Recommended Best Practices in Freeze Dryer Equipment Performance Qualification: 2022.

Best practices for performing freeze dryer equipment qualification are recommended, focusing on identifying methods to quantify shelf thermal uniformity (also known as "shelf surface uniformity"), equipment capability, and performance metrics of the freeze dryer essential to the pharmaceutical Quality by Design paradigm. Specific guidelines for performing shelf temperature mapping, freeze dryer equipment limit testing (the capability curve), and condenser performance metrics have been provided. Concerning shelf temperature mapping and equipment capability measurements, the importance of paying attention to the test setup and the use of appropriate testing tools are stressed. In all the guidelines provided, much attention has been paid to identifying the balance between obtaining useful process knowledge, logistical challenges associated with testing in the production environment vs that at laboratory scale, and the frequency of the testing necessary to obtain such useful information. Furthermore, merits and demerits of thermal conditions maintained on the cooled surfaces of the freeze dryer condenser have been discussed identifying the specific influence of the condenser surface temperature on the process conditions using experimental data to support the guidelines. Finally, guidelines for systematic leak rate testing criteria for a freeze dryer are presented. These specific procedural recommendations are based on calculations, measurements, and experience to provide useful process and equipment knowledge.

Investigation of design space for freeze-drying: use of modeling for primary drying segment of a freeze-drying cycle.

In this work, we explore the idea of using mathematical models to build design space for the primary drying portion of freeze-drying process. We start by defining design space for freeze-drying, followed by defining critical quality attributes and critical process parameters. Then using mathematical model, we build an insilico design space. Input parameters to the model (heat transfer coefficient and mass transfer resistance) were obtained from separate experimental runs. Two lyophilization runs are conducted to verify the model predictions. This confirmation of the model predictions with experimental results added to the confidence in the insilico design space. This simple step-by-step approach allowed us to minimize the number of experimental runs (preliminary runs to calculate heat transfer coefficient and mass transfer resistance plus two additional experimental runs to verify model predictions) required to define the design space. The established design space can then be used to understand the influence of critical process parameters on the critical quality attributes for all future cycles.

Determining Maximum Sublimation Rate for a Production Lyophilizer: Computational Modeling and Comparison With Ice Slab Tests.

Equipment capability is an important factor in scale up and technology transfer for lyophilized pharmaceutical products. Experimental determination of equipment capability limits, such as the maximum sublimation rate at a given chamber pressure, is time-intensive for production lyophilizers. Here, we present computational fluid dynamics modeling of equipment capability and compare it with experimental data for minimum controllable pressure ice slab sublimation tests in a 23 m2 shelf area freeze dryer. It is found that the vapor flow in the production scale is characterized by turbulent effects at high sublimation rates. For the considered freeze dryer configuration, the onset of turbulence occurs at a sublimation rate of 17 kg/h and leads to an increase in the minimum controllable pressure by 3-4 mTorr for the flow rates up to 40 kg/h. Variations in the shelf and duct orientations as well as the valve stroke distance and their effect on the equipment limit and pressure uniformity are also discussed. The minimum controllable pressure measured experimentally agreed within 5% with computational fluid dynamics results. For high vapor sublimation rates at final stages of ice slab testing, the condenser load affects the product chamber pressure control. Estimate of condenser pressure changes because of ice accumulation has been included.