Predicting the Effectiveness of Novel Tuberculosis Regimens

Taylor Joseph, a student from Michigan State University, worked with Dr. Andreas Handel to use computational methods to examine new tuberculosis treatment regimes.

Abstract: Tuberculosis (TB) remains one of the world’s most deadly diseases, as current treatment protocols are far outdated and often ineffective. Furthermore, current regimens are complicated and last many months, often leading to patient non-compliance and drug resistant bacteria. There is thus a need for more effective and efficient treatment strategies, yet conducting human trials on these new strategies is expensive and time consuming. As an alternative or supplement to human and animal trials, computational models may be used to predict the outcomes of new treatment strategies. In this study, we use a system of differential equations to describe within-host dynamics of TB and drug treatment, and we assess the model’s accuracy in comparison to data collected from previous clinical studies. We then use the model to predict and evaluate the outcome of new treatment regimens.


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