Integrated filtration and washing modelling of active pharmaceutical ingredients and impurities

Ottoboni, S. and Mehta, B. A. and Gramadnikova, E. and Brown, C. J. and Mitchell, N. A. (2022) Integrated filtration and washing modelling of active pharmaceutical ingredients and impurities. In: 13th World Filtration Congress, 2022-10-05 - 2022-10-09.

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There is an increasing interest in the application of continuous processing technologies in pharmaceutical manufacturing to control crystal properties and deliver consistent particulate products. The focus of the work reported here is to combine filtration and washing operations commonly used in active pharmaceutical ingredient (API) purification and isolation by combining predicted and experimental data generated during upstream crystallization process. In detail, this work focuses on the development of a mechanistic model-based workflow for the optimization of an integrated filtration and washing model, with a view to track impurities in the liquid phase. A Carman-Kozeny1 filtration model is integrated with a custom diffusion with axial dispersion washing model2,3. The custom washing model assumes no solid phase dissolution or precipitation. To mimic the dispersion washing mechanism, a single stage continuous stirred-tank reactor approach was used. Mefenamic acid was selected as a representative test compound. Three different mefenamic acid crystallization solvents with relative structurally-related impurities deriving from synthesis were selected. Two wash solvents were selected, n-heptane and cyclohexane. The objective of the models was to a) identify the product purity reached with a fixed wash ratio, and b) explore the design space in order to understand the process conditions to potentially minimize impurity content in the isolated cake. Two different filtration halting procedures were simulated: filtration halted to dryland. The integrated modelling tool uses information on the product crystal suspension characteristics predicted using gPROMS FormulatedProducts to predict filtration time, filtrate flow rate, and the composition of the filter cake and filtrate generated during filtration. The washing of the wet filtered cake is then simulated to predict: washing efficiency and to generate washing curves, cake and filtrate composition, and residual cake moisture content and composition. To validate the scenarios described using the integrated models, some experimental data measured from the biotage filtration unit was used. To validate the cake and filtrate composition during filtration and washing stages, HPLC quantitative method was used. As a precursor to optimization, a Global Systems Analysis was conducted to explore the design space and aid in the set-up of the optimization entity decisions.