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Developing a robust Quantitative Systems Pharmacology model of adeno-associated virus (AAV) based gene therapy for clinical applications
EP37829
Poster Title: Developing a robust Quantitative Systems Pharmacology model of adeno-associated virus (AAV) based gene therapy for clinical applications
Submitted on 02 Nov 2021
Author(s): Satyajit Rao, Jatin Narula, Zhiwei Zhang, Haobin Luo, Glen Ko, Cynthia J Musante, Nessy Tania
Affiliations: Pfizer Worldwide Research, Development and Medical
This poster was presented at American Conference of Pharmacometrics (ACoP12, November 2021)
Poster Views: 286
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Poster Information
Abstract: Gene therapy provides a breakthrough approach to alter genetic mutations and directly correct underlying disease etiology. Recently, advances in genetic engineering and vector developments have allowed new gene therapies to progress successfully through the clinical drug development process. Established model-informed drug discovery (MIDD) approaches such as PK/PD fall short for estimating exposure-responses in adeno associate virus (AAV) gene therapy. To address this gap, we have developed a Quantitative Systems Pharmacology (QSP) model that incorporates the following mechanistic steps: viral vector distribution to target tissue, receptor binding and internalization, endosomal escape, nuclear translocation, capsid uncoating and transgene expression. This baseline model was calibrated to a compilation of data for AAV8 from literature and from previously published pre-clinical data on AAV8-based liver-targeted gene therapy treatments.

In this presentation, we will focus on the application of the baseline model to clinical programs. Initial clinical translation of the model by accounting for physiological and biodistribution parameter changes could not fully capture the dynamics observed in individual Hemophilia B patient data (published Phase1/2a clinical trial of rAAV-Spark100-hFIX-Padua, PF-06838435). To address this gap, we explored several mechanisms such as allometric scaling of AAV-processing kinetics or slower secretion of Factor IX from hepatocytes. Finally, we will discuss the calibration of the baseline model to published AAV5 and AAV6 mouse data, in order to eventually translate the model for Hemophilia A clinical applications. We analyzed several underlying model assumptions and incorporated different mechanistic hypotheses in order to obtain consistent agreements with observed clinical data. Thus, we present a methodology of developing and calibrating mechanistic models of AAV gene therapy that can be used to aid clinical trial design.
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