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Computational fluid dynamics (CFD) is well established as a tool of choice for solving problems that involve one or more of the following phenomena: flow of fluids, heat transfer,mass transfer, and chemical reaction. Unit operations that are commonly utilized in biotechnology processes are often complex and as such would greatly benefit from application of CFD. The thirst for deeper process and product understanding that has arisen out of initiatives such as quality by design provides further impetus toward usefulness of CFD for problems that may otherwise require extensive experimentation. Not surprisingly, there has been increasing interest in applying CFD toward a variety of applications in biotechnology processing in the last decade. In this article, we will review applications in the major unit operations involved with processing of biotechnology products. These include fermentation,centrifugation, chromatography, ultrafiltration, microfiltration, and freeze drying. We feel that the future applications of CFD in biotechnology processing will focus on establishing CFD as a tool of choice for providing process understanding that can be then used to guide more efficient and effective experimentation. This article puts special emphasis on the work done in the last 10 years.

The concept of "design space" plays an integral part in implementation of quality by design for pharmaceutical products. ICH Q8 defines design space 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. Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post-approval change process. Design space is proposed by the applicant and is subject to regulatory assessment and approval." Computational fluid dynamics (CFD) is increasingly being used as a tool for modeling of hydrodynamics and mass transfer. In this study, a laboratory-scale aerated bioreactor is modeled using CFD. Eulerian-Eulerian multiphase model is used along with dispersed k-ε turbulent model. Population balance model is incorporated to account for bubble breakage and coalescence. Multiple reference frame model is used for the rotating region. We demonstrate the usefulness of CFD modeling for evaluating the effects of typical process parameters like impeller speed, gas flow rate, and liquid height on the mass transfer coefficient (k(L)a). Design of experiments is utilized to establish a design space for the above mentioned parameters for a given permissible range of k(L)a.

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