic considerations are not recommended. TRIAL REGISTRATION NUMBER: NL39647.048.12, registered on May 3rd 2012