ABSTRACT
We designed and implemented simulation models of bacterial growth and antibiotic resistance to determine the appropriate antibiotics to use against antibiotic-resistant bacteria. Simulation models were designed using individual-based modeling, and a simulation tool, ARSim, was developed to conduct experiments using the models. Simulations of bacterial growth were conducted by virtually growing Klebsiella pneumoniae bacteria in a virtual environment with predefined parameters. Other experiments included predicting the effects of antibiotics when added to two different groups, one group of nonresistant bacteria and another group of both resistant and nonresistant bacteria. Carbapenem class antibiotics such as Imipenem were used for the simulation. The simulation results showed that the biological principles of bacteria and their antibiotic resistance mechanisms were correctly designed and implemented. Using the computational approaches developed in this study, we hope to provide researchers with a more effective method for finding new ways to fight antibiotic resistance.
