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Lewis Sheiner


2018
Montreux, Switzerland



2017
Budapest, Hungary

2016
Lisboa, Portugal

2015
Hersonissos, Crete, Greece

2014
Alicante, Spain

2013
Glasgow, Scotland

2012
Venice, Italy

2011
Athens, Greece

2010
Berlin, Germany

2009
St. Petersburg, Russia

2008
Marseille, France

2007
København, Denmark

2006
Brugge/Bruges, Belgium

2005
Pamplona, Spain

2004
Uppsala, Sweden

2003
Verona, Italy

2002
Paris, France

2001
Basel, Switzerland

2000
Salamanca, Spain

1999
Saintes, France

1998
Wuppertal, Germany

1997
Glasgow, Scotland

1996
Sandwich, UK

1995
Frankfurt, Germany

1994
Greenford, UK

1993
Paris, France

1992
Basel, Switzerland



Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

Reference:
PAGE 25 (2016) Abstr 5704 [www.page-meeting.org/?abstract=5704]


Poster: Drug/Disease modeling - Oncology


I-16 María García-Cremades A comparison of different model-based approaches to scale preclinical to clinical tumour growth inhibition in gemcitabine-treated pancreatic cancer

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, Spain, (2) Global PK/PD & Pharmacometrics, Eli Lilly and Company, Windlesham, Surrey, UK, (3) Lilly Research laboratories, Eli Lilly and Company, Indianapolis, Indiana 46285, USA.

Objectives: To compare four translational scaling approaches to predict clinical response to gemcitabine treatment in pancreatic cancer patients using preclinical data obtained in xenograft tumour-bearing mice. This work formed part of pillar 3 in working package I (models in oncology) within the IMI7 founded project Drug Disease Models Resource (DDMoRe).

Methods: Pharmacokinetic/Pharmacodynamic models for Gemcitabine describing longitudinal tumour size data have been developed in xenograft mice, for different pancreatic cell lines, and in patients with pancreas cancer (1, 2). The information used to develop the translational simulation exercise comprises for both mice and human: Treatment (dose, dosing schedule), Pharmacokinetics (clearance, volume of distribution, drug exposure), Tumour dynamics (tumour proliferation rate) and Pharmacodynamics (drug-effects & resistance). Based on the above information, the following approaches were evaluated for predictive translational performance:

  1. Direct comparison between preclinical and clinical model parameters.
  2. Direct comparison between preclinical and clinical maximal tumour growth inhibition (TGI) and tumour growth delay (TGD).
  3. Allometric scaling of the pharmacokinetic and pharmacodyamics parameters.
  4. Simulations of tumour growth inhibition in patients using Treatment and Pharmacokinetics, from human and Tumour dynamics and Pharmacodynamics from mice. (3).

Results: Preliminary results show that direct comparison between preclinical and clinical parameters and descriptors is not possible due to the disparity of doses, schedules and structural models used for the trials. Meanwhile descriptors simulated with the combined preclinical-clinical model (such as TGI or TGD), appeared to provide better link; in fact the predicted percentage of TGI coupling patient dosing and PK with mice derived drug effect parameters resulted close with TGI predictions found with the human PKPD model (> 100 % TGI according to (3) in both cases). The results were more promising in the case of the panc1 xenografts than the rest of tumour cells lines implanted in mice.

Conclusions: Currently the preclinical tumor growth inhibition modelling work is often used more qualitatively then quantitatively to predict the clinical results. In this work, we compare different translational approaches which could lead to more quantitative alternatives. The same exercise will also be performed with the gemcitabine-treated ovarian cancer. 



References:
[1] PAGE 23 (2014) Abstr 3163 [www.page-meeting.org/?abstract=3163]
[2] PAGE 24 (2015) Abstr 3343 [www.page-meeting.org/?abstract=3343]
[3] Wong H.et al. Clin Cancer Res 2012; 18:3849-3855