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Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs

BACKGROUND AND OBJECTIVE: As a result of changes in physiology during pregnancy, the pharmacokinetics (PK) of drugs can be altered. It is unclear whether under- or overexposure occurs in pregnant cancer patients and thus also whether adjustments in dosing regimens are required. Given the severity of...

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Autores principales: Janssen, J. M., Damoiseaux, D., van Hasselt, J. G. C., Amant, F. C. H., van Calsteren, K., Beijnen, J. H., Huitema, A. D. R., Dorlo, T. P. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10386937/
https://www.ncbi.nlm.nih.gov/pubmed/37351792
http://dx.doi.org/10.1007/s40262-023-01263-1
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author Janssen, J. M.
Damoiseaux, D.
van Hasselt, J. G. C.
Amant, F. C. H.
van Calsteren, K.
Beijnen, J. H.
Huitema, A. D. R.
Dorlo, T. P. C.
author_facet Janssen, J. M.
Damoiseaux, D.
van Hasselt, J. G. C.
Amant, F. C. H.
van Calsteren, K.
Beijnen, J. H.
Huitema, A. D. R.
Dorlo, T. P. C.
author_sort Janssen, J. M.
collection PubMed
description BACKGROUND AND OBJECTIVE: As a result of changes in physiology during pregnancy, the pharmacokinetics (PK) of drugs can be altered. It is unclear whether under- or overexposure occurs in pregnant cancer patients and thus also whether adjustments in dosing regimens are required. Given the severity of the malignant disease and the potentially high impact on both the mother and child, there is a high unmet medical need for adequate and tolerable treatment of this patient population. We aimed to develop and evaluate a semi-physiological enriched model that incorporates physiological changes during pregnancy into available population PK models developed from non-pregnant patient data. METHODS: Gestational changes in plasma protein levels, renal function, hepatic function, plasma volume, extracellular water and total body water were implemented in existing empirical PK models for docetaxel, paclitaxel, epirubicin and doxorubicin. These models were used to predict PK profiles for pregnant patients, which were compared with observed data obtained from pregnant patients. RESULTS: The observed PK profiles were well described by the model. For docetaxel, paclitaxel and doxorubicin, an overprediction of the lower concentrations was observed, most likely as a result of a lack of data on the gestational changes in metabolizing enzymes. For paclitaxel, epirubicin and doxorubicin, the semi-physiological enriched model performed better in predicting PK in pregnant patients compared with a model that was not adjusted for pregnancy-induced changes. CONCLUSION: By incorporating gestational changes into existing population pharmacokinetic models, it is possible to adequately predict plasma concentrations of drugs in pregnant patients which may inform dose adjustments in this population.
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spelling pubmed-103869372023-07-31 Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs Janssen, J. M. Damoiseaux, D. van Hasselt, J. G. C. Amant, F. C. H. van Calsteren, K. Beijnen, J. H. Huitema, A. D. R. Dorlo, T. P. C. Clin Pharmacokinet Original Research Article BACKGROUND AND OBJECTIVE: As a result of changes in physiology during pregnancy, the pharmacokinetics (PK) of drugs can be altered. It is unclear whether under- or overexposure occurs in pregnant cancer patients and thus also whether adjustments in dosing regimens are required. Given the severity of the malignant disease and the potentially high impact on both the mother and child, there is a high unmet medical need for adequate and tolerable treatment of this patient population. We aimed to develop and evaluate a semi-physiological enriched model that incorporates physiological changes during pregnancy into available population PK models developed from non-pregnant patient data. METHODS: Gestational changes in plasma protein levels, renal function, hepatic function, plasma volume, extracellular water and total body water were implemented in existing empirical PK models for docetaxel, paclitaxel, epirubicin and doxorubicin. These models were used to predict PK profiles for pregnant patients, which were compared with observed data obtained from pregnant patients. RESULTS: The observed PK profiles were well described by the model. For docetaxel, paclitaxel and doxorubicin, an overprediction of the lower concentrations was observed, most likely as a result of a lack of data on the gestational changes in metabolizing enzymes. For paclitaxel, epirubicin and doxorubicin, the semi-physiological enriched model performed better in predicting PK in pregnant patients compared with a model that was not adjusted for pregnancy-induced changes. CONCLUSION: By incorporating gestational changes into existing population pharmacokinetic models, it is possible to adequately predict plasma concentrations of drugs in pregnant patients which may inform dose adjustments in this population. Springer International Publishing 2023-06-23 2023 /pmc/articles/PMC10386937/ /pubmed/37351792 http://dx.doi.org/10.1007/s40262-023-01263-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Janssen, J. M.
Damoiseaux, D.
van Hasselt, J. G. C.
Amant, F. C. H.
van Calsteren, K.
Beijnen, J. H.
Huitema, A. D. R.
Dorlo, T. P. C.
Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs
title Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs
title_full Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs
title_fullStr Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs
title_full_unstemmed Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs
title_short Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs
title_sort semi-physiological enriched population pharmacokinetic modelling to predict the effects of pregnancy on the pharmacokinetics of cytotoxic drugs
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10386937/
https://www.ncbi.nlm.nih.gov/pubmed/37351792
http://dx.doi.org/10.1007/s40262-023-01263-1
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