Mathematical model and tool to explore shorter multi-drug therapy options for active pulmonary tuberculosis.
John ForsNatasha StrydomWilliam S FoxRon J KeizerRadojka M SavicPublished in: PLoS computational biology (2020)
Standard treatment for active tuberculosis (TB) requires drug treatment with at least four drugs over six months. Shorter-duration therapy would mean less need for strict adherence, and reduced risk of bacterial resistance. A system pharmacology model of TB infection, and drug therapy was developed and used to simulate the outcome of different drug therapy scenarios. The model incorporated human immune response, granuloma lesions, multi-drug antimicrobial chemotherapy, and bacterial resistance. A dynamic population pharmacokinetic/pharmacodynamic (PK/PD) simulation model including rifampin, isoniazid, pyrazinamide, and ethambutol was developed and parameters aligned with previous experimental data. Population therapy outcomes for simulations were found to be generally consistent with summary results from previous clinical trials, for a range of drug dose and duration scenarios. An online tool developed from this model is released as open source software. The TB simulation tool could support analysis of new therapy options, novel drug types, and combinations, incorporating factors such as patient adherence behavior.
Keyphrases
- mycobacterium tuberculosis
- pulmonary tuberculosis
- clinical trial
- immune response
- adverse drug
- climate change
- drug induced
- squamous cell carcinoma
- type diabetes
- randomized controlled trial
- emergency department
- electronic health record
- stem cells
- staphylococcus aureus
- dendritic cells
- machine learning
- endothelial cells
- inflammatory response
- mesenchymal stem cells
- case report
- molecular dynamics
- human immunodeficiency virus
- metabolic syndrome
- hiv infected
- hiv aids
- weight loss
- phase ii
- combination therapy