(M0930-09-61) Scale-Down Modeling of the Filling Process for Protein-Based Parenteral Drug Products

Purpose: Drug manufacturing consists of a series of operations, generally referred to as formulation, filling, and finishing [1]. Filling represents the most critical operation, in which the drug product undergoes different steps, including mixing, pumping, filtration, and final filling into vials. As protein-based parenteral drug products are intended for humans, there is concern over their stability; indeed, they may be sensitive to temperature changes, oxidation, light, ionic strength and shear stress [2]. Among these, shear stress has gained interest over the past decades because of its frequent occurrence in filling lines and is the focus around which this work revolves. Exposure of protein-based parenteral drugs to such stresses is believed to promote unfolding and subsequent aggregation, which might alter the biological activity of the drug and raise the potential for side effects [3]. Several studies conducted in recent years have tried to shed light on the actual impact of shear stress on drug products, but the presence of additional stresses (such as interfacial stress) has complicated the interpretation of the results. In this work, we calculated the shear stress in the operating units of the filling process as a first step for broader experimental investigation. In addition, we explored the field of scale-down approaches, which are used to replicate the industrial line at the laboratory scale to perform experiments on product characterization [4].

Methods: In this project, we used Computational Fluid Dynamics (CFD) to investigate the fluid dynamics within the operating units of a filling line via OpenFoam 9 (https://github.com/OpenFOAM/OpenFOAM-9). The simulations were carried out on an Intel (R) Xeon (R) Gold 5118 CPU at 2.30 GHz and 128 GB of RAM. The simulations’ post-processing was conducted via Python 3.8 and the Paraview application. An incompressible and Newtonian fluid was considered to represent the drug product and gravity was neglected. For each operating unit, a specific method was pursued to develop a representative domain. In addition, when modeling the sterilizing filtration unit, experiments were performed in order to assess the filter permeability for experimental comparison with the models (Figure 1).

Results: We developed a model for calculating the shear stress distribution using a shear history-based approach. In detail, we considered a representative number of particles, i.e., active molecules, within the domain and studied their history of shear stress, residence time and velocity. Based on this information, we calculated an average shear stress. In Figure 2 the trajectories and velocities of particles moving within typical fittings, used for sampling operations, can be seen as an example. This proposed shear history-based approach has been applied on different operation units of the filling line and under different fluid dynamic conditions [4], [5]. In addition, we developed a scale-down approach aimed to ensure representativeness between the process at industrial and laboratory scales using the shear stress distribution as a scaling parameter and compared it with approaches traditionally used in the pharmaceutical industry.

Conclusion: This work addresses a current industrial problem, by focusing on the assessment of the exposure to shear stresses experienced by the product as it passes through some of the equipment in the filling line. In addition, the work done on scale-down approaches introduces a novelty in the pharmaceutical realm, where scale-down is never done considering the process from the product’s point of view. Nonetheless, unlike other industrial processes, product quality monitoring is fundamental; thus, it is pivotal that the scale-down approach maintains the same shear stress exposure as the commercial scale. This work can lay the groundwork for further experimental investigations to evaluate the effect of the shear stress exposure, we calculated for the various components of the line, on the stability of the parenteral drug product.

References: [1] S. Y. Patro, E. Freund, and B. S. Chang, “Protein formulation and fill-finish operations,” Biotechnol. Annu. Rev., vol. 8, pp. 55–84, 2002.
[2] ICH, “Guideline for Industry ICH Q5C Quality of Biotechnological Products: Stability Testing of Biotechnological/Biological Products,” Federal Register, 1996. https://www.ema.europa.eu/en/documents/scientific-guideline/ich-topic-q-5-c-quality-biotechnological-products-stability-testing-biotechnological/biological-products_en.pdf.
[3] W. Wang, S. Nema, and D. Teagarden, “Protein aggregation-Pathways and influencing factors,” Int. J. Pharm., vol. 390, no. 2, pp. 89–99, 2010.
[4] C. Moino, B. Scutellà, M. Bellini, E. Bourlès, G. Boccardo, and R. Pisano, “Analysis of the Shear Stresses in a Filling Line of Parenteral Products: The Role of Tubing,” Processes, vol. 11, no. 833, 2023.
[5] C. Moino, B. Scutellà, M. Bellini, E. Bourlès, G. Boccardo, and R. Pisano, “Analysis of the Shear Stresses in a Filling Line of Parenteral Products: The Role of Fittings,” Processes, vol. 11, no. 1797, 2023.

Acknowledgements:

Funding: This work was sponsored and financially supported by GlaxoSmithKline Biologicals SA. Conflicts of interest: The authors declare the following competing financial interest(s): Bernadette Scutellà, Andrea Albano, Marco Bellini, and Erwan Bourlès are employees of the GSK group of companies. Camilla Moino holds a Doctorate studentship and collaborates with GSK as part of her PhD training.

Figure 1. Experimental set up.

Figure 2. Particles are followed through their streamlines. Their trajectories (and velocities) are displayed.