Abstract

The aim of the present study was to optimize a tablet formulation using a quality by design approach. The selected methodology was based on the variation of the filler grade, taking into account the particle size distribution (PSD) of active pharmaceutical ingredient (API) in order to improve five critical quality attributes (CQAs). Thus, a mixture design of experiments (DoE) was performed at pilot scale. The blending step was monitored using near infrared (NIR) spectroscopy as process analytical technology tool enabling real-time qualitative process monitoring. Furthermore, some tablets were analyzed by Raman imaging to evaluate the API distribution within the samples. Based on the DoE results, design spaces were computed using a risk-based Bayesian predictive approach to provide for each point of the experimental domain the expected probability to get the five CQAs jointly within the specifications in the future. Finally, the optimal conditions of the identified design space were successfully validated. In conclusion, a design space approach supported by NIR and Raman spectroscopy was able to define a blend that complies with the target product profile with a quantified guarantee or risk.

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