New Model-Based Platform for Enhanced Content Uniformity Prediction of Oral Dosage Forms
New Model-based Platform for Enhanced Content Uniformity Prediction of Oral Dosage Forms
Being a critical quality attribute for capsules and tablets, content uniformity (CU) has received continued attention from practitioners and academics with multiples proposals to relate it with upstream properties such as the particle size distribution and true density of the active pharmaceutical ingredient (API).
In this work we propose a new model to predict the CU of a lot of tablets or capsules, based on a corrected algorithm that considers: the particle size distribution of the API and its variability, the true density of the API, the size dependant potency of any drug product intermediate and the weight variability of the lot of finished product. The model is based on a particle level mass balance and a Monte-Carlo simulation of the sampling process. The accuracy of this new model is demonstrated by showing predicted versus observed values of content uniformity (RSD) for multiples cases.
This model enables a much improved risk assessment exercise between API characteristics, production process and CU; and provides a platform to establish acceptable variability ranges and targets that are fundamental components of a Quality by Design development.
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