Predicting Tablet Potency in Continuous Manufacturing

In continuous pharmaceutical manufacturing, real-time assurance of critical quality attributes (CQAs) is highly desired. Among CQAs, control and assurance of tablet potency has been challenging due to lack of real-time measurement sensors tied to optimization programs. A modular self-contained toolbox developed using Python programming has been demonstrated to predict tablet potency based on a residence time distribution (RTD) model and apply a diversion strategy to divert out-of-specification tablets. The modular toolbox can be integrated with any commercially available tools to control tablet potency, can automatically calibrate the RTD model for different formulations and processes, and can be used to predict outlet concentrations, assuming accurately quantified inputs.

Read this article in Pharmaceutical Technology’s October 2021 APIs, Excipients, and Manufacturing eBook.

About the author

Ravendra Singh is Assistant Research Professor, NSF-ERC C-SOPS, Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey.

Article Details

Pharmaceutical Technology
eBook: APIs, Excipients, and Manufacturing
October 2021
Pages: 44–49

Citation

When referring to this article, please cite it as R. Singh, “Predicting Tablet Potency in Continuous Manufacturing,” Pharmaceutical Technology APIs, Excipients, and Manufacturing eBook (October 2021).