Nearly 30% of currently approved recombinant therapeutic proteins are produced in Escherichia coli. Due to its well-characterized genetics, rapid growth and high-yield production, E. coli has been a preferred choice and a workhorse for expression of non-glycosylated proteins in the biotech industry. There is a wealth of knowledge and comprehensive tools for E. coli systems, such as expression vectors, production strains, protein folding and fermentation technologies, that are well tailored for industrial applications. Advancement of the systems continues to meet the current industry needs, which are best illustrated by the recent drug approval of E. coli produced antibody fragments and Fc-fusion proteins by the FDA. Even more, recent progress in expression of complex proteins such as full-length aglycosylated antibodies, novel strain engineering, bacterial N-glycosylation and cell-free systems further suggests that complex proteins and humanized glycoproteins may be produced in E. coli in large quantities. This review summarizes the current technology used for commercial production of recombinant therapeutics in E. coli and recent advances that can potentially expand the use of this system toward more sophisticated protein therapeutics.

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The concept of "design space" has been proposed in the ICH Q8 guideline and is gaining momentum in its application in the biotech industry. It has been defined as "the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality." This paper presents a stepwise approach for defining process design space for a biologic product. A case study, involving P. pastoris fermentation, is presented to facilitate this. First, risk analysis Via Failure Modes and Effects Analysis (FMEA) is performed to identify parameters for process characterization. Second, small-scale models are created and qualified prior to their use in these experimental studies. Third, studies are designed using Design of Experiments (DOE) in order for the data to be amenable for use in defining the process design space. Fourth, the studies are executed and the results analyzed for decisions on the criticality of the parameters as well as on establishing process design space. For the application under consideration, it is shown that the fermentation unit operation is very robust with a wide design space and no critical operating parameters. The approach presented here is not specific to the illustrated case study. It can be extended to other biotech unit operations and processes that can be scaled down and characterized at small scale.