Right dose, right now: using big data to optimize antibiotic dosing in the critically ill

Antibiotics save lives and are essential for the practice of intensive care medicine. Adequate antibiotic treatment is closely related to outcome. However this is challenging in the critically ill, as their pharmacokinetic profile is markedly altered. Therefore, it is surprising that critical care physicians continue to rely on standard dosing regimens for every patient, regardless of the actual clinical situation. This review outlines the pharmacokinetic and pharmacodynamic principles that underlie the need for individualized and personalized drug dosing. At present, therapeutic drug monitoring may be of help, but has major disadvantages, remains unavailable for most antibiotics and has produced mixed results. We therefore propose the AutoKinetics concept, taking decision support for antibiotic dosing back to the bedside. By direct interaction with electronic patient records, this opens the way for the use of big data for providing the right dose at the right time in each patient.Antibiotics save lives and are essential for the practice of intensive care medicine. Adequate antibiotic treatment is closely related to outcome. However this is challenging in the critically ill, as their pharmacokinetic profile is markedly altered. Therefore, it is surprising that critical care physicians continue to rely on standard dosing regimens for every patient, regardless of the actual clinical situation. This review outlines the pharmacokinetic and pharmacodynamic principles that underlie the need for individualized and personalized drug dosing. At present, therapeutic drug monitoring may be of help, but has major disadvantages, remains unavailable for most antibiotics and has produced mixed results. We therefore propose the AutoKinetics concept, taking decision support for antibiotic dosing back to the bedside. By direct interaction with electronic patient records, this opens the way for the use of big data for providing the right dose at the right time in each patient