ABSTRACT
Antibiotic resistance is one of the biggest health threats right now, with 1.27 million people being directly killed by it in 2019. While bacteriophage therapy has emerged as an alternative to antibiotics, the dynamics between phages, bacteria, and antibiotics remain poorly understood. Current research often suffers significant limitations: math models often lack experimental validation, and empirical phage studies don’t provide a quantitative and predictive framework. This project addresses these gaps by developing an integrated computational-experimental approach to create a mathematical model and validate it. We propose to create this mathematical model using ordinary differential equations to simulate the population dynamics of both susceptible and resistant bacteria when being pressured by both the phages and antibiotics. The model will be implemented in both a deterministic and stochastic framework, and parameter values for E. coli and T7-like phages will be taken from literature. The model will later be validated through experimental testing which will find the population of susceptible and resistant bacteria after a week in vitro with phages and antibiotics. This research represents a shift from traditional single-disciplinary approaches toward an integrated approach that combines both mathematical rigor and biological experimentation.
Graphical ABSTRACT
