Now showing 1 - 1 of 1
  • Publication
    Dissolution Kinetics of a BCS Class II Active Pharmaceutical Ingredient: Experimental & Modelling Approaches
    (University College Dublin. School of Chemical and Bioprocess Engineering, 2021) ;
    0000-0001-7531-8281
    The dissolution processes of active pharmaceutical ingredient (API) crystals have been extensively studied in the pharmaceutical industry, as they have a significant impact upon the bioavailability of drugs within the body. Although much experimental work has been conducted and many models have been established, none of the models comprehensively describe the dissolution process of the API. Moreover, the impact of physiochemical properties on the dissolution of the API is not well understood. A deeper understanding of dissolution behaviour and of the factors affecting the dissolution process is critical to the design, evaluation, control and therapeutic efficacy of solid dosage forms. Hence in this thesis, the dissolution processes of API crystals were investigated using both experimental and modelling approaches. A BCS Class II drug, ibuprofen, characterized by a relatively low solubility but high permeability compared to other drugs was used as a model compound to investigate dissolution kinetics. The effect of physicochemical properties of the particles on the dissolution kinetics was also investigated. Firstly, an ibuprofen preparation protocol for dissolution was established. Different ibuprofen crystals with tailored solid-state characteristics (such as crystal morphology and size distribution) were prepared by cooling crystallization. The crystallization process was monitored in situ by process analytical techniques (PATs) such as FBRM, PVM and ATR-FTIR. The properties of the obtained crystalline products were also characterized by off-line techniques such as high performance liquid chromatography (HPLC), microscope, scanning electron microscope (SEM), powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), and Malvern Mastersizer, etc. A laboratory methodology for the dissolution processes of the obtained IBU crystals was then developed. UV and ATR-FTIR spectroscopic techniques were employed to measure the solute concentration and a FBRM probe was applied to track the change of the particle size and population profile during dissolution. The influence of the initial undersaturation ratio, agitation rate, crystal morphology and particle size on the dissolution were examined. Variations in the dissolution rate were observed, from which two distinct dissolution mechanisms during the dissolution process were proposed. Eight mathematical models which have been typically employed to quantify the dissolution of immediate and modified release dosage forms, including the zero-order, first-order kinetics, Weibull, Higuchi, Hixson-Crowell, Korsmeyer-Peppas, Baker-Lonsdale and Hopfenberg models, were used to correlate the dissolution profiles of ibuprofen crystals. The dissolution parameters of each model were determined and the simulation accuracies of the different models were evaluated by comparing simulated and experimental results. It was found that the Weibull, Korsmeyer-Peppas and first-order kinetics models provided the most accurate results, suggesting that these models may be successfully applied to the dissolution of API powders in both API processing and drug product performance analysis. A diffusion-based model which can be used to predict non-sink circumstances was next devised to study the dissolution kinetics of ibuprofen. Variations of the model were created to compare the accuracy of simulation results when applied to spherical and cylindrical particle geometries, with and without the inclusion of a size-dependent diffusion layer thickness component in the model. Experimental data was fitted to the model to obtain the diffusion layer thickness and post-dissolution particle size distribution predictions. The comparison between simulated and experimental results demonstrated that both size-dependent and size-independent models can give good simulation results.
      396