2014 - Alicante - Spain

PAGE 2014: Drug/Disease modeling - Oncology
María García-Cremades

Pharmacokinetic and Pharmacodynamic analysis of Gemcitabine in pancreatic cancer in mice.

Maria Garcia-Cremades (1), Celine Pitou (2), Philip W Iversen (3), Iñaki F Troconiz (1)

(1)Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Navarra, Pamplona, Navarra, Spain, (2) Global PK/PD & Trial Simulation, Eli Lilly and Company, Windlesham, Surrey, UK, (3) Global Discovery Statistics, Eli Lilly and Company, Indianapolis, Indiana 46285, USA.

Background: Gemcitabine is a nucleoside antimetabolite anticancer pro-drug that shows activity against several solid tumours. Its main indication given as a single agent is to treat pancreatic cancer. Gemcitabine has been chosen as model drug to build a translational approach from early (preclinical) to advanced (clinical) stages in drug development as a part of pillar 3 of working package I (models in oncology) within the IMI7 founded project, Drug Disease Models Resource (DDMoRe).

Objectives: The aim of this study is to develop a tumour growth-response model for the effects of gemcitabine in a xenograft model of pancreatic cancer. Model parameters will be used in next step to establish the translational/multi-scale model.

Methods: Information related to tumour growth was obtained from eleven studies where Gemcitabine was given i.p or p.o to athymic and CD1 nude mice (n=211) inoculated with different human derived pancreatic tumor cell lines (KP4, ASPC1, MIA PACA2, PANC1 and BXPC3). In each study, mice were randomized in two or three groups, the first one receiving saline and the rest receiving gemcitabine under different dosing schedules with dose levels varying from 15 to 200 mg/kg. Tumour volume (mm3) was measured every three or four days. PK parameters were extracted from literature. Typical PK profiles of gemcitabine were used to describe drug response. Tumour volume versus time data were fit using the population approach with NONMEM 7.2. Model evaluation was performed through predictive checks.

Results: Different tumour growth models were tested such as the linear, exponential, and Gompertz. Models for tumour growth and corresponding parameters were found to be cell-line specific. Preliminary analysis of the data corresponding to the active treatment groups reveals that gemcitabine exerts its tumour effects reducing proliferation of tumour cells as well as promoting apoptosis. Delayed tumour shrinkage is seen with respect to time to dosing, and finally dosing schedule appear to be determinant of drug effects.

Conclusions: The modelling exercise which is currently ongoing is based on a database obtained from eleven pre-clinical studies involving a wide range of dose levels and treatment schedules. It is expected that the results from this analysis in terms of model parameters, and/or model derived descriptors can be related to metrics obtained from the outcome of clinical trials.

Acknowledgements: This work was supported by the DDMoRe project.

Reference: PAGE 23 (2014) Abstr 3163 [www.page-meeting.org/?abstract=3163]
Poster: Drug/Disease modeling - Oncology
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