The response surface methodology speeds up the search for optimal parameters in the photoinactivation of E. coli by...

Antimicrobial Photodynamic Inactivation (a-PDI) is based on the oxidative destruction of biological molecules by reactive oxygen species generated by the photo-excitation of a photosensitive molecule. When a-PDT is performed with the use of mathematical models, the optimal conditions for maximum inactivation are found. Experimental designs allow a multivariate analysis of the experimental parameters. This is usually made using a univariate approach, which demands a large number of experiments, being time and money consuming. This paper presents the use of the response surface methodology for improving the search for the best conditions to reduce E. coli survival levels by a-PDT using methylene blue (MB) and toluidine blue (TB) as photosensitizers and white light. The goal was achieved by analyzing the effects and interactions of the three main parameters involved in the process: incubation time (IT), photosensitizer concentration (C_PS), and light dose (LD). The optimization procedure began with a full 2³ factorial design, followed by a central composite one, in which the optimal conditions were estimated. For MB, C_PS was the most important parameter followed by LD and IT whereas, for TB, the main parameter was LD followed by C_PS and IT. Using the estimated optimal conditions for inactivation, MB was able to inactivate 99.999999% CFU mL^-1 of E. coli with IT of 28 min, LD of 31 J cm^-2, and C_PS of 32 μmol L^-1, while TB required 18 min, 39 J cm^-2, and 37 μmol L^-1. The feasibility of using the response surface methodology with a-PDT was demonstrated, enabling enhanced photoinactivation efficiency and fast results with a minimal number of experiments.