Lyophilization scale-up to industrial manufacturing: A modeling framework including probabilistic success prediction

Scaling-up a lyophilization cycle to the manufacturing scale successfully at the first pass is of crucial importance to the bio-pharmaceutical community in order to save expensive and sparsely available drug products for clinical and industrial manufacturing. The con-straints on time, cost and energy consumption during process development are prohibi-tive to performing multiple experimental studies at the manufacturing scale. Most process analytical techniques to obtain cycle data are often not available at the manu-facturing scale due to sterility concerns with intrusive tools and experimental un-certainties at industrial manufacturing scales. Modeling techniques offer an attractive alternative solution under these circumstances to gain knowledge about the manu-facturing scale equipment limitations and predict the probability of success prior to performing experimental trials in order to minimize the risk associated with scale-up. In this paper, we present a detailed characterization of equipment capability curves for lyophilizers across laboratory, pilot and manufacturing scales using Computational Fluid Dynamics (CFD) modeling and highlight the flow features in manufacturing-scale equip-ment with different geometric attributes. We present the equipment, process and product parameters which determine the outcome of the cycle and develop guidelines for robust scale-up practices from the laboratory and pilot scales to the manufacturing scale using vial heat and mass transfer modeling. We present examples of cycles which would seem to scale-up to the manufacturing-scale successfully using a deterministic model but would have a high probability of failure when process excursions, deviations, and input uncertainties are accounted for by applying a Monte-Carlo based probabilistic model. We demonstrate the method to reduce the failure probability and de-risk the scale-up of such processes. We also present the significant reduction in primary drying time that can be achieved by implementing a lyophilization recipe with varying setpoints of chamber pressure and shelf temperature for the primary drying stage in a manufacturing-scale lyophilizer. All the observations from our modeling analyses and example studies indicate that CFD simulations in combination with deterministic and Monte-Carlo based prob-abilistic vial heat and mass transfer modeling would significantly improve the success of scale-up to industrial lyophilized drug manufacturing. (c) 2023 Published by Elsevier Ltd on behalf of Institution of Chemical Engineers.