Mechanistic multi-scale systems pharmacokinetics model applied for the anticancer drug gemcitabine in pancreatic cancer
Maria Garcia-Cremades (1), Nicola Melillo (2), Paolo Magni (2), Iñaki F Troconiz (1)
(1) Pharmacometrics & System Pharmacology, Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy and Nutrition, University of Navarra, Pamplona 31008, Spain, (2) Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
Objectives: Build a mechanistic multi scale model for gemcitabine based on its molecular metabolic pathway, integrating in vitro- in vivo data, to anticipate the different rate of responses to treatment in pancreatic cancer depending on the accumulation and retention of the gemcitabine active metabolite (dFdCTP).
Methods: A mechanistic network of gemcitabine metabolism pathway was developed using in vitro literature data[1] and was coupled with a physiological pharmacokinetic (PBPK) model. Once the model was built, simulations of different concentration profiles of the active metabolites of gemcitabine in pancreas were generated based on known genetic polymorphisms affecting the enzymes´ expression responsible of gemcitabine metabolism pathway[2]. Analyses were done with Matlab R2016b.
Results: The network is able to describe the time course of extracellular and intracellular metabolites of gemcitabine for two different pancreatic cancer cell lines (normal-PK9 and resistant to gemcitabine-RPK9) using the same set of parameters and including the ratio of protein concentration of the target metabolic enzymes (CDA (1.64), dCK(<0.02)) and transporters (hENT1(1.35))as covariates of the model. Once the system model was integrated with the PBPK model, it was possible to generate plasma concentrations of gemcitabine (AUC 4.43x10-2 mmolxh/L; Cmax 4.07x10-2 mmol/L) and of dFdCTP in pancreas (AUC 2.21x10-5 mmolxh/mL; Cmax 1.05x10-6 mmol/mL) of the range of those reported in literature[3] given the standard dose used for pancreatic cancer patients (3.34 mmol/m2 iv infusion (0.5h)).
Conclusions: A multi scale system pharmacokinetics model characterizing the metabolic pathway of gemcitabine, and predicting the pharmacokinetics of its active metabolite has been developed. The model is able to generate different concentrations of dFdCTP depending on individual’s enzyme levels, which would explain the different rate of responses to gemcitabine treatment observed in patients with pancreatic cancer[4,5,6]. The developed platform has the potential of being used together with PKPD models[7] providing different predictions of clinical response to gemcitabine associated to individual genetic factors affecting, among other processes, the gemcitabine metabolism pathway.
References:
[1]Ohmine, K., Kawaguchi, K., Ohtsuki, S., Motoi, F., Egawa, S., Unno, M., & Terasaki, T. (2012). Attenuation of phosphorylation by deoxycytidine kinase is key to acquired gemcitabine resistance in a pancreatic cancer cell line: targeted proteomic and metabolomic analyses in PK9 cells. Pharmaceutical Research, 29(7), 2006–2016. http://doi.org/10.1007/s11095-012-0728-2
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[6]Bengala, C., Guarneri, V., Giovannetti, E., Lencioni, M., Fontana, E., Mey, V., … Conte, P. F. (2005). Prolonged fixed dose rate infusion of gemcitabine with autologous haemopoietic support in advanced pancreatic adenocarcinoma. British Journal of Cancer, 93(1), 35–40. [7]PAGE 24 (2015) Abstr 3343 [www.page-meeting.org/?abstract=3343]