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Comparison of Two Pharmacodynamic Transduction Models for the Analysis of Tumor Therapeutic Responses in Model Systems

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Abstract

Semi-mechanistic pharmacodynamic (PD) models that capture tumor responses to anticancer agents with fidelity can provide valuable insights that could aid in the optimization of dosing regimens and the development of drug delivery strategies. This study evaluated the utility and potential interchangeability of two transduction-type PD models: a cell distribution model (CDM) and a signal distribution model (SDM). The evaluation was performed by simulating dense and sparse tumor response data with one model and analyzing it using the other. Performance was scored by visual inspection and precision of parameter estimation. Capture of tumor response data was also evaluated for a liposomal formulation of paclitaxel in the paclitaxel-resistant murine Colon-26 model. A suitable PK model was developed by simultaneous fitting of literature data for paclitaxel formulations in mice. Analysis of the simulated tumor response data revealed that the SDM was more flexible in describing delayed drug effects upon tumor volume progression. Dense and sparse data simulated using the CDM were fit very well by the SDM, but under some conditions, data simulated using the SDM were fitted poorly by the CDM. Although both models described the dose-dependent therapeutic responses of Colon-26 tumors, the fit by the SDM contained less bias. The CDM and SDM are both useful transduction models that recapitulate, with fidelity, delayed drug effects upon tumor growth. However, they are mechanistically distinct and not interchangeable. Both fit some types of tumor growth data well, but the SDM appeared more robust, particularly where experimental data are sparse.

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Acknowledgements

Support for the studies that provided the data analyzed in this publication was obtained from various sources, including grants R01-CA55251 and R01-CA107570 from the National Cancer Inst., National Institutes of Health, to RMS. JY was supported by unrestricted postdoctoral fellowship funds provided to the University at Buffalo (SUNY) through the UB/Pfizer Strategic Alliance.

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Authors and Affiliations

  1. The Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, 539 Cooke Hall, Amherst, New York, 14260-1200, USA

    Jun Yang, Donald E. Mager & Robert M. Straubinger

  2. New York State Center of Excellence in Bioinformatics and Life Sciences, 701 Ellicott St., Buffalo, New York, 14203-1101, USA

    Donald E. Mager & Robert M. Straubinger

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  1. Jun Yang
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  2. Donald E. Mager
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  3. Robert M. Straubinger
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Correspondence to Robert M. Straubinger.

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Yang, J., Mager, D.E. & Straubinger, R.M. Comparison of Two Pharmacodynamic Transduction Models for the Analysis of Tumor Therapeutic Responses in Model Systems. AAPS J 12, 1–10 (2010). https://doi.org/10.1208/s12248-009-9155-7

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