Mining Small Routine Clinical Data: A Population Pharmacokinetic Model and Optimal Sampling Times of Capecitabine and its Metabolites
Keywords: 
Materias Investigacion::Ciencias de la Salud::Química médica
Therapeutic drug monitoring
Capecitabine
Metabolites
Pharmacokinetic model
Issue Date: 
2019
Publisher: 
University of Alberta Libraries
Publisher Version: 
ISSN: 
1482-1826
Note: 
This is an open access journal with free of charge submission and non-commercial download. At the time of submission, authors will be asked to transfer the copyright to the accepted article to the Journal of Pharmacy and Pharmaceutical Sciences. The author may purchase the copyright for $500 upon which he/she will have the exclusive copyright to the article. Nevertheless, acceptance of a manuscript for publication in the Journal is with the authors' approval of the terms and conditions of the Creative Commons copyright license Creative Common license (Attribution-ShareAlike) License for non-commercial uses.
Citation: 
Oyaga-Iriarte, E. (Esther); Insausti, A. (Asier); Bueno, L. (Lorea); et al. "Mining Small Routine Clinical Data: A Population Pharmacokinetic Model and Optimal Sampling Times of Capecitabine and its Metabolites". Journal of Pharmacy & Pharmaceutical Sciences. 22, 2019, 112 - 121
Abstract
Purpose: The present study was performed to demonstrate that small amounts of routine clinical data allow to generate valuable knowledge. Concretely, the aims of this research were to build a joint population pharmacokinetic model for capecitabine and three of its metabolites (5-DFUR, 5-FU and 5-FUH2) and to determine optimal sampling times for therapeutic drug monitoring. Methods: We used data of 7 treatment cycles of capecitabine in patients with metastatic colorectal cancer. The population pharmacokinetic model was built as a multicompartmental model using NONMEM and was internally validated by visual predictive check. Optimal sampling times were estimated using PFIM 4.0 following D-optimality criterion. Results: The final model was a multicompartmental model which represented the sequential transformations from capecitabine to its metabolites 5-DFUR, 5-FU and 5-FUH2 and was correctly validated. The optimal sampling times were 0.546, 0.892, 1.562, 4.736 and 8 hours after the administration of the drug. For its correct implementation in clinical practice, the values were rounded to 0.5, 1, 1.5, 5 and 8 hours after the administration of the drug. Conclusions: Capecitabine, 5-DFUR, 5-FU and 5-FUH2 can be correctly described by the joint multicompartmental model presented in this work. The aforementioned times are optimal to maximize the information of samples. Useful knowledge can be obtained for clinical practice from small databases.

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