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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.
Afiliación
  • Walsh C; Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK.
  • Bonner JJ; Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK.
  • Johnson TN; Simcyp Limited (a Certara Company), Sheffield, UK.
  • Neuhoff S; Simcyp Limited (a Certara Company), Sheffield, UK.
  • Ghazaly EA; Barts Cancer Institute, Queen Mary University of London, London, UK.
  • Gribben JG; Barts Cancer Institute, Queen Mary University of London, London, UK.
  • Boddy AV; Faculty of Pharmacy, The University of Sydney, NSW, 2006, Australia.
  • Veal GJ; Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK.
Br J Clin Pharmacol ; 81(5): 989-98, 2016 May.
Article en En | MEDLINE | ID: mdl-26727248
ABSTRACT

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, bloodplasma 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 AUC0-26h of simulated subjects was within 1.25-fold of the observed AUC0-26h (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 AUC0-26h 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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Dactinomicina / Antibióticos Antineoplásicos / Neoplasias Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Animals / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: Br J Clin Pharmacol Año: 2016 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Dactinomicina / Antibióticos Antineoplásicos / Neoplasias Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Animals / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: Br J Clin Pharmacol Año: 2016 Tipo del documento: Article País de afiliación: Reino Unido