Development of a predictive model for antimicrobial activity of titanium dioxide structures surfaces
Despite numerous existing potent antibiotics and other antimicrobial means, bacterial infections are still a major cause of morbidity, implant rejection, and mortality. Moreover, the need to develop additional bactericidal means has significantly increased due to the growing concern regarding multidrug-resistant bacterial strains and biofilm associated infections.
The projects aimed to develop and implement machine learning based model for prediction of the formed structures’ surface antimicrobial activity for targeted gram-negative bacteria. The development of this model would lead to the advanced use of antimicrobial coatings and bacterial control. The main project result – machine learning based model for prediction of the TiO2 structures’ surface antimicrobial activity for targeted gram-negative bacteria and related software.