Elsje Pienaar, PhD

Tuberculosis (TB) and HIV are deadly infections and TB/HIV co-infection is common. TB/HIV coinfection further complicates the individual infections and presents treatment challenges, including drug-drug interactions, excessive inflammation and reduced treatment efficacy. TB/HIV co-infection is more than the sum of its parts, and it is becoming clear that treatment should be more than standard anti-TB and anti-retroviral treatment given together. Treatment design in the context of host-pathogen-drug interactions can be challenging using experiments alone. This project aims to build a drug development tool integrating experimental models with computational simulations of co-infection. This integrated system considers complex interactions as well as physical structures at the site of infection, all of which affect treatment efficacy. In this project, the team is developing a co-infection disease simulation, building on existing simulations of TB and experimental coinfection results. The disease simulation will set the stage for future applications to quickly and cost-effectively explore large treatment design spaces, predicting optimal treatment strategies to be tested in the experimental model. This integration of experimental and computational approaches advances a drug development strategy in which sophisticated and mechanistic computational tools become part of routine data analysis, complementing usual statistical and image analyses.