Published online by Cambridge University Press: 24 February 2015
In the developing of scaffolds for cell culture, a large number of architectures with different combinations of properties should be tested to determine the best. This can be costly in time, money and materials. In this paper we have proposed an optimization model that aims to maximize the growth of osteoblasts on polymeric scaffolds by regulating their properties and architecture. Based on the optimization model it was implemented a genetic algorithm to calculate the architecture and properties of the scaffolds. The fiber diameter, pore diameter, porosity, Young's modulus and contact angle of the scaffolds were calculated through four electrospinning parameters: voltage (kV), concentration (% w/v), flow rate (ml/h) and distance (cm). A fitness value was assigned to each scaffold and the highest one was chosen as the best condition for osteoblast growth. The preliminary results obtained by the Genetic Algorithm were consistent with the tendencies reported experimentally in other studies. Also, the methodology established here can be easily adapted to different types of polymers and cells. Finally, the optimization model can be applied not only by means of heuristic method, like a Genetic Algorithm, but also by exact methods.