Practice for Pharmaceutical Process Design Utilizing Process Analytical Technology

2014 ◽  
Author(s):  
Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1600
Author(s):  
Alex Juckers ◽  
Petra Knerr ◽  
Frank Harms ◽  
Jochen Strube

Lyophilization is widely used in the preservation of thermolabile products. The main shortcoming is the long processing time. Lyophilization processes are mostly based on a recipe that is not changed, but, with the Quality by Design (QbD) approach and use of Process Analytical Technology (PAT), the process duration can be optimized for maximum productivity while ensuring product safety. In this work, an advanced PAT approach is used for the endpoint determination of primary drying. Manometric temperature measurement (MTM) and comparative pressure measurement are used to determine the endpoint of the batch while a modeling approach is outlined that is able to calculate the endpoint of every vial in the batch. This approach can be used for process development, control and optimization.


Processes ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1325
Author(s):  
Leon S. Klepzig ◽  
Alex Juckers ◽  
Petra Knerr ◽  
Frank Harms ◽  
Jochen Strube

Lyophilization stabilizes formulated biologics for storage, transport and application to patients. In process design and operation it is the link between downstream processing and with final formulation to fill and finish. Recent activities in Quality by Design (QbD) have resulted in approaches by regulatory authorities and the need to include Process Analytical Technology (PAT) tools. An approach is outlined to validate a predictive physical-chemical (rigorous) lyophilization process model to act quantitatively as a digital twin in order to allow accelerated process design by modeling and to further-on develop autonomous process optimization and control towards real time release testing. Antibody manufacturing is chosen as a typical example for actual biologics needs. Literature is reviewed and the presented procedure is exemplified to quantitatively and consistently validate the physical-chemical process model with aid of an experimental statistical DOE (design of experiments) in pilot scale.


2009 ◽  
Vol 63 (3) ◽  
pp. 171-173 ◽  
Author(s):  
Tobias Broger ◽  
Res P. Odermatt ◽  
Pablo Ledergerber ◽  
Bernhard Sonnleitner

2019 ◽  
Vol 42 (5) ◽  
Author(s):  
Rifna E. Jerome ◽  
Sushil K. Singh ◽  
Madhuresh Dwivedi

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