DocumentCode :
10070
Title :
A Model-Based Pharmacokinetics Characterization Method of Engineered Nanoparticles for Pilot Studies
Author :
Tylcz, Jean-Baptiste ; Bastogne, T. ; Benachour, H. ; Bechet, D. ; Bullinger, E. ; Garnier, H. ; Barberi-Heyob, M.
Author_Institution :
CRAN, Univ. de Lorraine, Vandœ uvre-lès-Nancy, France
Volume :
14
Issue :
4
fYear :
2015
fDate :
Jun-15
Firstpage :
368
Lastpage :
377
Abstract :
Recent developments on engineered multifunctional nanomaterials have opened new perspectives in oncology. But assessment of both quality and safety in nanomedicine requires new methods for their biological characterization. This paper proposes a new model-based approach for the pre-characterization of multifunctional nanomaterials pharmacokinetics in small scale in vivo studies. Two multifunctional nanoparticules, with and without active targeting, designed for photodynamic therapy guided by magnetic resonance imaging are used to exemplify the presented method. It allows to the experimenter to rapidly test and select the most relevant PK model structure planned to be used in the subsequent explanatory studies. We also show that the model parameters estimated from the in vivo responses provide relevant preliminary information about the tumor uptake, the elimination rate and the residual storage. For some parameters, the accuracy of the estimates is accurate enough to compare and draw significant pre-conclusions. A third advantage of this approach is the possibility to optimally refine the in vivo protocol for the subsequent explanatory and confirmatory studies complying with the 3Rs (reduction, refinement, replacement) ethical recommendations. More precisely, we show that the identified model may be used to select the appropriate duration of the MR imaging sessions planned for the subsequent studies. The proposed methodology integrates MRI image processing, continuous-time system identification algorithms and statistical analysis. Except, the choice of the model parameters to be compared and interpreted, most of the processing procedure may be automated to speed up the PK characterization process at an early stage of experimentation.
Keywords :
biomedical MRI; cancer; medical image processing; nanomedicine; nanoparticles; photodynamic therapy; statistical analysis; tumours; 3Rs ethical recommendations; MR imaging sessions; MRI image processing; PK characterization process; PK model structure; active targeting; biological characterization; continuous-time system identification algorithms; elimination rate; in vivo protocol; in vivo responses; magnetic resonance imaging; model parameters; model-based pharmacokinetics characterization method; multifunctional nanomaterial pharmacokinetics; multifunctional nanoparticules; nanomedicine; nanoparticles; oncology; photodynamic therapy; precharacterization; preconclusion; processing procedure; reduction; refinement; replacement; residual storage; statistical analysis; tumor uptake; Brain modeling; Magnetic resonance imaging; Mathematical model; Nanobioscience; Nanoparticles; Rats; Tumors; Cancer; nanomedicine; parameter estimation; pharmacokinetic modeling; system identification;
fLanguage :
English
Journal_Title :
NanoBioscience, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1241
Type :
jour
DOI :
10.1109/TNB.2015.2418792
Filename :
7076604
Link To Document :
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