Using machine learning to optimise antibiotic combinations: dosing strategies for meropenem and polymyxin B against carbapenem-resistant Acinetobacter baumannii

Abstract Objective Increased rates of carbapenem-resistant Acinetobacter baumannii has forced clinicians to rely upon last-line agents, such as the polymyxins, or empiric, un-optimized combination therapy. Therefore, the objectives of this study were to: (1) evaluate the in vitro pharmacodynamics of meropenem and polymyxin B (PMB) combinations against A. baumannii; (2) utilise a mechanism-based mathematical model to quantify bacterial killing; and (3) develop a genetic algorithm (GA) to define optimal dosing strategies of meropenem and PMB. Methods A. baumannii (N16870; MICmeropenem = 16mg/L, MICPMB = 0.5mg/L) was studied in the hollow-fibre infection model (initial inoculum 108 cfu/mL) over 14 days against meropenem and PMB combinations. A mechanism-based model (MBM) of the data and population pharmacokinetics of each drug were used to develop a GA to define the optimal regimen parameters. Results Monotherapies resulted in regrowth to ∼1010 cfu/mL by 24 h while combination regimens employing high intensity PMB exposure achieved complete bacterial eradication (0 cfu/mL) by 336 h. The MBM demonstrated a SC50 (PMB concentration for 50% of maximum synergy on meropenem killing) of 0.0927mg/L for PMB-susceptible subpopulations versus 3.40mg/L for PMB-resistant subpopulations. The GA had a preference for meropenem regimens that improved the %T>MIC via longer infusion times and shorter dosing intervals. The GA predicted that treating 90% of simulated subjects harbouring a 108 cfu/mL starting inoculum to a point of 100 cfu/mL would require a regimen of meropenem 19.6 g/day 2 h prolonged infusion (2hPI) q5h + PMB 5.17 mg/kg/day 2hPI q6h (where the 0h meropenem and PMB doses should be ‘loaded' with 80.5% and 42.2% of the daily dose, respectively). Conclusion This study provides a methodology leveraging in vitro experimental data, a mathematical pharmacodynamic model, and population pharmacokinetics provides a possible avenue to optimize treatment regimens beyond the use of the "traditional" indices of antibiotic action.