Genotype-driven pharmacokinetic simulations of warfarin levels in Puerto Ricans

Author:

Reyes-González Stephanie1,de las Barreras Camila2,Reynaldo Gledys2,Rodríguez-Vera Leyanis2,Vlaar Cornelis1,Mejias Vilmali Lopez34,Monbaliu Jean-Christophe M.5,Stelzer Torsten14,Mangas Victor67,Duconge Jorge1

Affiliation:

1. Department of Pharmaceutical Sciences , School of Pharmacy, University of Puerto Rico – Medical Sciences Campus , San Juan 00936, Puerto Rico , USA

2. Institute of Pharmacy and Foods, University of Havana , Havana , Cuba

3. Department of Chemistry , University of Puerto Rico – Río Piedras Campus , San Juan , USA

4. Crystallization Design Institute, Molecular Sciences Research Center, University of Puerto Rico , San Juan , USA

5. Center for Integrated Technology and Organic Synthesis, MolSys Research Unit, University of Liège , Liège (Sart Tilman) , Liège , Belgium

6. Department of Pharmacy and Pharmaceutical Technology and Parasitology , University of Valencia , Valencia , Spain

7. Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia , Valencia , Spain

Abstract

Abstract Objectives The inter-individual variability of warfarin dosing has been linked to genetic polymorphisms. This study was aimed at performing genotype-driven pharmacokinetic (PK) simulations to predict warfarin levels in Puerto Ricans. Methods Analysis of each individual dataset was performed by one-compartmental modeling using WinNonlin®v6.4. The k e of warfarin given a cytochrome P450 2C9 (CYP2C9) genotype ranged from 0.0189 to 0.0075 h−1. K a and V d parameters were taken from literature. Data from 128 subjects were divided into two groups (i.e., wild-types and carriers) and statistical analyses of PK parameters were performed by unpaired t-tests. Results In the carrier group (n=64), 53 subjects were single-carriers and 11 double-carriers (i.e., *2/*2, *2/*3, *2/*5, *3/*5, and *3/*8). The mean peak concentration (Cmax) was higher for wild-type (0.36±0.12 vs. 0.32±0.14 mg/L). Likewise, the average clearance (CL) parameter was faster among non-carriers (0.22±0.03 vs. 0.17±0.05 L/h; p=0.0001), with also lower area under the curve (AUC) when compared to carriers (20.43±6.97 vs. 24.78±11.26 h mg/L; p=0.025). Statistical analysis revealed a significant difference between groups with regard to AUC and CL, but not for Cmax. This can be explained by the variation of k e across different genotypes. Conclusions The results provided useful information for warfarin dosing predictions that take into consideration important individual PK and genotyping data.

Publisher

Walter de Gruyter GmbH

Subject

Pharmacology (medical)

Reference22 articles.

1. IBM Watson Health, Greenwood Village, Colorado, USA. Warfarin. In: IBM Micromedex® 2.0. 2015 (electronic version). Available from: https://www.micromedexsolutions.com/ [Accessed 2 July 2020].

2. Li, J, Wang, S, Barone, J, Malone, B. Warfarin pharmacogenomics. Pharm Ther 2009;34:422–7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2799123/.

3. Aitken, M, Kleinrock, M, Declining medicine use and costs: for better or worse? A review of the use of medicines in the United States in 2012. In: Appendix 3: top medicines by prescriptions. NJ, USA: IMS Institute for Healthcare Informatics; 2013:43 p. Available from: https://www.sefap.it/web/upload/2012_USMedicines_Report.pdf [Accessed 2 July 2020].

4. Moore, TJ, Cohen, MRFC. Anticoagulants the leading reported drug risk in 2011. Inst Safe Medicat Pract; 2012. Available from: https://www.ismp.org/quarterwatch/anticoagulants-reported-drug-risk [Accessed 2 July 2020].

5. Holford, NH. Clinical PK and pharmacodynamics of warfarin. Understanding the dose-effect relationship. Clin Pharmacokinet 1986;11:483–504. https://doi.org/10.2165/00003088-198611060-00005.

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