Crossed mixture design and multiple response analysis for developing complex culture media used in recombinant protein production

A crossed mixture design coupled with data analysis by means of response surface methodology (RSM) and multiple response optimization through a Desirability function (D) was applied for the first time to the area of development and optimization of culture media for the production of recombinant proteins in mammalian cells. A mixture of three hexoses (H1, H2 and H3) was evaluated combined with a mixture of three energy-provider compounds (E1, E2 and E3) to determine the optimal proportion of these components in the culture medium. se surfaces were generated according to two different analyses of empirical data. In the first approach, a model (linear, quadratic or special cubic) dependent on hexose composition was fitted for each response, at each different energy provider mixture. Alternatively, the second approach fitted a quadratic × quadratic product model for every response. In the first analysis, the best empirically tested combination of the E compounds was selected, and the optimal proportions of the hexoses were predicted at this point. On the other hand, following the product model analysis allowed the prediction of the optimal blend of all six components being studied. gh values obtained for function D (0.59, 0.61 and 0.62) are very significant since this function was demanded to satisfy five simultaneous requirements. The predicted mixtures of compounds are expected to maximize cell growth, specific productivity and biological activity of the produced molecule, while minimizing the accumulation of potentially inhibitory by-products.