Application of Membrane Separation Processes in the Pharmaceutical Industry – A Study of Process Development for Overcoming Membrane Limitations

The prevalent business model in the pharmaceutical industry requires rapid and robust process development and flexible manufacturing processes. This work reports the attempts to develop structured procedures for membrane process development to meet these requirements. The Donnan Steric Pore Model, in conjunction with a computational molecular dynamics programme, was evaluated as tool for membrane performance predictions to circumvent the need for tedious membrane screening experiments. However, the computational effort required was too onerous, making experimentation more efficient than computational method at this stage. Process chemistry manipulation enabled the use of otherwise incompatible membranes for separation and reduced the time needed for membrane scoping. Firstly, through pH manipulation to selectively increase electrostatic sieving, the permeation selectivity of a membrane to 2 different solutes was changed. Secondly, a structured procedure for polyalkylation of an ‘anchor’ molecule to increase the steric hindrance of an organocatalyst was used to enable the total retention of the catalyst so that a single stage membrane recycling strategy for the catalyst could be enacted. Published membrane processes were analysed and found to lack robustness and to be too sensitive to slight deviations in membrane performance. Hence new membrane processes were devised to address these challenges. Firstly, a membrane cascade process was used to enhance the rejection of an active pharmaceutical ingredient (API) over the single pass membrane rejection. This cascade process was then used for concurrent API concentration and solvent recovery. Secondly, a permeable stripping cascade configuration was used for the removal of an excess reagent from an API to enable the excess loading of the reagent to increase the yield of the API. The membrane cascades benefited from enhanced reliability, increased productivity and improved robustness