Water-Intrusion Test Integration - Pharmaceutical Technology

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Water-Intrusion Test Integration
The authors describe the operational qualification of test accuracy with regard to temperature drift using a thermal-compensation algorithm on several freeze dryers.


Pharmaceutical Technology
pp. 64-70

Temperature influence during the stabilization phase




During the stabilization phase preceding the pressure drop measurement, the compacted gas net volume is also influenced by temperature variation, although to a much smaller extent. As the pressure remains constant during the stabilization phase (p stab ) the equation 2 can be written as:




During the stabilization phase there is no variation of the pressure. Therefore, one can say that p T1 = p T2 = p stab , so:




Thus volume variation (ΔV T ) due to the eventual temperature variation during the stabilization phase can be calculated according to the following equation:

Using the above equation, the gas net volume is influenced by less than 0.4% per degree of temperature drift.

Effective temperature influence from the environment

A variation of 1 C in the environment of the filter housing that is being tested is not likely to influence the test result in the above mentioned manner (i.e., by 24%). The housing is filled with water, which has a great heat capacity, and it takes time to transfer the energy from the stainless steel into the gas net volume. Nevertheless, during risk analysis, the temperature influence has to be taken into account, especially because the environment of a freeze dryer or an autoclave can be subject to temperature variations caused by the previous steaming cycle or other equipment.

Insulating the top part of the headspace volume is often sufficient to protect against temperature influence. However, from a risk-analysis point of view, it is safer to monitor and record any temperature variation using a temperature sensor inside the headspace volume. The integration of an algorithm to compensate for influence caused by an eventual temperature drift gives higher process security and avoids false conformity and false nonconformity test results.


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