Syringe Filling of High-Concentration mAb Products Using Peristaltic Pump-Based Mechanism: Challenges and Mitigation Strategies.

Syringe filling of high-concentration mAb formulation during manufacturing of large-scale drug product batches may present challenges such as product deposition onto the area of the syringe barrel where the stopper is inserted, product splashing or dripping, droplets left after the fill cycle, filling needle clogging, product build-up inside the needle during line stoppages, variation in fill weight/volume, and potential impact on product quality attributes. In this article, a summary of these issues and approaches to overcome them are summarized. Potential failure modes of the syringe filling process and appropriate in-process controls are provided. In addition to developing the filling process or resolving manufacturing issues, the pharmaceutical company developing the product and associated drug product manufacturing process may want to implement long-term strategic approaches to support the portfolio progression. Potential long-term approaches such as use of a viscosity reducing formulation development approach, improving peristaltic filling technology performance, building small-scale filling capability and establishing a streamlined filling process management cycle are also summarized. The aspects summarized in this article may be used to develop a robust filling process and control strategy for high-concentration mAb products and implement long-term strategic approaches to support the portfolio progression.

Mixing of a mAb Formulation in a New Magnetically Coupled Single-Use Mixing System: Key Learnings of Preliminary Experimental and Computational Evaluation.

MilliporeSigma recently introduced a new magnetically coupled single-use mixing system (Mobius® Power MIX) for more efficient mixing of buffers and media in biopharmaceutical applications. Experimental and computational fluid dynamics (CFD) assessments were performed on the Power MIX 100 system to understand product quality impact, shear, and mixing efficiency. It was interesting to note slightly higher submicron (0.4-1 µm) and subvisible (1-54 µm) particle formation at the lower mixing speed (50 RPM) compared to higher mixing speeds (100/200 RPM). Mixing speed and time showed negligible impact on the other product quality attributes tested, including protein concentration, turbidity, general appearance, purity, and soluble aggregates. The CFD simulations provided useful information with respect to the impact of batch size (20-100 L), viscosity (2-50 cP), and impeller speed (100-300 RPM) on mixing time (mixing time ranged from 10 to 365 s) and shear (maximum shear rate was found to be localized around the impeller and it was about 30,260 s-1, whereas the average shear rate ranged from 4 to 36 s-1). Statistical analysis of the CFD results showed that natural-log transformation and quadratic fitting were found to be suitable statistical models to predict mixing time and shear within the design space of the parameters assessed in the present study.

Quality by design: scale-up of freeze-drying cycles in pharmaceutical industry.

This paper shows the application of mathematical modeling to scale-up a cycle developed with lab-scale equipment on two different production units. The above method is based on a simplified model of the process parameterized with experimentally determined heat and mass transfer coefficients. In this study, the overall heat transfer coefficient between product and shelf was determined by using the gravimetric procedure, while the dried product resistance to vapor flow was determined through the pressure rise test technique. Once model parameters were determined, the freeze-drying cycle of a parenteral product was developed via dynamic design space for a lab-scale unit. Then, mathematical modeling was used to scale-up the above cycle in the production equipment. In this way, appropriate values were determined for processing conditions, which allow the replication, in the industrial unit, of the product dynamics observed in the small scale freeze-dryer. This study also showed how inter-vial variability, as well as model parameter uncertainty, can be taken into account during scale-up calculations.