Abstract/Summary

Particle size analysis is one of the most utilised particle characterisation approaches within the pharmaceutical industry. Particle size can affect the quality, processability and/or performance of a pharmaceutical process/product. The particle size and shape of an active pharmaceutical ingredient (API) can affect the stability, dissolution rate, flow, sticking propensity to name but a few. In turn, these can affect product quality attributes such as content uniformity (via cohesion and/or segregation), tablet die filling, tablet disintegration/dissolution rates etc. Consequently, particle size is commonly an integral part of a drug release specification designed to ensure the quality of a drug product. Historically, the use of laser light scattering (LLS) has dominated the particle sizing arena, however, as scientists move towards the need to better understand and model their materials and processes, the use of image analysis tools such as static image analysis (SIA) have see a significant increase in popularity due to their ability to provide data rich information about a wider range of particle characteristics. The aim of this work was first to curate a database of active pharmaceutical ingredients (API), characterising not just size but also information relating to shape (e.g., elongation, width, and length) for each particle within the samples. It was hoped that this information would also enable understand of the influence of distribution shape and separate the information provided through different weighting approaches, both arithmetically and volumetrically weighted. Using this data, the next stage would be to investigate means to improve how the data is reported and used. The next stage would be to consider how this data could be utilised to enable improved understanding of our powders, and through comparison with materials of similar sets of particle characteristics, provide a means to use historical knowledge to mitigate future challenges. In addition to this, work to characterise and track API characteristics within a multi-component system using an integrated image analysis / Raman system. The aim of this would be to challenge the common assumption that the characteristics of the input API are indicative of the API after manufacture. The work was aimed to assess the propensity for an API to undergo process induced attrition during manufacture and determine the sources of attrition. Finally, a proposal of how the above approaches can be implemented into the pharmaceutical development workflow to enhance the understanding of our materials and thereby the performance of our products.