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We represent a community with a shared interest in data analysis using the population approach.


2005
   Pamplona, Spain

Application of Pharmacokinetic/Pharmacodynamic Concepts to Modeling in Gene Therapy

Pedro Berraondo1, Gloria González-Aseguinolaza1, Iñaki F. Trocóniz2

1, Laboratory of Gene Therapy of Viral Hepatitis. Division of Hepatology and Gene Therapy. Center for Applied Medical Research (CIMA). University of Navarra; 2, Department of Pharmacy; School of Pharmacy; University of Navarra; Pamplona; Spain

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Introduction: Gene therapy seen as a tool for drug delivery implies accessibility to the site of action, release of the active components and their coupling with the proper structures within the nucleus, and finally response induction. Those processes are similar to the absorption/disposition and response-related (receptor binding, signal transduction, homeostasis, etc) processes that can be identified and quantified after more traditional therapy using pharmacokinetic/pharmacodynamic modeling. However, there are differences such as that during gene therapy “drug disposition” is not measured and usually the induced responses last for very long periods.

Methods: Models using the indirect response, precursor, and push-pull concepts as the main platform, and resembling different possible mechanisms of transduction were fitted to the response data. Response data consisted on Luciferase activity measured in vivo in mice liver over an one month period after simultaneous administration of three recombinant plasmids via tail vein. Three different groups were analyzed: 1- pLuc+control plasmid+ pIFN-alpha, 2- pLuc+pIFN-alpha+ pDcR, 3- pLuc+ placZ+ pIFN-alpha.

Results: More than one model provided a reasonable description of the data, which was charaterized in general by an intial burst followed by a pseudo steady-state in response. Computer simulations helped to identify design conditions maximizing differences in performance between model candidates.

Conclusion: Applying semimechanistic modelling to this type of data allowed to discriminate between possible mechanisms and to design future studies to adquire insight in the transduction processes.



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