Völler, S.(1); Boddy, A.V.(2); Boos, J.(3); Krischke, M.(4); Würthwein, G. (4); Hempel G.(1)
(1) Westfälische Wilhelms-Universität, Institut für pharmazeutische und medizinische Chemie, Klinische Pharmazie, Corrensstraße 48, 48149 Münster, Germany, (2) Northern Institute for Cancer Research, Paul O'Gorman Building, Medical School, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK; present address: Faculty of Pharmacy, University of Sydney, Sydney, NSW 2006, Australia, (3) Universitätsklinikum Münster, Klinik und Poliklinik für Kinderheilkunde, Pädiatrische Hämatologie und Onkologie, Funktionsbereich Pädiatrische Hämatologie und Onkologie, Albert-Schweitzer-Straße 33, 48149 Münster, Germany, (4) Universitätsklinikum Münster, Centre for Clinical Trials, ZKS Münster, Von-Esmarch-Straße 62, 48149 Münster, Germany
Objectives: Knowledge on the pharmacokinetics (PK) of doxorubicin, especially in very young children (<2 years), is extremely limited. As doxorubicin was featured on the European Medicines Agency priority list for studies on off-patent paediatric medicinal products, a phase II PK study investigating a possible age-dependency in the clearance (CL) of doxorubicin in children was conducted (EudraCT-Nr: 2009-011454-17). The population PK (popPK) model built within the study was utilized in order to review current dosing concepts in children and to propose a model-based dose recommendation aiming at an equal exposure, calculated as area under the concentration-time-curve (AUC), in patients of all ages.
Methods: A three compartment model for doxorubicin, linearly scaled on BSA, with an additional power function for age on the CL, was developed in NONMEM 7.2®, based on samples from 2 administrations in 101 patients. Sets of 3 different hypothetic children of the same age were generated, one child on the 5th percentile of height (HT) and weight (WT), one child on the 50th percentile of HT and WT and one child on the 95th percentile of HT and WT [1]. The effects of five different currently applied dose adjustment schemes, based on age, WT or a combination thereof, were compared to the dose reduction scheme developed using the popPK model of our recent study. In order to study the effects of the developed scheme in the real-life patients, the empirical Bayesian estimates of the clearance of each study patient were used to calculate the resulting AUCs for the proposed dose reduction.
Results: The comparison of dose reduction schemes in hypothetical patients showed that the cut-off times for the termination of dose reduction were highly variable, e.g. between one year and slightly below three years in children on the 5th percentile of HT and WT. Furthermore, recommended doses in the same child differed up to 33% between schemes. When compared to the model-based recommendation, WT-based dose reductions performed slightly better than proportional reductions (i.e. 67 or 75%). However, our model proposes a continuous dose reduction that also affects children above three years. The application of the dose reduction scheme to our study population shows that AUC is adequately balanced in all age groups.
Conclusion: Current dose reduction schemes in the very young lead to inconsistent exposure. Our model might help to develop a general dose-reduction formula for this population.
References:
[1] Centers for Disease Control and Prevention, National Center for Health Statistics. CDC growth charts: United States. http://www.cdc.gov/growthcharts/. May 30, 2000.
Reference: PAGE 24 (2015) Abstr 3352 [www.page-meeting.org/?abstract=3352]
Poster: Drug/Disease modeling - Paediatrics