Fernandez-Nunez E.G.,University of Sao Paulo |
Fernandez-Nunez E.G.,University Estadual Julio Of Mesquita Filho Campus Assis |
de Rezende A.G.,Instituto Butantan |
Puglia A.L.P.,Instituto Butantan |
And 4 more authors.
Biotechnology Letters | Year: 2015
Objective: To assess the expression of rabies virus G-glycoprotein (RVGP) expression using Semliki Forest virus as a vector in combination with BHK-21 cells cultured in suspension. Results: A multilevel factorial design was used to quantify effects of temperature (33–37 °C), fresh medium addition after the viral adsorption step (100–200 % with respect to the initial cell suspension volume before infection) and harvest time (8–40 h) on RVGP production. Experimental runs were performed in 24-well cell culture plates at a multiplicity of infection (MOI) of 16. An additional experiment in spinner-flask was performed at MOI of 9, using the optimal conditions determined in cell culture plates. Values for temperature, fresh medium addition and harvest time of 33 °C, 100 % and 16 h, respectively, ensured the optimal RVGP production in culture plates. The volumetric yield (239 ng ml−1) in these conditions was higher than that reported previously for adherent cell culture. In spinner-flasks, the volumetric yield was improved (559 ng ml−1). Conclusion: These results establish the basis for designing bioprocess to produce RVGP. © 2015, Springer Science+Business Media Dordrecht. Source
Buenno L.H.,University Estadual Julio Of Mesquita Filho Campus Assis |
Rocha J.C.,University Estadual Julio Of Mesquita Filho Campus Assis |
Leme J.,Instituto Butantan |
Caricati C.P.,Instituto Butantan |
And 3 more authors.
Biotechnology Progress | Year: 2015
This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions. © 2015 American Institute of Chemical Engineers. Source