The Michaelis-Menten model is used to model data for various chemical applications. Recent examples using Michaelis-Menten type kinetic modeling include: the modeling of damson plum polyphenol oxidase enzyme for different substrate concentrations; kinetic characteristic modeling of biological simultaneous anaerobic sulfide and nitrite removal; glucose oxidase kinetics consistency with the Michaelis-Menten model; and the bioremediation efficiency of soil fungi for the removal of pesticide toxicants. In this presentation we will use simulations to model improved percent product yield to controlled experimental conditions. Johnson and Huang (2006) previously examined product yield of oxazoline and examined models developed with independent variables of temperature (oC) and the concentration of amino alcohol (Molar concentration). The concentration of carboxylic acid was fixed at a constant in order to measure the effects of temperature (X1) and the concentration of amino alcohol (X2). For this presentation Y(ield) varies from 70% yield to 99% yield and a Beta (α, β) prior distribution is used in simulation. The experiments were quantified so that at a certain point in time changes in the independent variables produced no significant increase in yield; thus indicating a plateau of values after that point. Of interest was when this point was reached and the experimental conditions of this point. The simulated data is used to illustrate methodology. SAS® will be used to perform the data analysis.

The Michaelis-Menten model is used to model data for various chemical applications. Recent examples using Michaelis-Menten type kinetic modeling include: the modeling of damson plum polyphenol oxidase enzyme for different substrate concentrations; kinetic characteristic modeling of biological simultaneous anaerobic sulfide and nitrite removal; glucose oxidase kinetics consistency with the Michaelis-Menten model; and the bioremediation efficiency of soil fungi for the removal of pesticide toxicants. In this presentation we will use simulations to model improved percent product yield to controlled experimental conditions. Johnson and Huang (2006) previously examined product yield of oxazoline and examined models developed with independent variables of temperature (^o^C) and the concentration of amino alcohol (Molar concentration). The concentration of carboxylic acid was fixed at a constant in order to measure the effects of temperature (X~1~) and the concentration of amino alcohol (X~2~). For this presentation Y(ield) varies from 70% yield to 99% yield and a Beta (α, β) prior distribution is used in simulation. The experiments were quantified so that at a certain point in time changes in the independent variables produced no significant increase in yield; thus indicating a plateau of values after that point. Of interest was when this point was reached and the experimental conditions of this point. The simulated data is used to illustrate methodology. SAS^®^ will be used to perform the data analysis.

The Michaelis-Menten model used to model product yield

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