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DDMODEL00000007: DelBene_2009_oncology_in_vitro

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Short description:
PD model describing the effect of anticancer agents on in vitro human A2780 ovarian carcinoma cell growth
PharmML (0.6.1)
  • A model-based approach to the in vitro evaluation of anticancer activity.
  • Del Bene F, Germani M, De Nicolao G, Magni P, Re CE, Ballinari D, Rocchetti M
  • Cancer chemotherapy and pharmacology, 4/2009, Volume 63, Issue 5, pages: 827-836
  • Accelera, Nerviano Medical Sciences, Nerviano (MI), Italy. Universit√† degli Studi di Pavia, Pavia, Italy
  • PURPOSE: The use of in vitro screening tests for characterizing the activity of anticancer agents is a standard practice in oncology research and development. In these studies, human A2780 ovarian carcinoma cells cultured in plates are exposed to different concentrations of the compounds for different periods of time. Their anticancer activity is then quantified in terms of EC(50) comparing the number of metabolically active cells present in the treated and the control arms at specified time points. The major concern of this methodology is the observed dependency of the EC(50) on the experimental design in terms of duration of exposure. This dependency could affect the efficacy ranking of the compounds, causing possible biases especially in the screening phase, when compound selection is the primary purpose of the in vitro analysis. To overcome this problem, the applicability of a modeling approach to these in vitro studies was evaluated. METHODS: The model, consisting of a system of ordinary differential equations, represents the growth of tumor cells using a few identifiable and biologically relevant parameters related to cell proliferation dynamics and drug action. In particular, the potency of the compounds can be measured by a unique and drug-specific parameter that is essentially independent of drug concentration and exposure time. Parameter values were estimated using weighted nonlinear least squares. RESULTS: The model was able to adequately describe the growth of tumor cells at different experimental conditions. The approach was validated both on commercial drugs and discovery candidate compounds. In addition, from this model the relationship between EC(50) and the exposure time was derived in an analytic form. CONCLUSIONS: The proposed approach provides a new tool for predicting and/or simulating cell responses to different treatments with useful indications for optimizing in vitro experimental designs. The estimated potency parameter values obtained from different compounds can be used for an immediate ranking of anticancer activity.
Paolo Magni
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  • Model owner: Paolo Magni
  • Submitted: Sep 25, 2014 5:50:36 PM
  • Last Modified: Oct 10, 2016 7:42:41 PM
Revisions
  • Version: 11 public model Download this version
    • Submitted on: Oct 10, 2016 7:42:41 PM
    • Submitted by: Paolo Magni
    • With comment: Edited model metadata online.
  • Version: 9 public model Download this version
    • Submitted on: May 24, 2016 11:25:29 PM
    • Submitted by: Paolo Magni
    • With comment: Edited model metadata online.
  • Version: 6 public model Download this version
    • Submitted on: Dec 10, 2015 10:16:45 PM
    • Submitted by: Paolo Magni
    • With comment: Edited model metadata online.
  • Version: 2 public model Download this version
    • Submitted on: Sep 25, 2014 5:50:36 PM
    • Submitted by: Paolo Magni
    • With comment: Edited model metadata online.
 
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