2013 - Glasgow - Scotland

PAGE 2013: Oncology
Paolo Magni

A PK-PD model of tumor growth after administration of an anti-angiogenic agent given alone or in combination therapies in xenograft mice

Massimiliano Germani (1), Maurizio Rocchetti, Francesca Del Bene (1), Nadia Terranova (2), Italo Poggesi (3), Giuseppe De Nicolao (2), Paolo Magni (2)

(1) PK & Modeling, Accelera srl, Nerviano (MI), Italy, (2) Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Italy, (3) Johnson & Johnson, c/o Janssen Cilag S.p.A., Via M. Buonarroti 23, 20093, Cologno M.se, MI, Italy.

Objectives: PK–PD models able to predict the action of anticancer compounds in tumor xenografts have an important impact on drug development. In case of antiangiogenic compounds, many of the most common models are inadequate , as they are based on a cell kill hypothesis, while these drugs mainly act on the tumor vascularization, without a direct tumor cell kill effect. For this reason, a PK–PD model able to describe the tumor growth modulation following treatment with a cytostatic therapy, as opposed to a cytotoxic treatment, is proposed here.

Methods: Experimental Methods
The experimental setting is that of a typical in vivo study routinely performed within several drug development projects using human carcinoma cell lines on xenograft mice [1]. Bevacizumab (Avasin) was given either alone or in combination with a polo-like kinase 1 (PLK1) inhibitor synthesized by Nerviano Medical Sciences (NMS). Average data of tumor weight of control and treated groups were considered.
The mathematical model
Untreated tumor growth was described using an exponential growth phase followed by a linear one. The effect of anti-angiogenic compounds was implemented using an inhibitory effect on the growth function. A combination model was also developed under a ‘no-interaction’ assumption [2] to assess the effect of the combination of bevacizumab with a target-oriented agent. Nonlinear regression techniques were used for estimating the model parameters.

Results: The model successfully captured the tumor growth data following different bevacizumab dosing regimens, allowing to estimate experiment-independent parameters. In combination therapies, the observation of a significant difference between model-predicted (under the no-interaction hypothesis) and observed tumor growth curves [3] was suggestive of the presence of a pharmacological interaction that was further accommodated into the model.

Conclusions: This approach can be used for optimizing the design of preclinical experiments and for investigate the best combination treatments.

This work was supported by the DDMoRe project (www.ddmore.eu).

[1] M. Simeoni, G. De Nicolao, P. Magni, M. Rocchetti, and I. Poggesi. Modeling of human tumor xenografts and dose rationale in oncology. Drug Discovery Today: Technologies, 2012.
[2] P. Magni and N. Terranova and F. {Del Bene} and M. Germani and G. {De Nicolao}. A Minimal Model of Tumor Growth Inhibition in Combination Regimens under the Hypothesis of no Interaction between Drugs. IEEE Trans. on Biomed. Eng.59:2161-2170, 2012
[3] M. Rocchetti, F. Del Bene, M. Germani, F. Fiorentini, I. Poggesi, E. Pesenti, P. Magni, and G. De Nicoalo. Testing additivity of anticancer agents in pre-clinical studies: A PK/PD modelling approach. Eur. J of Cancer, 45(18):3336-3346, 2009.

Reference: PAGE 22 (2013) Abstr 2934 [www.page-meeting.org/?abstract=2934]
Poster: Oncology
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