António Lima Grilo

The monoclonal antibody (mAb) industry is witnessing unprecedented growth, with an increasing range of new molecules and biosimilars as well as disease targets approved than ever before. Competition necessitates pharmaceutical companies to reduce development/production costs and time‐to‐market. To this aim, mathematical modeling can aid traditional experiment‐only‐based process development by reducing the design space, integrating scales, and assisting in identifying optimal operating conditions in less time and with lower expense. Mathematical models have been employed by other industries for control and optimization purposes and are important decisional tools for testing scenarios, process configurations, operating conditions, etc. Herein, a predictive, experimentally validated mathematical model that captures cellular metabolism and growth with cell cycle, cell death (apoptosis), and mAb production in GS–NS0 cells is presented. The model utilizes cellular, metabolic, and gene expression data, highlighting how multiple data sources can be integrated in one tool with the aim of optimizing mammalian cell bioprocessing.

Monoclonal antibodies currently dominate the biopharmaceutical market with growing sales having reached 80 billion USD in 2016. As most top‐selling mAbs are approaching the end of their patent life, biopharmaceutical companies compete fiercely in the biosimilars market. These two factors present a strong motivation for alternative process strategies and process optimization. In this work a novel purification strategy for monoclonal antibodies comprising phenylboronic acid multimodal chromatography for capture followed by polishing by ion‐exchange monolithic chromatography and packed bed hydrophobic interaction chromatography is presented and compared to the traditional protein‐A‐based process. Although the capital investment is similar for both processes, the operation cost is 20% lower for the novel strategy. This study shows that the new process is worthwhile investing in and could present a viable alternative to the platform process used by most industrial players.

Over the last years, aqueous two-phase systems (ATPS) regained an increasing interest due to their potential in the downstream processing of biomolecules. After many years with only a few articles published, a lot of effort and work has been put into studying these systems for the partitioning of a range of compounds including proteins, organic low-molecular weight molecules or metal ions. Although several research and review articles appeared, a background review on ATPS partitioning fundamentals is needed. In this article, partitioning theories and main effects of several important factors for partitioning, such as molecular weight of the polymer, effect of added salts, pH, electrical charges, and temperature on phase diagrams, tie-line lengths, interfacial tension and settling time of the two aqueous phases are extensively reviewed. The trend in ATPS research is given compiling the recent 2008–2013 research articles published in the field.