Optimization of dosing regimens and dosing in special populations

Treatment of infectious diseases is becoming increasingly challenging with the emergence of less-susceptible organisms that are poorly responsive to existing antibiotic therapies, and the unpredictable pharmacoldnetic alterations arising from complex pathophysiologic changes in some patient populations. In view of this fact, there has been a progressive work on novel dose optimization strategies to renew the utility of forgotten old antibiotics and to improve the efficacy of those currently in use. This review summarizes the different approaches of optimization of antibiotic dosing regimens and the special patient populations which may benefit most from these approaches. The existing methods are based on monitoring of antibiotic concentrations and/or use of clinical covariates. Measured concentrations can be correlated with predefined pharmacokinetic/pharmacodynamic targets to guide clinicians in predicting the necessary dose adjustment. Dosing nomograms are also available to relate observed concentrations or clinical covariates (e.g. creatinine clearance) with optimal dosing. More precise dose prediction based on observed covariates is possible through the application of population pharmacokinetic models. However, the most accurate estimation of individualized dosing requirements is achieved through Bayesian forecasting which utilizes both measured concentration and clinical covariates. Various software programs are emerging to ease clinical application. Whilst more studies are warranted to clarify the clinical outcomes associated with the different dose optimization approaches, severely ill patients in the course of marked infections and/or inflammation including those with sepsis, septic shock, severe trauma, burns injury, major surgery, febrile neutropenia, cystic fibrosis, organ dysfunction and obesity are those groups which may benefit most from individualized dosing. Clinical Microbiology and Infection (C) 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.