Mechanism-based modelling of the response from hypermutable cystic fibrosis Pseudomonas aeruginosa isolates to inhaled aztreonam and tobramycin dosing regimens simulated in a dynamic biofilm model

Background

Hypermutable, resistant and biofilm forming Pseudomonas aeruginosa proves challenging to treat in patients with cystic fibrosis (CF). Understanding biofilm killing and regrowth is important for the selection of effective antibiotic dosing regimens.

Aim

To develop a mechanism-based model (MBM) which characterises the time-course of planktonic and biofilm bacteria in response to aztreonam and tobramycin regimens, in monotherapy and combination.

Methods

168h dynamic in vitro biofilm studies exposed two multidrug-resistant hypermutable CF isolates to simulated regimens of inhaled aztreonam (75mg, q8h) and tobramycin (300mg, q12h), in monotherapy and combination (n=2/isolate). Total viable and resistant counts were determined for planktonic and biofilm bacteria. An MBM was developed using S-ADAPT (version 1.57) facilitated by SADAPT-TRAN with the importance sampling algorithm (pmethod=4) to simultaneously estimate all pharmacodynamic model parameters.   

Results

The MBM included two subpopulations, inhibition of successful replication by aztreonam, direct bacterial killing by tobramycin and mechanistic synergy. Each growth mode was simultaneously modelled across isolates, with population fits well describing the total and resistant bacterial counts for all treatments. Biofilm bacteria had a lower maximum killing rate constant of tobramycin compared to planktonic. A lower aztreonam concentration for half-maximal inhibition of replication in resistant biofilm bacteria was seen, however the longer mean generation time of the biofilm attenuated this effect. The MBM indicated greater mechanistic synergy against biofilm compared to planktonic bacteria.

Conclusions

The MBM well described the synergistic effects of aztreonam and tobramycin against planktonic and biofilm bacteria, and identified common trends in pharmacodynamic parameter estimates across the isolates.

Bonnie.Breen

  • Monash University

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