Model predicts unwanted clumping in pharmaceutical drying processes
Integrated Population Balance and Multiphysics Modeling for Predicting Undesired Agglomeration in Small Molecule Manufacturing
Computational Engineering, Finance, and Science
Summary
In making small-molecule medicines, drying processes can cause particles to stick together in ways that ruin the product and damage machines. The authors developed a detailed model that tracks how particle clumps form and grow during drying. This model also predicts temperature, moisture, and particle sizes over time. It helps manufacturers know when and why clumps form and suggests better ways to run the drying step.
What this means in practice
- •For chemical process engineers: Design and optimize drying steps in pharmaceutical production to reduce harmful particle clumping and improve product consistency.
- •For pharmaceutical equipment manufacturers: Develop smarter drying machines that monitor and control conditions to prevent agglomerates, improving reliability and minimizing damage.$Commercial implications: Enables creation of advanced agitated filter dryers with embedded predictive controls selling better performance to pharma producers.
Authors
Prakitr Srisuma, Peter Hou, Shashank Venkat Muddu, Neda Nazemifard, Allan S. Myerson, Richard D. Braatz
Abstract
Agitated filter dryers (AFDs) are a crucial unit operation in small molecule manufacturing that enables simultaneous filtration, washing, and drying of active pharmaceutical ingredients. One of the key challenges in AFDs is associated with undesired agglomeration, where the presence of hard agglomerates results in off-spec products, equipment damage, and additional downstream processing. This article presents a novel mechanistic model that describes the formation of soft and hard agglomerates during agitated filter drying. By integrating population balance and multiphysics modeling, the model can accurately predict the evolution of the product temperature, moisture content, and particle size distribution, and hence quantify the extend and impact of undesired agglomeration across various operating conditions. Our proposed model-based framework enables the rational design and operation of AFDs for improving the product quality and process reliability.