The Library

Compartmental modelling of the pharmacokinetics of a breast cancer resistance protein

Tools

Grandjean, Thomas R. B., Chappell, M. J. (Michael J.), Yates, J. W. T., Jones, Kevin, Wood, Gemma and Coleman, Tanya (2011) Compartmental modelling of the pharmacokinetics of a breast cancer resistance protein. Computer Methods and Programs in Biomedicine, Vol.104 (No.2). pp. 81-92. ISSN 0169-2607

Preview

PDF
WRAP_Chappell_0873262-es-060312-cmpb_tgrandjeanpaper.pdf - Submitted Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1524Kb)

Official URL: http://dx.doi.org/10.1016/j.cmpb.2010.08.018

Abstract

A mathematical model for the pharmacokinetics of Hoechst 33342 following administration into a culture medium containing a population of transfected cells (HEK293 hBCRP) with a potent breast cancer resistance protein inhibitor, Fumitremorgin C (FTC), present is described. FTC is reported to almost completely annul resistance mediated by BCRP in vitro. This non-linear compartmental model has seven macroscopic sub-units, with 14 rate parameters. It describes the relationship between the concentration of Hoechst 33342 and FTC, initially spiked in the medium, and the observed change in fluorescence due to Hoechst 33342 binding to DNA. Structural identifiability analysis has been performed using two methods, one based on the similarity transformation/exhaustive modelling approach and the other based on the differential algebra approach. The analyses demonstrated that all models derived are uniquely identifiable for the experiments/observations available. A kinetic modelling software package, namely FACSIMILE (MPCA Software, UK), was used for parameter fitting and to obtain numerical solutions for the system equations. Model fits gave very good agreement with in vitro data provided by AstraZeneca across a variety of experimental scenarios.

Item Type:

Submitted Journal Article

Subjects:

R Medicine > RM Therapeutics. Pharmacology

Divisions:

Faculty of Science > Engineering

Library of Congress Subject Headings (LCSH):

Pharmacokinetics -- Mathematical models, Breast -- Cancer -- Effect of drugs on -- Mathematical models, Antineoplastic agents -- Mathematical models

Journal or Publication Title:

Computer Methods and Programs in Biomedicine

Publisher:

Elsevier Ireland Ltd.

ISSN:

0169-2607

Official Date:

November 2011

Dates:

Date	Event
November 2011	Published

Volume:

Vol.104

Number:

No.2

Page Range:

pp. 81-92

Identification Number:

10.1016/j.cmpb.2010.08.018

Status:

Peer Reviewed

Publication Status:

Published

Access rights to Published version:

Restricted or Subscription Access

References:

[1] Doyle LA, Yang W, Abruzzo LV, Krogmann T, Gao Y, Rishi AK and Ross DD (1998) A multidrug resistance transporter from human MCF-7 breast cancer cells. Proc Natl Acad Sci USA 95:15665-15670.
[2] Lalande ME, Ling V and Miller RG (1981) Hoechst 33342 dye uptake as a probe of membrane permeability changes in mammalian cells. Proc Natl Acad Sci USA 78:363-367.
[3] Paine SW, Parker AJ, Gardiner P, Webborn PJH, and Bailey RJ. (2008). Prediction of the pharmacokinetics of atorvastation, cerivastatin and indomethacin using kinetic models applied to isolated rat hepatocytes. Drug Metabolism and Distribution. 36: 1365-1374
[4] Baker M, and Parton T (2007). Kinetic determinants of hepatic clearance: Plasma protein binding and hepatic uptake. Xenobiotica. 37: 1110-1134.
[5] R. Bellman, K.J. A ˚ stro¨m, On structural identifiability, Math. Biosci. 7 (1970) 329.
[6] K.R. Godfrey, J.J. DiStefano III, Identifiability of model parameters, in: E. Walter (Ed.), Identifiability of
Parametric Models, Pergamon, Oxford, 1987, p. 1 (Chapter 1).
[7] E. Walter (Ed.), Identifiability of Parametric Models, Pergamon, Oxford, 1987.
[8] H. Pohjanpalo, System identifiability based on the power series expansion of the solution, Math. Biosci. 41 (1978) 21.
[9] E.T. Tunali, T.J. Tarn, New results for identifiability of nonlinear systems, IEEE Trans. Automat. Contr. 32 (1987) 146.
[10] S. Vajda, K.R. Godfrey, H. Rabitz, Similarity transformation approach to identifiability analysis of nonlinear compartmental models, Math. Biosci. 93 (1989) 217.
[11] M. Fliess, S.T. Glad, An algebraic approach to linear and nonlinear control, in: H.L. Trentelman, J.C. Willems (Eds.), Essay on Control: Perspectives in the Theory and its Applications, vol. 14, Progress in Systems and Control Theory, Birkha¨user, Boston, 1993.
[12] L. Ljung, T. Glad, On global identifiability for arbitrary model parametrizations, Automatica 30 (1994) 265.
[13] S.Y.A. Cheung, N.D. Evans, M.J. Chappell, K.R. Godfrey, P.J. Smith, R.J. Errington (2008) 'Exploration of the intercellular heterogeneity of topotecan uptake into human breast cancer cells through compartmental modelling' Mathematical Biosciences 213 (2), 119 - 134 (0025-5564)
[14] N.D. Evans, M.J. Chapman, M.J. Chappell, K.R. Godfrey, Identifiability of uncontrolled nonlinear rational systems, Automatica 38 (2002) 1799.
[15] Evans N D, White L J, Chapman M J, Chappell M J, Godfrey K R (2005) 'The structural identifiability of the Susceptible Infected Recovered model with seasonal forcing', Mathematical Biosciences, 194 (2), 175 - 197 (0025-5564).
[16] Facsimile (Version 4.0) Technical Reference. (1995), Laboratory, A.T.H., Didcot, Oxon, uUK.