Engineering protein A ligands to mitigate antibody loss during high-pH washes in protein A chromatography

Novel multimodal cation-exchange membrane for the purification of a single-chain variable fragment from Pichia pastoris supernatant

A novel salt-tolerant cation-exchange membrane, prepared with a multimodal ligand, 2-mercaptopyridine-3-carboxylic acid (MMC-MPCA), was examined for its purification properties in a bind-and-elute mode from the high conductivity supernatant of a Pichia pastoris fermentation producing and secreting a single-chain variable fragment (scFv). If successful, this approach would eliminate the need for a buffer exchange prior to product capture by ion-exchange. Two fed-batch fermentations of Pichia pastoris resulted in fermentation supernatants reaching an scFv titer of 395.0 mg/L and 555.7 mg/L, both with a purity of approximately 83 %. The MMC-MPCA membrane performance was characterized in terms of pH, residence time (RT), scFv load, and scFv concentration to identify the resulting dynamic binding capacity (DBC), yield, and purity achieved under optimal conditions. The MMC-MPCA membrane exhibited the highest DBC of 39.06 mg/mL at pH 5.5, with a residence time of 1 min, while reducing the pH below 5.0 resulted in a significant decrease of the DBC to around 2.5 mg/mL. With almost no diffusional limitations, reducing the RT from 2 to 0.2 min did not negatively impact the DBC of the MMC-MPCA membrane, resulting in a significant improvement in productivity of up to 180 mg/mL/min at 0.2 min RT. Membrane fouling was observed when reusing the membranes at 0.2 and 0.5 min RT, likely due to the enhanced adsorption of impurities on the membrane. Changing the amount of scFv loaded onto the membrane column did not show any changes in yield, instead a 10-20 % loss of scFv was observed, which suggested that some of the produced scFv were fragmented or had aggregated. When performing the purification under the optimized conditions, the resulting purity of the product improved from 83 % to approximately 92-95 %.

Predictive mechanistic modeling of loading and elution in protein A chromatography

Protein A chromatography is an enabling technology in current manufacturing processes of monoclonal antibodies (mAbs) and mAb derivatives, largely due to its ability to reduce the levels of process-related impurities by several orders of magnitude. Despite its widespread application, the use of mathematical modeling capable of accurately predicting the full protein A chromatographic process, including loading, post-loading wash and elution stages, has been limited. This work describes a mechanistic modeling approach utilizing the general rate model (GRM), the capabilities of which are explored and optimized using two isotherm models. Isotherm parameters were estimated by inverse-fitting simulated breakthrough curves to experimental data at various pH values. The parameter values so obtained were interpolated across the relevant pH range using a best-fit curve, thus enabling their use in predictive modeling, including of elution over a range of pH. The model provides accurate predictions (< 3% mean error in 10% dynamic binding capacity predictions and ∼ 5% mean error in elution mass and pool volume predictions, both on scale-up) for various residence times, buffer conditions and elution schemes and its effectiveness for use in scale-up and process development is shown by applying the same parameters to larger columns and a wider range of residence times.