Lena Friberg, Mats Karlsson, Elisabet Nielsen
Antibiotics are considered one of the greatest discoveries of modern medicine. Today, treatment failures due to multidrug-resistant bacteria are becoming more frequently observed, and both a use and misuse of antibiotics accelerate this phenomenon.
Our research aim to advance the understanding of the pharmacokinetic/pharmacodynamic (PKPD) relationships for antibiotics of value for a more streamlined drug development process and an improved therapeutic use of clinically available antibiotics.
Typically, the PKPD characterization of antibiotics is done based on pre-clinical data and high performing translational methods are thus central in the assessment of an appropriate antibiotic drug use. Mechanism-based models describing time-kill curves from in vitro experiments form the basis of our modelling. The developed models have shown to be applicable across drugs and bacterial strains, for both static and dynamic concentration experiments, for different sizes of start inocula, and for predicting selection of resistance in competition experiments. Based on the developed models, optimal experimental design techniques are applied to find experimental protocols that increase the efficiency of both pre-clinical and clinical studies.
The use of a mechanism-based PKPD modelling approach in dose selection has been suggested for increased robustness and extrapolation potential, especially for special patient populations. To further increase the translatability of pre-clinical results, our current research aim to incorporate the activation and effect of the innate immune response in the model predictions. We also focus on describing the efficacy of antibiotic combination therapies, where the use of mechanism-based modelling that describes the combined effect on the bacterial killing while taking the time-aspect of PK as well as PD into account, is highly advantageous and may facilitate the translation of in vitro information to in vivo.