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.

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.

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Whole Escherichia coli cells overexpressing ω-transaminase (ω-TA) and immobilized cells entrapped in LentiKats® were used as biocatalysts in the asymmetric synthesis of the aromatic chiral amines 1-phenylethylamine (PEA) and 3-amino-1-phenylbutane (APB). Whole cells were permeabilized with different concentrations of cetrimonium bromide (CTAB) and ethanol; the best results were obtained with CTAB 0.1% which resulted in an increase in reaction rate by 40% compared to the whole cells. The synthesis of PEA was carried out using isopropyl amine (IPA) and L-alanine (Ala) as amino donors. Using whole cell biocatalysis, the reaction with IPA was one order of magnitude faster than with Ala. No reaction was detected when permeabilized E. coli cells containing ω-TA were employed using Ala as the amino donor. Additionally, the synthesis of APB from 4-phenyl-2-butanone and IPA was studied. Whole and permeabilized cells containing ω-TA and their immobilized LentiKats® counterparts showed similar initial reactions rates and yields in the reaction systems, indicating 100% of immobilization efficiency (observed activity/activity immobilized) and absence of diffusional limitations (due to the immobilization). Immobilization of whole and permeabilized cells containing ω-TA in LentiKats® allowed improved stability as the biocatalyst was shown to be efficiently reused for five reaction cycles, retaining around 80% of original activity.