(377a) A Digital Twin Model of Homogenizer Used in Continuous Injectables Manufacturing

Currently, the pharmaceutical industry is going through a paradigm shift from batch to advanced continuous manufacturing (CM) of liquid dosages form. The continuous manufacturing provides several advantages including low footprint [1], better process control and safety [2], improved product quality [3], easier adaptation, lesser manufacturing and operating cost, and easier scale-up/number-up. However, the development, and adaptation of the continuous manufacturing of the liquid dosages forms is still a challenging task because of different levels of complexities. Therefore, systematic methods and digital tools are needed to support the quick development, adaptation, optimization, and control of the continuous manufacturing of the injectable liquid dosages forms.

Continuous homogenizer plays a very important role in the continuous manufacturing of liquid dosages forms. The products achieve better active ingredient dispersion after being processed through the homogenizer. This further helps to enhance the bioavailability and drug release profiles. Reducing the agglomerates &/or particles size and improving the uniformity in composition can also have a significant impact on the consumer appeal of the products, besides having other advantages. In this research, an advanced digital twin model of continuous homogenizer has been developed. This model describes the particle size reduction within the homogenizer which results in the generation of fines. Mechanical forces such as shear, turbulence, impact, cavitation, and centrifugal action are the primary causes, leading to the subdivision of particles into very small sizes for further processing. The action of homogenization leads to better dispersion of the API, thereby resulting in more stable products. It provides a clear understanding of the flow structure and the flow field parameters inside the homogenizer which is essential for the design and optimization of this unit operation. Being highly adaptive, it enables digital design, optimization and control of the homogenizer. The model has been validated for homogenization of ingredients used in albuterol production.

The applications of the model have been demonstrated for scenario analysis, sensitivity analysis and to optimize the process. Since mixing and particle size reduction are the key processes in any continuous manufacturing line, this study is essential for enhancing the overall efficiency and effectiveness of the process and the product.

References

1. Rogers, L., Jensen, K. (2019). Continuous manufacturing – the Green Chemistry promise? Royal Society of Chemistry, 21, 3481-3498.
2. Mascia, S., Heider, P., Zhang, H., Lakerveld, R., Benyahia, B., Barton, P., Braatz, R., Cooney, C., Evans, J., Jamison, T., Jensen,K., Myerson, A., Trout, B. (2013). End-to-End Continuous Manufacturing of Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation. Angewandte Chemie, 125, 12585-12589.
3. May,S. (2017). Flow Chemistry, Continuous Processing, and Continuous Manufacturing: A Pharmaceutical Perspective. Journal of Flow Chemistry, 7, 3-4.

Acknowledgements

This work is supported by the US Food and Drug Administration (FDA) under contract number 75F40122C00122.