QbD Strategies for Managing Chromatography Resin Lot-to-Lot Variability Based On Design of Experiments and Monte Carlo Simulation

Quality by Design highlights the need for better process understanding, both regarding Critical Process Parameters and Critical Raw Material Attributes (CMA’s). Chromatographic media contain several potential CMA’s, and GE Healthcare is considering a multifaceted raw material framework that focuses on identification of CMA’s through dedicated studies and intensified supplier – end user collaboration efforts.
The framework will be illustrated by examples describing process characterization studies performed using high-throughput process development tools and chromatography medium batches with varying attributes within respective specification ranges. The underlying principle behind this approach should be contrasted to typical resin screening where different resins are compared, as in the proposed framework all attributes reflect the normal manufacturing variation within one resin product. Special emphasis will be placed on ligand density, one of the top CMA candidates as it can affect chromatographic selectivity.
The framework employs HTPD data, Design of Experiments and Monte Carlo simulation to establish the effect of chromatography medium attributes and selected process parameters on CQA’s. The evaluation includes process parameter adaptation by looking for parameter interactions that allow an adaptive control strategy where the effect of variations in chromatography medium attributes can be counteracted by changing process parameters. The proposed approach outperforms conventional testing of a few resin lots from normal production by explicitly investigating a potential CMA.
When established, the adaptive process control strategy maintains the process within the defined operating window, yet minimizes effects related to chromatography medium lot to lot variability and/or eventually leading to a non-critical assessment of the medium from the raw material classification perspective. The proposed adaptive control strategy will result in a more robust purification step and increased security of supply, and in turn better process economy.