Biocatalytic transamination is being established as key tool for the production of chiral amine pharmaceuticals and precursors due to its excellent enantioselectivity as well as green credentials. Recent examples demonstrate the potential for developing economically competitive processes using a combination of modern biotechnological tools for improving the biocatalyst alongside using process engineering and integrated separation techniques for improving productivities. However, many challenges remain in order for the technology to be more widely applicable, such as technologies for obtaining high yields and productivities when the equilibrium of the desired reaction is unfavorable. This review summarizes both the process challenges and the strategies used to overcome them, and endeavors to describe these and explain their applicability based on physiochemical principles. This article also points to the interaction between the solutions and the need for a process development strategy based on fundamental principles.

Biocatalysis is already established in chemical synthesis on an industrial scale, in particular in the pharmaceutical sector. However, the wider implementation of biocatalysis is currently hindered by the extensive effort required to develop a competitive process. In order that resources spent on development are used in the most efficient manner for these challenging systems, a holistic view on process development and a more in-depth understanding of the underlying constraints (process related as well as biocatalyst related) are required. In this concept article a systematic approach to solve this problem is proposed, involving the use of process tools and methods to assist in development.

Effective estimation of parameters in biocatalytic reaction kinetic expressions are very important when building process models to enable evaluation of process technology options and alternative biocatalysts. The kinetic models used to describe enzyme-catalyzed reactions generally include several parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches. The parameter estimation problem is decomposed into five hierarchical steps, where the solution of each of the steps becomes the input for the subsequent step to achieve the final model with the corresponding regressed parameters. The model is further used for validating its performance and determining the correlation of the parameters. The final model with the fitted parameters is able to describe both initial rate and dynamic experiments. Application of the methodology is illustrated with a case study using the ω-transaminase catalyzed synthesis of 1-phenylethylamine from acetophenone and 2-propylamine.

Previously, it could be demonstrated, that the monophasic, enzymatic reduction of aliphatic 2-ketones into the corresponding (R)-2-alcohols is an adequate and viable method as carried out in a cascade of two enzyme−membrane reactors (Leuchs, S.; Na'amnieh, S. N.; Greiner, L. Green Chemistry 2013, 15, 167−176.). In the present work, the process metrics of the ketone reduction were calculated. A cost analysis revealed that the enzyme costs are negligible, but the cost for nicotinamide cofactor NADP + is dominating the overall cost of the chemical raw material followed by the ionic liquid (TEGO IL K5) used as solubiliser and the buffer. The overall cost of chemicals was €148/kg product . To assess the environmental impact of the process, the E-factor (kg waste /kg product ) 132 and the process mass intensity 133 (PMI, kg substrate /kg product ) were calculated. A process model based on initial rate experiments was elaborated and used to improve the process under cost and environmental aspects. Applying several measures to enhance the cofactor utilisation, the cost base could be reduced by 65% and the E-factor (PMI) to 17 (18).

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