(563f) Why Thermal Interactions Among Vials Matter in Pharmaceutical Freeze-Drying: Experimental Evidence and Mechanistic Modeling

Main body

Freeze-drying (or lyophilization) is commonly used for stabilizing sensitive biopharmaceutical drug products because it allows for water removal at low temperatures. On a commercial scale, tens of thousands of vials containing the pharmaceutical formulation are densely packed on temperature-controlled shelves and freeze-dried together. [1-2] Regulatory requirements dictate that the products in all vials must meet quality specifications, which requires both a detailed process understanding and a tight process control.

Here we report an experimental investigation on the role of thermal interaction among vials in freeze-drying, which we recently identified as main pathway to batch heterogeneity, i.e., to variability in product attributes among vials. We studied the freezing process for a shelf packed with vials in a lab-scale freeze-dryer (Telstar Lyobeta 3PS). We considered multiple packing densities and geometries which correspond to different magnitudes of thermal interaction. To assess the freezing behavior in a statistically significant number of vials, as necessitated by the stochastic nature of ice nucleation, we rely on direct thermal imaging using an infrared camera (FLIR A65). This technique provided us with detailed information on the time when ice nucleation occurs in each vial, as well as on the time required for complete solidification.

We found that thermal interactions among vial play a significant role in freezing: for process configurations corresponding to strong interaction, the heat released in a vial upon nucleation significantly directly affected the thermal evolution of its neighboring vials. These neighboring vials cooled down slower, or in the most extreme case, heated up temporarily, until solidification of the earlier nucleating vial had been completed. This effect led to a significant broadening of the distributions of both nucleation and solidification times compared to process configurations with less strong interaction (i.e., with smaller packing density).

Broad distributions in solidification and nucleation times among vials are detrimental to process quality and control, since they translate into variability in drying behavior, and eventually in critical quality attributes such as residual drug activity or residual moisture. Thermal interaction can be mitigated by lowering the packing density of vials on the shelf, however, this comes with a decrease in throughput. [1-3] We note that thermal interactions play a major role not only in freeze-drying, but also in commercial freezing processes in pallets: when analyzing engineering run data for the freezing process of the Janssen COVID-19 vaccine, we recently observed that thermal interactions among vials govern thermal evolution, process duration, and the distributions of nucleation and solidification times. [2,4,5]

As our findings indicate, thermal interactions among vials should be considered in process design. To this end, we recently developed a mechanistic shelf-scale model for freezing in vials that accounts for both the stochastic nature of ice nucleation, and for thermal interaction. It is worth underling that the experimentally observed trends are well predicted by the model: simulations under conditions with strong interactions result in broader distributions of nucleation and solidification times, in line with the experiments. To promote the use and further development of the model in the wider community, we provide open source access to it in the form of a python package (available at https://pypi.org/project/ethz-snow/ ). [2,4,5,6]

Fig. 1. Example for a vial holder with square arrangement of the vials. Such square arrangement corresponds to a lower packing density and hence less strong thermal interaction compared to a hexagonal arrangement.

Acknowledgement

The authors thank the Janssen Pharmaceutical Companies of Johnson & Johnson, especially Juan Carlos Araque and Ryan Wall, for the support in the course of the project and the financial funding.

References

[1] JC Kasper and W Friess: The freezing step in lyophilization: Physicochemical fundamentals, freezing methods and consequences on process performance and quality attributes of biopharmaceuticals, Eur. J. Pharm. Biopharm. (2011), 78, 248-263.

[2] LT Deck, DR Ochsenbein and M Mazzotti: Stochastic Shelf-Scale Modeling Framework for the Freezing Stage in Freeze-Drying Processes, Int. J. Pharm. (2022), 613, 121276.

[3] R Pisano, A Arsiccio, K Nakagawa and AA Barresi: Tuning, measurement and prediction of the impact of freezing on product morphology: A step toward improved design of freeze-drying cycles, Drying Technology (2019), 37:5, 579-599.

[4] LT Deck, DR Ochsenbein and M Mazzotti: Stochastic ice nucleation governs the freezing process of biopharmaceuticals in vials, Int. J. Pharm. (2022), 625, 122051.

[5] LT Deck, DR Ochsenbein and M Mazzotti: SNOW – Stochastic Nucleation of Water, (2021), GitHub Repository, https://github.com/SPLIfA/snow/

[6] LT Deck and M Mazzotti: Characterizing and measuring the ice nucleation kinetics of aqueous solutions in vials, Chem. Eng. Sci. (2023), 272, 118531.