Simulating treatment effects for gonorrhoea using a within-host mathematical model
<i>Neisseria gonorrhoeae</i> (NG) bacteria have evolved resistance to many of the antibiotics used to treat gonorrhoea infection. To explore potential treatment options for gonorrhoea, we extend a previously developed within-host mathematical model to integrate treatment dynamics by accounting for key pharmacokinetic (PK) and pharmacodynamic (PD) features. This extended model was used to investigate different treatment regimens for two potential drugs: monotreatment with gepotidacin, and dual treatment with gentamicin and azithromycin. The simulated treatment success rates aligned well with the limited clinical trial data available. The simulation results indicated that antibiotic treatment failure is associated with failure to successfully clear intracellular NG (NG residing within epithelial cells and neutrophils), and extracellular PK indices alone cannot differentiate between treatment success/failure. Also, the index defined by the ratio of area under the curve to minimum inhibitory concentration (AUC/MIC) index >150, evaluated using intracellular gepotidacin concentration, successfully distinguished between treatment success and failure. For the dual treatment regimen, AUC/MIC index >140 evaluated using the simulated single drug concentration, representing the combined effect of gentamicin and azithromycin with the Loewe additivity concept, successfully differentiated between treatment success and failure. However, we found this PK threshold associated with dual treatment to be less informative than that of gepotidacin, as a majority of samples below this threshold still resulted in infection clearance. Although previous experimental results on antibiotic killing of intracellular NG are scarce, our findings highlight the need for further studies on this. This will be useful for testing putative new anti-gonorrhoea antibiotics.
Authors
- David.G. Regan
- Pavithra Jayasundara
- Philip Kuchel
- James.G. Wood
Institutions
- The University of Sydney (AU)
- UNSW Sydney (AU)
Publication Details
- Journal
- Infectious Disease Modelling
- Published
- 2026-01-27
- DOI
- https://doi.org/10.1016/j.idm.2026.01.002
- Primary Topic
- Bacterial Infections and Vaccines
- Type
- article
- Field-Weighted Citation Impact
- 0.00