A Pharmacokinetic-Pharmacodynamic (PKPD) Model Characterizing Resistance for Predictions of Bacterial Kill in vivo
Anders Kristoffersson (1), Pascale David-Pierson (2), Neil J. Parrott (2), Olaf Kuhlmann (2), Thierry Lave (2), Lena E. Friberg (1), Elisabet I. Nielsen (1)
(1) Department of Pharmaceutical Biosciences, Uppsala Universitet, Uppsala, Sweden, (2) Hoffmann LaRoche LtD., Basel, Switzerland
Objectives: Within the infectious disease area, the pharmacokinetic (PK) -pharmacodynamic (PD) characterization is generally limited to the establishment of the so called PK/PD indices or drivers [1]. PK/PD indices are summary endpoints assessed at a single time point and can therefore not accurately describe emergence of resistance. This study aims to predict bacterial kill and resistance development in vivo based on a PKPD model characterizing the in vitro time course of meropenem activity against Pseudomonas aeruginosa.
Methods: A semi-mechanistic PKPD model described the in vitro effect of meropenem on two strains of P. aeruginosa (wild type, and resistant clinical isolate) [2]. Each strain was modelled as consisting of compartments for susceptible and resting bacteria. Regrowth after initial kill was explained by a pre-existing subpopulation with greatly reduced meropenem susceptibility (>200 × higher EC50). The model was evaluated for in vivo conditions by replicating a murine PKPD study [3] using PK established in mice [4], and applied to make predictions of efficacy in humans [5].
Results: The murine in vivo study results were well replicated with the same PK/PD index selected, with similar magnitude required for efficacy. Contrary to expectation [6], the clinical isolate required concentrations above the minimum inhibitory concentration (MIC) for twice as long as the wild type (30 vs. 63 % of the dosing interval). In order to suppress emergence of resistance to meropenem concentrations greatly exceeding the MIC over a large part of the dosing interval are expected to be needed, hence prolonged infusions were required in patients with short meropenem half-life. As expected [7], the clinical maximum daily dose was predicted not to be sufficient to treat the resistant isolate.
Conclusions: An in vivo murine dose finding study was successfully replicated in silico using a PKPD model based on in vitro data. The magnitude of the PK/PD index was found to be sensitive to the susceptibility of the strain. Simulations illustrated that combination therapy is expected to be required to treat infections by the resistant strain. Contrary to the PK/PD indices, a PKPD modelling approach naturally lends itself to investigation of effect from drug combinations. The ability to integrate in vitro findings on resistance with in vivo PK data to provide dosing recommendations is of great potential for dose finding of antibiotics and to guide improved treatment.
References:
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