Peer-Reviewed Technical Note: Quality by Design in Freeze-Drying - Pharmaceutical Technology

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Peer-Reviewed Technical Note: Quality by Design in Freeze-Drying
Cycle design and robustness testing using advanced process analytical technology.

Pharmaceutical Technology
Volume 32, Issue 10, pp. 88-93

Figure 2
The "adjustment" of the profile showing T s over time (averaging of the SMART shelf-temperature settings during primary drying to obtain a constant shelf temperature over time) and P c setting (increase of P c from 52 to 62 mTorr) was conducted to further improve the recipe and to facilitate scale-up (see Figure 2) (10). T p and R p profiles over time for this modified cycle were found in very good agreement to the initial SMART cycle with a maximum temperature of –34.8 C during the run (see Figure 3 and Table I). Total primary drying time was 1190 min, or about 5% longer than the initial cycle recipe. It is important to note that the product processed in both cycles showed no indication of shrinkage or collapse (see Figure 5a).

Figure 3
Impact of T s and P c variation on product temperature. For 50 mg/mL sucrose, variation of shelf temperature of 5 C had very little influence on the profile of T p over time (see Figure 3). However, an increase in P c from 52 to 200 mTorr led to a significant increase in T p (>3 C), thereby exceeding T c . In contrast, an increase in solid content to 200 mg/mL and use of identical process conditions revealed only an increase of 1 C in T p .

Theoretical modeling of the freeze-drying cycle is an alternative method to gain a better understanding of the impact of process variables on the product-temperature profile. A one-dimensional steady state of the freeze-drying process was used to simulate the influence of T s and P c variations on T p for the 50 mg/mL sucrose solution. Note that T s and P c parameters were used according to the experimental design described above (see Figure 3 and Table I). During primary drying, the system is in a "pseudo steady state" and the following equation can be applied to predict product temperature (3, 11):


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