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

Tingjie Guo, Lucas M. Fleuren, Ronald Driessen, Patrick Thoral, Reinier M. van Hest, Ron A. A. Mathot, Eleonora L. Swart, Harm-Jan de Grooth, Bas van den Bogaard, Armand R. J. Girbes, Rob J. Bosman, Paul W. G. Elbers

Research output: Contribution to journalReview articleAcademicpeer-review

20 Citations (Scopus)


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, although therapeutic drug monitoring may be of help, it 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.

Original languageEnglish
Article number265
Pages (from-to)457-463
Number of pages7
JournalCritical care (London, England)
Issue number5
Publication statusPublished - 4 Dec 2015


  • Antibiotics
  • Autokinetics
  • Decision support
  • Electronic patient record
  • Intensive care critical care
  • Pharmacokinetics

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