Many liquid formulations for monoclonal antibodies (MAbs) require the final ultrafiltration/diafiltration step to operate at high protein concentrations, often at or above 100 g/L. When operating under these conditions, the excipient concentrations and pH of the final diafiltered retentate are frequently not equal to the corresponding excipient concentrations and pH of the diafiltration buffer. A model based on the Poisson-Boltzmann equation combined with volume exclusion was extended to predict both pH and excipient concentrations in the retentate for a given diafiltration buffer. This model was successfully applied to identify the diafiltration buffer composition required to achieve the desired pre-formulated bulk drug substance (retentate) conditions. Predictions were in good agreement with the experimental results, and reduced the number of experimental iterations needed to define the diafiltration buffer composition. Additionally, the predictive model was applied in a sensitivity analysis across ranges of protein charge, protein concentration, and diafiltration buffer pH and excipient concentration. This sensitivity analysis can facilitate the design of experiments for robustness testing, and allow for generalized predictions across classes of molecules such as MAbs.

A small-volume chromatography system was developed for rapid resin and parameter screening and applied to the purification of a therapeutic monoclonal antibody from a key product-related impurity. Accounting for constraints in peripheral volume, gradient formation, column integrity, and fraction collection in microtiter plates, the resulting system employed 2-mL columns and was successfully integrated with plate-based methods for rapid sample analysis (e. g., use of automated liquid handlers, plate readers, and HPLC). Several cation-exchange chromatography resins were screened using automated programs and tailored gradients for the combination of a particular resin and a given antibody feedstock produced during Phase 1 development. Results from the tailored gradient runs were used to select a resin, and to arrive at efficient stepwise elution schedules for the chosen resin. By maintaining a constant residence time, final operating parameters were successfully scaled to representative bed heights and column diameters up to 2.6 cm (106 mL). This approach significantly improved throughput while reducing development time and material consumption.

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