(603f) Characterization of Residence Time Distribution of One Formulation on Two Mirror Continuous Lines

Over the past ten years, continuous manufacturing (CM) has garnered considerable momentum in the pharmaceutical industry due to its capacity for enhancing agility, flexibility, and robustness in both product and process development [1, 2]. Companies that have implemented CM may seek to expand their production capacity or investigate new products on their originally established continuous line requiring them to explore the possibility of transferring products to other manufacturing sites. However, achieving the same level of quality as the original continuous line may prove to be a challenging task, even if the same version of equipment is employed. Conducting a complete Design of Experiments (DoE) for each continuous line can be an arduous and costly process.

To depict process dynamics and gauge the degree of back-mixing in continuous flow systems, the residence time distribution (RTD) [3] is a tool that finds extensive application. Characterizing mixing and flow patterns necessitates an understanding of the RTD for every unit operation and the integrated manufacturing line [4]. While a CM line operates under normal conditions, several process parameters may undergo modification, and the properties of blend and ingredient materials may also fluctuate, thereby leading to variations in the RTD [5].

In this study, we aimed to explore the RTD of two so-called “mirror” integrated manufacturing lines using one specific formulation, to only focus on the process parameters effect on RTD. 3-factor 3-level DoE for throughput, blender speed, and feed frame speed was conducted on both manufacturing lines. Tracer experiments were performed under each DoE, and the tracer concentration profiles are pretreated using wavelet transform denoising methods and the baseline truncation procedure to obtain meaningful RTD profiles. Then, axial dispersion models [6] were fitted and reliable RTD model parameters were obtained. Finally, response surface models were developed to describe the dependence of RTD parameters as a function of process parameters followed by statistical analysis to demonstrate the goodness of fit. Despite some differences in layout, and size of equipment connections between the two lines and using two different tablet presses, the study found that the results were consistent, with throughput being the most significant parameter. A single predictive model effectively described the RTD in both mirror lines, eliminating the need for a complete DoE to transfer the knowledge to other mirror lines.

References

1. Ierapetritou, M., F. Muzzio, and G. Reklaitis, Perspectives on the continuous manufacturing of powder-based pharmaceutical processes. AIChE Journal, 2016. 62(6): p. 1846-1862.
2. Lee, S.L., et al., Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production. Journal of Pharmaceutical Innovation, 2015. 10(3): p. 191-199.
3. Danckwerts, P.V., Continuous flow systems. Distribution of Residence Times. Chemical Engineering Science, 1953. 2: p. 1-13.
4. Gao, Y., F.J. Muzzio, and M.G. Ierapetritou, A review of the Residence Time Distribution (RTD) applications in solid unit operations. Powder Technology, 2012. 228: p. 416-423.
5. Van Snick, B., et al., Impact of material properties and process variables on the residence time distribution in twin screw feeding equipment. Int J Pharm, 2019. 556: p. 200-216.
6. Escotet-Espinoza, M.S., et al., Effect of material properties on the residence time distribution (RTD) characterization of powder blending unit operations. Part II of II: Application of models. Powder Technology, 2019. 344: p. 525-544.