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Browsing by Subject "modelling of lung deposition"

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  • Vähä-Mäkilä, Maria (2012)
    The aim of this master`s thesis was to investigate the accuracy of in silico inhalation model to predict pharmacokinetics of orally inhaled products. In literature review special features of the inhalation medication and current statements of medicinal regulatory agencies about bioequivalence (BE) of inhaled products are discussed. The ability of generalized pharmacokinetic BE studies to replace the traditional efficacy studies is a major question in the regulatory agencies. Also the usefulness of published in vitro - in vivo correlations (IVIVC) as an aid for inhaled product development in pharmaceutical industry is considered. Furthermore the most commonly used in silico lung deposition models and their properties are presented. In the experimental part a generic in silico inhalation model was constructed using a proper software and Orion Oyj`s in vitro and in vivo research materials on certain dry powder inhaler (DPI) products. Based on in vitro knowledge the aim of modeling was to predict the pharmacokinetic behavior of a therapeutic drug used in inhaled products. Also the applicability as a tool in clinical study design of inhaled products was estimated. Inhalation model consisted of two separate modeling parts utilizing primary in vitro characterization results of DPI products. Lung deposition of products was predicted with the ARLA (The Aerosol Research Laboratory of Alberta) respiratory deposition calculator available to the public while drugspecific pharmacokinetics was simulated using constructed Stella model (isee systems). ARLA lung deposition model takes into account several factors affecting the final lung dose of medical aerosol. Those include aerosol formulation and the dimensions of the device, as well as breathing conditions and inhalation mode. A rough sensitivity analysis was carried out with ARLA considering the effect of these factors on predicted lung deposition fractions. The predicted plasma concentration profiles, Cmax and AUCt values of the model drug were markedly lower than the experimental values. ARLA deposition model predicted moderately the order of systemic drug exposure obtained with different DPI products. The inhalation model built in the experimental part needs to be refined using more comprehensive and trustable source and reference material. The role of clinical BE studies in the marketing approval of generic inhalation product will be important because currently in silico predictions are still under development.