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Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer
AIMS: Use of the anti‐tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834588/ https://www.ncbi.nlm.nih.gov/pubmed/26727248 http://dx.doi.org/10.1111/bcp.12878 |
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author | Walsh, Christopher Bonner, Jennifer J. Johnson, Trevor N. Neuhoff, Sibylle Ghazaly, Essam A. Gribben, John G. Boddy, Alan V. Veal, Gareth J. |
author_facet | Walsh, Christopher Bonner, Jennifer J. Johnson, Trevor N. Neuhoff, Sibylle Ghazaly, Essam A. Gribben, John G. Boddy, Alan V. Veal, Gareth J. |
author_sort | Walsh, Christopher |
collection | PubMed |
description | AIMS: Use of the anti‐tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was to develop a physiologically based pharmacokinetic (PBPK) model using a combination of data from the literature and generated from experimental analyses. METHODS: Assays to determine actinomycin D Log P, blood:plasma partition ratio and ABCB1 kinetics were conducted. These data were combined with physiochemical properties sourced from the literature to generate a compound file for use within the modelling‐simulation software Simcyp (version 14 release 1). For simulation, information was taken from two datasets, one from 117 patients under the age of 21 and one from 20 patients aged 16–48. RESULTS: The final model incorporated clinical renal and biliary clearance data and an additional systemic clearance value. The mean AUC(0‐26h) of simulated subjects was within 1.25‐fold of the observed AUC(0‐26h) (84 ng h ml(−1) simulated vs. 93 ng h ml(−1) observed). For the younger age ranges, AUC predictions were within two‐fold of observed values, with simulated data from six of the eight age/dose ranges falling within 15% of observed data. Simulated values for actinomycin D AUC(0‐26h) and clearance in infants aged 0–12 months ranged from 104 to 115 ng h ml(−1) and 3.5–3.8 l h(−1), respectively. CONCLUSIONS: The model has potential utility for prediction of actinomycin D exposure in younger patients and may help guide future dosing. However, additional independent data from neonates and infants is needed for further validation. Physiological differences between paediatric cancer patients and healthy children also need to be further characterized and incorporated into PBPK models. |
format | Online Article Text |
id | pubmed-4834588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-48345882016-05-06 Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer Walsh, Christopher Bonner, Jennifer J. Johnson, Trevor N. Neuhoff, Sibylle Ghazaly, Essam A. Gribben, John G. Boddy, Alan V. Veal, Gareth J. Br J Clin Pharmacol Paediatric Clinical Pharmacology AIMS: Use of the anti‐tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was to develop a physiologically based pharmacokinetic (PBPK) model using a combination of data from the literature and generated from experimental analyses. METHODS: Assays to determine actinomycin D Log P, blood:plasma partition ratio and ABCB1 kinetics were conducted. These data were combined with physiochemical properties sourced from the literature to generate a compound file for use within the modelling‐simulation software Simcyp (version 14 release 1). For simulation, information was taken from two datasets, one from 117 patients under the age of 21 and one from 20 patients aged 16–48. RESULTS: The final model incorporated clinical renal and biliary clearance data and an additional systemic clearance value. The mean AUC(0‐26h) of simulated subjects was within 1.25‐fold of the observed AUC(0‐26h) (84 ng h ml(−1) simulated vs. 93 ng h ml(−1) observed). For the younger age ranges, AUC predictions were within two‐fold of observed values, with simulated data from six of the eight age/dose ranges falling within 15% of observed data. Simulated values for actinomycin D AUC(0‐26h) and clearance in infants aged 0–12 months ranged from 104 to 115 ng h ml(−1) and 3.5–3.8 l h(−1), respectively. CONCLUSIONS: The model has potential utility for prediction of actinomycin D exposure in younger patients and may help guide future dosing. However, additional independent data from neonates and infants is needed for further validation. Physiological differences between paediatric cancer patients and healthy children also need to be further characterized and incorporated into PBPK models. John Wiley and Sons Inc. 2016-02-25 2016-05 /pmc/articles/PMC4834588/ /pubmed/26727248 http://dx.doi.org/10.1111/bcp.12878 Text en © 2016 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of The British Pharmacological Society. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Paediatric Clinical Pharmacology Walsh, Christopher Bonner, Jennifer J. Johnson, Trevor N. Neuhoff, Sibylle Ghazaly, Essam A. Gribben, John G. Boddy, Alan V. Veal, Gareth J. Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer |
title | Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer |
title_full | Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer |
title_fullStr | Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer |
title_full_unstemmed | Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer |
title_short | Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer |
title_sort | development of a physiologically based pharmacokinetic model of actinomycin d in children with cancer |
topic | Paediatric Clinical Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834588/ https://www.ncbi.nlm.nih.gov/pubmed/26727248 http://dx.doi.org/10.1111/bcp.12878 |
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