(442d) Exploring Nondestructive Analytical Methods for Characterizing the Effect of Polymers in Pharmaceutical Formulations from Continuous Manufacturing Process

In the Pharmaceutical industry, Critical Quality Attributes (CQA) play a pivotal role in ensuring the efficacy and safety of the final product. It is imperative to evaluate these parameters to get an overall estimation pertaining to tablet properties. Non-destructive methods have emerged as a valuable tool for evaluating tablet properties without altering or damaging the sample. In this study, we focus on how non-destructive methods provide information about tablet properties such as the amount of polymer, tablet hardness, density, and tensile strength by characterizing the effect of polymers in pharmaceutical formulations produced through continuous manufacturing processes. The objective was to create a model that utilized powder blends containing different concentrations of Active Pharmaceutical Ingredients (API) and Polymer. Powder blends were made in V-Blender with an Intensifier bar by varying concentrations of API and excipients but with an identical operation setup. Parameters like varied Blender RPM and Feed Frame RPM were subjected to change in the continuous line. It involved the exploration of the use of various nondestructive techniques, including near-infrared spectroscopy (NIRS), to characterize the effect of polymers in pharmaceutical formulations manufactured using a continuous manufacturing process. The model employed Principal Component Analysis (PCA), Partial Least Squares (PLS) regression, and spectral preprocessing for analyzing the spectral data obtained. These are useful techniques for reducing dimensionality, modeling relationships between variables, and preparing spectroscopic data for analysis. It provides the quantitative and qualitative estimation of the in-line powder blends being characterized. The results obtained from these techniques were compared to traditional destructive methods and UV spectroscopy. The use of these nondestructive methods not only provides a more efficient means of analysis but also has the potential to enhance process understanding and improve product quality control in continuous manufacturing processes.

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