Pharmacokinetic and Pharmacodynamic Modeling of Antibiotics and Bacterial Drug Resistance

University dissertation from Uppsala : Acta Universitatis Upsaliensis

Abstract: Exposure to antibiotics is an important factor influencing the development of bacterial resistance.  In an era where very few new antibiotics are being developed, a strategy for the development of optimal dosing regimen and combination treatment that reduces the rate of resistance development and overcome existing resistance is of utmost importance. In addition, the optimal dosing in subpopulations is often not fully elucidated. The aim of this thesis was to develop pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PKPD) models that characterize the interaction of antibiotics with bacterial growth, killing and resistance over time, and can be applied to guide optimization of dosing regimens that enhance the efficacy of mono- and combination antibiotic therapy.A mechanism-based PKPD model that incorporates the growth, killing kinetics and adaptive resistance development in Escherichia coli against gentamicin was developed based on  in vitro time-kill curve data. After some adaptations, the model was successfully applied for similar data on colistin and meropenem alone, and in combination, on one wild type and one meropenem-resistant strain of Pseudomonas aeruginosa.The developed population PK model for colistin and its prodrug colistin methanesulfonate (CMS) in combination with the PKPD model showed the benefits for applying a loading dose for this drug. Simulations predicted the variability in bacteria kill to be larger between dosing occasions than between patients. A flat-fixed loading dose followed by an 8 or 12 hourly maintenance dose with infusion duration of up to 2 hours was shown to result in satisfactory bacterial kill under these conditions.Pharmacometric models that characterize the time-course of drug concentrations, bacterial growth, antibacterial killing and resistance development were successfully developed. Predictions illustrated how PKPD models based on in vitro data can be utilized to guide development of antibiotic dosing, with examples advocating regimens that (i) promote bacterial killing and reduce risk for toxicity in preterm and term newborn infants receiving gentamicin, (ii) achieve a fast initial bacterial killing and reduced resistance development of colistin in critically ill patients by application of a loading dose, and (iii) overcome existing meropenem resistance by combining colistin and meropenem