Visualizing and Understanding Batch Heterogeneity During Freeze-Drying Using Shelf-Scale Infrared Thermography

Various biopharmaceutical products are distributed as freeze-dried formulations in vials. Minimizing batch heterogeneity, which refers to the variability of relevant properties among vials and negatively affects product quality, represents a major challenge in process design and operation. Both the...

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Veröffentlicht in:Industrial & engineering chemistry research 2024-09, Vol.63 (38), p.16335-16346
Hauptverfasser: Deck, Leif-Thore, Ferru, Nicole, Košir, Andraž, Mazzotti, Marco
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Sprache:eng
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Zusammenfassung:Various biopharmaceutical products are distributed as freeze-dried formulations in vials. Minimizing batch heterogeneity, which refers to the variability of relevant properties among vials and negatively affects product quality, represents a major challenge in process design and operation. Both the root causes of batch heterogeneity and its dependence on the operating conditions of the process remain poorly understood. To study batch heterogeneity, we here introduce a quantitative tool consisting of an infrared thermography setup (camera plus mirror) capable of monitoring non invasively and online the temperature of 60 vials densely packed on a shelf during freeze-drying. The stochastic nature of nucleation, the differences in heat transfer between vials in the core and at the edges of the batch on the shelf, and the heat transfer between neighboring vials are all demonstrated to be causes of heterogeneity during freezing. The last phenomenon causes the latent heat released by a vial upon nucleation to heat up its neighboring vials, thus delaying their nucleation. Based on the results obtained using a mechanistic model, whose predictive capabilities were confirmed by experiments, fast cooling rates and sparse vial arrangements were identified as means to mitigate batch heterogeneity. Regarding drying, the setup enabled the determination of the end point of primary drying, a process feature that is essential for whole-process optimization.
ISSN:0888-5885
1520-5045
DOI:10.1021/acs.iecr.4c02215