(430c) Modeling of Cake Filtration – Applications in Predicting the On-Scale Filtration Performance of Various Pharmaceutical Intermediates

We present two simple and straightforward modeling approaches based on Darcy's law to analyze raw data from laboratory scale filtration to predict the pilot plant/manufacturing plant filtration performance. Using these models could avoid potential surprises during scale-up in terms of both cycle time and quality of the isolated pharmaceutical intermediates. With the first approach, data from a simple Buchner funnel filtration is used to estimate the cake resistance and provide a first order approximation of the expected on-scale filtration performance. This result is used to justify further characterization of the cake properties. This novel capability of estimating the on-scale filtration performance from Buchner funnel filtration would save a significant amount of time and resources. If necessary, a detailed filtration study incorporating dynamic pressure modulation is used to obtain a more accurate representation of cake properties and improve the fidelity of the predictions. With dynamic pressure modulation (a single filtration with ascending pressures), we are able to use one filtration experiment to perform the calculation of the cake properties, which usually requires more than one filtration experiment. We also discuss various case studies of how these approaches were used to predict and optimize the filtration conditions used for scale-up.