Antibiotic pharmacodynamics

Pharmacodynamics is classically described as the effect of drugs on the body, which for most drugs relates to effects on pathophysiological processes so as to achieve the desired treatment outcomes. Unlike drugs which act on human cells/organs to elicit their pharmacological effect, antibiotics act on ‘non-physiologic’ bacterial cells to produce pharmacological effect. Because antibiotics are not meant to act on (affect) the human physiological system but rather directly bind or interact with bacterial cells, presents both advantages and challenges in terms of our ability to characterize dose–effect relationships. One important advantage is that, unlike other drugs, we can easily describe concentration–effect relationships of antibiotics in vitro and describe concentrations that achieve inhibition of bacterial growth or maximal killing [1]. This is advantageous not only for designing dosing regimens, but also for optimizing treatment for individual patients relative to the susceptibility of the causative pathogen. Further, advanced in vitro infection models that can simulate human-like pharmacokinetic exposure of bacteria to changing antibiotics concentrations are now available to predict efficacy of novel dosing regimens in patients [2]. On the other hand, whilst for drugs which act by modifying human physiology (e.g. antihypertensive drugs) the actual clinical effect can be readily monitored by an objective clinical end point (e.g. blood pressure monitoring), such a direct objective end point is not possible for antibiotics which act directly on bacterial cells for therapeutic action, i.e. there is no direct human physiological change (signal) induced by the therapeutic action of antibiotics on bacteria. The clinical end point of antibiotic therapy, resolution of infection, remains largely subjective although a number of physiological markers of infection are considered useful surrogate indicators [3]. Unfortunately, the relationship between antibiotic exposure and biomarkers of infection that could signal optimal treatment outcome is not yet well established to guide the design and optimization of dosing regimens. It has not yet been possible to optimize antibiotic dosing based on a graded clinical response