We combined experimental methods with modeling tools to gain insights into key process parameters of the preparative batch HPLC purification of an active pharmaceutical ingredient (API). A batch-column model was developed to systematically optimize the operating conditions and maximize the yield of the purification as a function of the feed quality. This information would have likely required amounts of API and analytical resources not readily available if obtained experimentally through a statistical design of experiments. A lumped, kinetic batch-elution model for the API and a key isomeric impurity was developed. A bi-Langmuir isotherm was used. The model-based optimized operating conditions enabled the purification of API containing levels of the impurity above release specifications, which in turn avoided the synthesis of new material from scratch. These modeling tools are currently being applied to the design and optimization of other preparative HPLC processes at BMS to complement traditional experimental approaches.

Model-based optimization of preparative batch HPLC for pharmaceutical development

240th National Meeting (2010)

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