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Optimizing lyophilization primary drying: A vaccine case study with experimental and modeling techniques.
Jeff Najarian1, Efimia Metsi-Guckel1, Harshil K Renawala1
1Merck & Co., Inc., Rahway, NJ 07065, USA.
International Journal of Pharmaceutics
|April 25, 2024
Summary
Optimizing lyophilization cycles for vaccines involves aggressive drying, challenging traditional methods. This study found that exceeding the collapse temperature (Tc) can safely reduce drying times by 45% while maintaining vaccine quality.
Area of Science:
- Pharmaceutical Sciences
- Chemical Engineering
- Biotechnology
Background:
- Lyophilization (freeze-drying) is crucial for vaccine stability and shelf-life.
- Optimizing primary drying time is key to reducing overall lyophilization cycle length.
- Conventional methods often lead to sub-optimal, lengthy drying cycles.
Purpose of the Study:
- To optimize the primary drying time of a vaccine formulation.
- To evaluate thermal characteristics, temperature profiles, and critical quality attributes (CQAs).
- To develop a more reliable method for determining macroscopic collapse temperature in vials.
Main Methods:
- Differential Scanning Calorimetry (DSC) and Freeze-Drying Microscopy (FDM) to determine critical temperatures (Tg', Tc).
- Manometric Temperature Measurement (MTM) to assess product resistance (Rp) and temperature profiles.
- First principles modeling for heat and mass transfer to generate a primary drying design space.
Main Results:
- Aggressive drying conditions, exceeding the FDM-determined collapse temperature (Tc), reduced drying time by ~45% without compromising CQAs.
- Product temperature drop post-primary drying correlated with the degree of macroscopic collapse.
- A more representative macroscopic collapse temperature (Tcm) was determined using quantitative analysis of temperature, resistance, and visual cake appearance.
Conclusions:
- Accurate determination of macroscopic collapse in vials is critical for process optimization.
- Pursuing aggressive lyophilization drying, tailored to specific product characteristics, can significantly reduce cycle times.
- Integrating experimental data with modeling techniques enables efficient development and optimization of lyophilization processes.

