Characterization of acoustic emission analysis in applications for inhalation device performance assessment

Abstract

Acoustic Emission (AE) measurement technology has gained wide appreciation in material sciences and process monitoring. In inhalation research, AE has been used for adherence indicating applications in clinical studies. Promising results from feasibility studies using AE combined with multivariate data analysis (AE-MVDA) in the analysis of devices for inhalation have prompted a broader study reported in this paper. This work presents the novel application of AE-MVDA for assessment of the combined inhalation device and formulation performance. The purpose is to evaluate the benefits that this technology can provide to inhalation product development programs. The work was carried out using two different dry powder inhaler device model systems while investigating different performance features. The devices were filled with dry powder formulations with both placebo and with active pharmaceutical ingredient (API). The acquired AE data was analyzed using multivariate data analysis tools such as Principal component analysis (PCA) and orthogonal projections to latent structures (OPLS). The AE profiles were indicative for device and formulation performance. Normal and deviating performances were readily picked up in the AE data. Moreover, performance trends between doses withdrawn from the inhalers were also observable. Lastly, differences in the AE profile between the formulations could be detected. The overall conclusion from the AE-MVDA measurement approach evaluation is that it has the potential to add value as a cost-effective, non-invasive quality and performance monitoring technology both in development and in production of inhaled medicines.