Developing Antibiotic Regimens Using Evolutionary Algorithms

Antibiotics have been given to food animals for several decades as a performance enhancer. For nearly as long there has been a concern that using these antimicrobials in production animals could lead to bacteria developing resistance to antibiotics and eventually escaping into the human population. While this risk is still undefined, it would be of benefit to minimize the ratio of resistant bacteria to susceptible bacteria while still maintaining the benefits of administering performance enhancers. In this study we use graph based evolutionary algorithms to find a variety of antibiotic treatment regimens that maintain the weight gain granted by antibiotic use while minimizing the risk from the presence of resistant bacteria. Previous work investigated the effect on Campylobacter.spp only. This study examines different regimens of Tylosin Phosphate use on all bacteria populations, divided into Gram positive and Gram negative types, with a focus on Campylobacter.spp