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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

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Abstract

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.

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Acknowledgements

The authors would like to thank the Palestinian Ministry of Health for providing the laboratory facilities.

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Authors and Affiliations

  1. Department of Pharmacology, Faculty of Pharmacy, University of Monastir, Monastir, Tunisia

    Deema Hilmi Adawi, Nadia Ben Fredj, Ichrack Dridi & Karim Aouam

  2. Department of Pharmacology, Palestinian Ministry of Health, Ramallah, Palestine

    Deema Hilmi Adawi, Ahmad Al-barghouthi, Mustafa Lubada & Mohammad Manasra

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  1. Deema Hilmi Adawi
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Correspondence to Deema Hilmi Adawi.

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Author Contributions

D.A. was responsible for conceiving and designing the study, collecting the blood samples, performing data analysis, interpreting the data, and writing the manuscript; N.B. for critically revising the manuscript and contributing in writing the manuscript; A.A. for contributing in samples analysis HPLC method validation; I.D. for contributing in HPLC method validation and development for imatinib detection; M.L. for contributing in sample analysis and in HPLC method validation; M.M. for facilitating cooperation for patients hospital admission and following up patients; and K.A. for providing critical intellectual input, revising the manuscript, and contributing in writing the manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of Data and Material

The data and materials used in this study are available upon reasonable request. Researchers interested in accessing the data and materials may contact Deema hilmi adawi at deema.hilmi.adawi@gmail.com.

Code Availability

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Ethics Approval

All procedures in this study were conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. The study was approved by the Palestinian ministry of Health on 15 September 2021

Consent to Participate

Informed consent was obtained from all study participants. They were informed about the nature of the study, its objectives, and the use of their data.

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Adawi, D.H., Fredj, N.B., Al-barghouthi, A. et al. 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. Eur J Drug Metab Pharmacokinet 49, 43–55 (2024). https://doi.org/10.1007/s13318-023-00868-y

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