Most biotechnology unit operations are complex in nature with numerous process variables, feed material attributes, and raw material attributes that can have significant impact on the performance of the process. Design of experiments (DOE)-based approach offers a solution to this conundrum and allows for an efficient estimation of the main effects and the interactions with minimal number of experiments. Numerous publications illustrate application of DOE towards development of different bioprocessing unit operations. However, a systematic approach for evaluation of the different DOE designs and for choosing the optimal design for a given application has not been published yet. Through this work we have compared the I-optimal and D-optimal designs to the commonly used central composite and Box-Behnken designs for bioprocess applications. A systematic methodology is proposed for construction of the model and for precise prediction of the responses for the three case studies involving some of the commonly used unit operations in downstream processing. Use of Akaike information criterion for model selection has been examined and found to be suitable for the applications under consideration.

Aggregation of biotech products used therapeutically, such as antibodies, can contribute to potential immunogenicity of the product. Charge-based heterogeneities may also impact the safety and/or efficacy of a therapeutic. In this study, an approach based on empirical modeling and least squares regression is suggested for establishing hold times for process intermediates during production of monoclonal antibody (Mab) therapeutics. Two immunoglobulins were analyzed with respect to aggregation and charge heterogeneity in buffer conditions that are typically used during downstream processing of Mab products. Size exclusion chromatography, ion exchange chromatography (IEC), and circular dichroism were used. We found that aggregation primarily occurs at pH 3 (buffers used in affinity chromatography) and is higher in citrate buffer compared to acetate and glycine buffers. Aggregation is minimal in buffers used in anion exchange chromatography (Tris-HCl buffer at pH 7.2 and 8) and in cation exchange chromatography (citrate buffer at pH 6, acetate buffer at pH 6, and phosphate buffer at pH 6.5 and 7.5). The behavior is opposite in the case of charged heterogeneities (basic and acidic variants) as measured by IEC. The product is more susceptible to degradation at high pH than at low pH. The data presented here demonstrate that product stability can be a significant issue within the routinely used manufacturing conditions. We suggest that the approach presented needs to be adopted by all manufacturers to ensure product stability during processing.

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Chromatography has long been, and remains, the workhorse of downstream processing in the production of biopharmaceuticals. As bioprocessing has matured, there has been a growing trend toward seeking a detailed fundamental understanding of the relevant unit operations, which for some operations include the use of mechanistic modeling in a way similar to its use in the conventional chemical process industries. Mechanistic models of chromatography have been developed for almost a century, but although the essential features are generally understood, the specialization of such models to biopharmaceutical processing includes several areas that require further elucidation. This review outlines the overall approaches used in such modeling and emphasizes current needs, specifically in the context of typical uses of such models; these include selection and improvement of isotherm models and methods to estimate isotherm and transport parameters independently. Further insights are likely to be aided by molecular-level modeling, as well as by the copious amounts of empirical data available for existing processes.

Achieving consistent product quality of a biotherapeutic is a major target for any biopharmaceutical manufacturer, even more for a biosimilar producer as comparability with the innovator product is a regulatory expectation. The complexity of biotherapeutic products and their tedious manufacturing processes, however, make this a non-trivial exercise. The primary motivation of this work is to develop an integrated chromatographic platform for purification of monoclonal antibody (mAb) therapeutics that can deliver the desired separation of both charge variants and aggregates, in addition to the process related impurities like host cell proteins (HCP) and host cell DNA. To achieve the same, an integrated two-stage chromatographic process platform consisting of cation exchange chromatography and multimodal chromatography is being proposed. The versatility of the proposed platform has been successfully demonstrated for three different mAbs. It have been shown that in each case charge variant separation is achieved with the required clearance of aggregates (<1%), HCP (<10 ppm), and DNA (<5 ppb). Moreover, the proposed platform is conducive to use for development of a continuous process and offers smaller process time, lower buffer utilization, and decreased operational costs when compared to the conventional purification platforms.

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