Optimization of cultivation conditions for monoclonal IgM antibody production by M1A2 hybridoma using artificial neural network.

Monoclonal antibody (McAb) has been established as one of the most successful therapeutic strategies for the treatment of cancer. M1A2 (McAb) as a new monoclonal antibody was designed to recognize heat shock protein (HSP60), but its optimum production condition has not been studied. In this study, the cell culture conditions for both Roswell Park Memorial Institute Medium (RPMI 1640) and Dulbecco's Modified Eagle Medium (DMEM) were optimized using artificial neural network (ANN) analysis to obtain maximum production of IgM McAb by hybridoma M1A2 cells. By using a central composite design, an experimental matrix with cultivation parameters of incubation time, temperature and fetal bovine serum (FBS) concentration on IgM McAb production was designed. The results was analysed by ANN network with different learning algorithms. From the analysis, batch back propagation (BBP) trained ANN composed of eight hidden nodes using a hyperbolic tangent sigmoid transfer function was capable to provide the highest McAb production for both RPMI and DMEM media. Under optimum conditions of 12.5% of FBS, at 33 °C after 3(1/2) days of incubation, maximum McAb production (1132.69 μg/ml) in DMEM was achieved. With PRMI 1640 medium, maximum McAb production (1105.12 μg/ml) was achieved at optimum conditions of 11% of FBS, at 33 °C after 4 days of incubation. The results of this study will provide information for optimum culture conditions of M1A2 McAb production in both DMEM and RPMI 1640 media and also give some clues for the other hybridoma excreting antibodies in the development of in vitro cell culture.