On the robustness of the soft sensors used to monitor a vial freeze-drying process

Abstract

ABSTRACTProcess monitoring is a key issue in pharmaceutical freeze-drying to evaluate if the limit product temperature is approached, to identify the ending point of the main drying stage, and to estimate the value of some parameters of a mathematical model of the process so that it can be used for cycle optimization. Soft sensors can be used for this purpose: three algorithms, based on the extended Kalman filter and on product temperature measurement, have been compared in this study; they differ on the number of estimated parameters and on the way used to set their initial estimates. Results evidence that the accuracy of estimates is strongly dependent on the initial values of model parameters, and soft sensors #1 and #2 require a preliminary investigation to get accurate initial estimates of the heat and mass transfer coefficients. Soft sensor #2 should be preferred as it just requires an initial estimate of the heat transfer coefficient. Significant advantages are obtained with soft sensor #3: accurate estimates are obtained whichever values of the parameters are used to start the calculations (provided that reasonable values are used) and, thus, it can be effectively used to monitor the freeze-drying cycle without any preliminary investigation. Soft sensor #3 should thus be preferred to the other tools for freeze-drying monitoring.