Parameter identification of in vivo kinetic models: Limitations and challenges

2013 ◽  
Vol 8 (7) ◽  
pp. 768-775 ◽  
Author(s):  
Joseph J. Heijnen ◽  
Peter J. T. Verheijen
Author(s):  
Pradeep HK ◽  
Girish B ◽  
Nooruddeen K ◽  
Thimmasetty J ◽  
Venkateswarlu BS

The buccal cavity is an alternate route for the administration of the drug. This route gained acceptance as increase in bioavailability is observed due to bypass of first pass metabolism. Solvent casting method was employed for the preparation of the risperidone mucoadhesive patches using different combinations of water soluble and water insoluble polymers using polyvinyl alcohol as a backing layer. Our main objective of this study was to understand the behaviour of water soluble and water insoluble polymers in combination on release pattern. Six different formulations of mucoadhesive patches were evaluated for physicochemical parameters like weight uniformity, content uniformity, thickness uniformity, surface pH, swelling studies, tensile strength, folding endurance, in-vitro drug release, and in-vivo drug absorption. Drug loaded mucoadhesive patches of various polymer bases had shown 35.64 to 72.33% drug release in 30 min in phosphate buffer solution of pH 6.6. In-vitro release data from patches were fit to different equations and kinetic models to explain release profiles. Kinetic models like Hixon-Crowell and Higuchi models were used. The formulation containing HPMC (15Cps) and polyvinyl pyrrolidone was considered as optimized based on the physicochemical and pharmaceutical properties. In-vivo studies in rabbits, carried out with prior permission from IAEC, showed 80.40% of drug release from the optimized patches. In-vivo and in-vitro correlations were found to be good. The drug absorption was found significant from the optimized formulation in healthy rabbits. The structure of the buccal membrane and permeability factors are similar in both human beings and rabbits. Therefore mucoadhesive patches of risperidone may be accepted with the important advantage of reduced risperidone dose.


2010 ◽  
Vol 80 (3) ◽  
pp. 599-617 ◽  
Author(s):  
Anthony C. Dona ◽  
Guilhem Pages ◽  
Robert G. Gilbert ◽  
Philip W. Kuchel

2013 ◽  
Vol 15 (4) ◽  
pp. 456-467 ◽  
Author(s):  
Tina Kroll ◽  
David Elmenhorst ◽  
Andreas Matusch ◽  
Franziska Wedekind ◽  
Angela Weisshaupt ◽  
...  

1991 ◽  
Author(s):  
John A. Pearce ◽  
Wai-Fung Cheong ◽  
Kirit Pandit ◽  
Tom J. McMurray ◽  
Sharon L. Thomsen

Author(s):  
Jan-Lucas Gade ◽  
Carl-Johan Thore ◽  
Björn Sonesson ◽  
Jonas Stålhand

AbstractIn this paper an existing in vivo parameter identification method for arteries is extended to account for smooth muscle activity. Within this method a continuum-mechanical model, whose parameters relate to the mechanical properties of the artery, is fit to clinical data by solving a minimization problem. Including smooth muscle activity in the model increases the number of parameters. This may lead to overparameterization, implying that several parameter combinations solve the minimization problem equally well and it is therefore not possible to determine which set of parameters represents the mechanical properties of the artery best. To prevent overparameterization the model is fit to clinical data measured at different levels of smooth muscle activity. Three conditions are considered for the human abdominal aorta: basal during rest; constricted, induced by lower-body negative pressure; and dilated, induced by physical exercise. By fitting the model to these three arterial conditions simultaneously a unique set of model parameters is identified and the model prediction agrees well with the clinical data.


2019 ◽  
Vol 35 (24) ◽  
pp. 5216-5225 ◽  
Author(s):  
Shyam Srinivasan ◽  
William R Cluett ◽  
Radhakrishnan Mahadevan

Abstract Motivation In kinetic models of metabolism, the parameter values determine the dynamic behaviour predicted by these models. Estimating parameters from in vivo experimental data require the parameters to be structurally identifiable, and the data to be informative enough to estimate these parameters. Existing methods to determine the structural identifiability of parameters in kinetic models of metabolism can only be applied to models of small metabolic networks due to their computational complexity. Additionally, a priori experimental design, a necessity to obtain informative data for parameter estimation, also does not account for using steady-state data to estimate parameters in kinetic models. Results Here, we present a scalable methodology to structurally identify parameters for each flux in a kinetic model of metabolism based on the availability of steady-state data. In doing so, we also address the issue of determining the number and nature of experiments for generating steady-state data to estimate these parameters. By using a small metabolic network as an example, we show that most parameters in fluxes expressed by mechanistic enzyme kinetic rate laws can be identified using steady-state data, and the steady-state data required for their estimation can be obtained from selective experiments involving both substrate and enzyme level perturbations. The methodology can be used in combination with other identifiability and experimental design algorithms that use dynamic data to determine the most informative experiments requiring the least resources to perform. Availability and implementation https://github.com/LMSE/ident. Supplementary information Supplementary data are available at Bioinformatics online


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