Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor
International Journal of Applied Mathematics and Computer Science, Tome 15 (2005) no. 4, pp. 517-526.

Voir la notice de l'article provenant de la source Library of Science

The aim of this paper is numerical estimation of pharmacokinetic parameters of the ligands of the macrophage mannose receptor, without knowing a priori the values of these parameters. However, it first requires a model identifiability analysis, which is done by applying an algorithm implemented in a symbolic computation language. It is shown that this step can lead to a direct numerical estimation algorithm. In this way, a first estimate is computed from noisy simulated observations without a priori parameter values. Then the resulting parameter estimate is improved by using the classical least-squares method.
Keywords: nonlinear systems, identifiability, parameter estimation, biological applications
Mots-clés : układ nieliniowy, identyfikowalność, estymacja parametrów, zastosowania biologiczne
@article{IJAMCS_2005_15_4_a8,
     author = {Verdiere, N. and Denis-Vidual, L and Joly-Blanchard, G. and Domurado, D.},
     title = {Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor},
     journal = {International Journal of Applied Mathematics and Computer Science},
     pages = {517--526},
     publisher = {mathdoc},
     volume = {15},
     number = {4},
     year = {2005},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/IJAMCS_2005_15_4_a8/}
}
TY  - JOUR
AU  - Verdiere, N.
AU  - Denis-Vidual, L
AU  - Joly-Blanchard, G.
AU  - Domurado, D.
TI  - Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor
JO  - International Journal of Applied Mathematics and Computer Science
PY  - 2005
SP  - 517
EP  - 526
VL  - 15
IS  - 4
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/IJAMCS_2005_15_4_a8/
LA  - en
ID  - IJAMCS_2005_15_4_a8
ER  - 
%0 Journal Article
%A Verdiere, N.
%A Denis-Vidual, L
%A Joly-Blanchard, G.
%A Domurado, D.
%T Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor
%J International Journal of Applied Mathematics and Computer Science
%D 2005
%P 517-526
%V 15
%N 4
%I mathdoc
%U http://geodesic.mathdoc.fr/item/IJAMCS_2005_15_4_a8/
%G en
%F IJAMCS_2005_15_4_a8
Verdiere, N.; Denis-Vidual, L; Joly-Blanchard, G.; Domurado, D. Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor. International Journal of Applied Mathematics and Computer Science, Tome 15 (2005) no. 4, pp. 517-526. http://geodesic.mathdoc.fr/item/IJAMCS_2005_15_4_a8/

[1] Aubrée-Lecat A., Hervagault C., Delacour C., Beaude C., Bourdillon C. and Rémy M.H. (1989): Direct electrochemical determination of glucose oxidase in biological samples. — Anal. Biochem., Vol. 178, No. 2, pp. 427–430.

[2] Aubrée-Lecat A., Duban M.C., Demignot S., Domurado M., Fournié P. and Domurado D. (1993): Influence of barriercrossing limitations on the amount of macromolecular drug taken up by its target. —J. Pharmacokin. Biopharm., Vol. 21, No. 1, pp. 75–98.

[3] Balazuc A.-M., Lagranderie M., Chavarot P., Pescher P., Roseeuw E., Schacht E., Domurado D. and Marchal G. (2005): In vivo efficiency of targeted norfloxacin against persistent, isoniazid-insensitive, Mycobacterium bovis BCG present in the physiologically hypoxic mouse liver. — Microbes Infect., Vol. 7, No. 7–8, pp. 969–975.

[4] Boulier F., Lazard D., Ollivier F. and Petitot M. (1995): Representation for the radical of a finitely generated differential ideal. — Proc. Int. Symp. Symbolic and Algebraic Computation, ISSAC’95, Montréal, Canada, pp. 158–166.

[5] de Bellefontaine C., Josse F., Domurado M. and Domurado D. (1994): Immunoassay for native enzyme quantification in biological samples. — Appl. Biochem. Biotech., Vol. 48, No. 2, pp. 117–123.

[6] Demignot S., and Domurado D. (1987): Effect of prosthetic sugar groups on the pharmacokinetics of glucose-oxidase. —Drug Design Deliv., Vol. 1, No. 4, pp. 333–348.

[7] Denis-Vidal L., Joly-Blanchard G. and Noiret C. (2001a): Some effective approaches to check the identifiability of uncontrolled nonlinear systems.—Math. Comp. Simul., Vol. 57, No. 1, pp. 35–44.

[8] Denis-Vidal L., Joly-Blanchard G., Noiret C., and Petitot M. (2001b): An algorithm to test identifiability of non-linear systems. — Proc. 5th IFAC Conf. Nonlinear Control Systems, NOLCOS, St. Petersburg, Russia, pp. 174–178.

[9] Denis-Vidal L., Joly-Blanchard G. and Noiret C. (2003): System identifiability (symbolic computation) and parameter estimation (numerical computation). — Numer. Algo., Vol. 34, No. 2–4, pp. 282–292.

[10] Domurado M., Domurado D., Vansteenkiste S., De Marre A. and Schacht E. (1995): Glucose oxidase as a tool to study in vivo the interaction of glycosylated polymers with the mannose receptor of macrophages. — J. Contr. Rel., Vol. 33, No. 1, pp. 115–123.

[11] Gibaldi M. and Perrier D. (1975): Pharmacokinetics. — New York: Marcel Dekker.

[12] Ibrir S. and Diop S. (2004): A numerical procedure for filtering and efficient high-order signal differentiation. — Int. J. Appl. Math. Comput. Sci., Vol. 14, No. 2, pp. 201–208.

[13] Ljung L. and Glad T. (1994): On global identifiability for arbitrary model parametrizations. — Automatica, Vol. 30, No. 2, pp. 265–276.

[14] Marino R. and Tomei P. (1995): Adaptive observers with arbitrary exponential rate of convergence for nonlinear systems. — IEEE Trans. Automat. Contr., Vol. 40, No. 7, pp. 1300–1304.

[15] Roseeuw E., Coessens V., Balazuc A.-M., Lagranderie M., Chavarot P., Pessina A., Neri M.G., Schacht E., Marchal G. and Domurado D. (2003): Synthesis, degradation and antimicrobial properties of targeted macromolecular prodrugs of norfloxacin. — Antimicrob. Agents Chemother., Vol. 47, No. 11, pp. 3435–3441.

[16] Vajda S., Godfrey K.R. and Rabitz H. (1989): Similarity transformation approach to structural identifiability of nonlinear models. — Math. Biosci., Vol. 93, pp. 217–248.