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Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment
PURPOSE: Adverse effects related to anti-cancer drug treatment influence patient’s quality of life, have an impact on the realized dosing regimen, and can hamper response to treatment. Quantitative models that relate drug exposure to the dynamics of adverse effects have been developed and proven to...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865542/ https://www.ncbi.nlm.nih.gov/pubmed/26915815 http://dx.doi.org/10.1007/s00228-016-2030-4 |
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author | de Vries Schultink, A. H. M. Suleiman, A. A. Schellens, J. H. M. Beijnen, J. H. Huitema, A. D. R. |
author_facet | de Vries Schultink, A. H. M. Suleiman, A. A. Schellens, J. H. M. Beijnen, J. H. Huitema, A. D. R. |
author_sort | de Vries Schultink, A. H. M. |
collection | PubMed |
description | PURPOSE: Adverse effects related to anti-cancer drug treatment influence patient’s quality of life, have an impact on the realized dosing regimen, and can hamper response to treatment. Quantitative models that relate drug exposure to the dynamics of adverse effects have been developed and proven to be very instrumental to optimize dosing schedules. The aims of this review were (i) to provide a perspective of how adverse effects of anti-cancer drugs are modeled and (ii) to report several model structures of adverse effect models that describe relationships between drug concentrations and toxicities. METHODS: Various quantitative pharmacodynamic models that model adverse effects of anti-cancer drug treatment were reviewed. RESULTS: Quantitative models describing relationships between drug exposure and myelosuppression, cardiotoxicity, and graded adverse effects like fatigue, hand-foot syndrome (HFS), rash, and diarrhea have been presented for different anti-cancer agents, including their clinical applicability. CONCLUSIONS: Mathematical modeling of adverse effects proved to be a helpful tool to improve clinical management and support decision-making (especially in establishment of the optimal dosing regimen) in drug development. The reported models can be used as templates for modeling a variety of anti-cancer-induced adverse effects to further optimize therapy. |
format | Online Article Text |
id | pubmed-4865542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-48655422016-05-25 Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment de Vries Schultink, A. H. M. Suleiman, A. A. Schellens, J. H. M. Beijnen, J. H. Huitema, A. D. R. Eur J Clin Pharmacol Review PURPOSE: Adverse effects related to anti-cancer drug treatment influence patient’s quality of life, have an impact on the realized dosing regimen, and can hamper response to treatment. Quantitative models that relate drug exposure to the dynamics of adverse effects have been developed and proven to be very instrumental to optimize dosing schedules. The aims of this review were (i) to provide a perspective of how adverse effects of anti-cancer drugs are modeled and (ii) to report several model structures of adverse effect models that describe relationships between drug concentrations and toxicities. METHODS: Various quantitative pharmacodynamic models that model adverse effects of anti-cancer drug treatment were reviewed. RESULTS: Quantitative models describing relationships between drug exposure and myelosuppression, cardiotoxicity, and graded adverse effects like fatigue, hand-foot syndrome (HFS), rash, and diarrhea have been presented for different anti-cancer agents, including their clinical applicability. CONCLUSIONS: Mathematical modeling of adverse effects proved to be a helpful tool to improve clinical management and support decision-making (especially in establishment of the optimal dosing regimen) in drug development. The reported models can be used as templates for modeling a variety of anti-cancer-induced adverse effects to further optimize therapy. Springer Berlin Heidelberg 2016-02-26 2016 /pmc/articles/PMC4865542/ /pubmed/26915815 http://dx.doi.org/10.1007/s00228-016-2030-4 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Review de Vries Schultink, A. H. M. Suleiman, A. A. Schellens, J. H. M. Beijnen, J. H. Huitema, A. D. R. Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
title | Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
title_full | Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
title_fullStr | Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
title_full_unstemmed | Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
title_short | Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
title_sort | pharmacodynamic modeling of adverse effects of anti-cancer drug treatment |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865542/ https://www.ncbi.nlm.nih.gov/pubmed/26915815 http://dx.doi.org/10.1007/s00228-016-2030-4 |
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