TY - JOUR
T1 - Right dose, right now
T2 - Using big data to optimize antibiotic dosing in the critically ill
AU - Roggeveen, Luca F.
AU - Guo, Tingjie
AU - Fleuren, Lucas M.
AU - Driessen, Ronald
AU - Thoral, Patrick
AU - van Hest, Reinier M.
AU - Mathot, Ron A. A.
AU - Swart, Eleonora L.
AU - de Grooth, Harm-Jan
AU - van den Bogaard, Bas
AU - Girbes, Armand R. J.
AU - Bosman, Rob J.
AU - Elbers, Paul W. G.
N1 - © 2022. The Author(s).
PY - 2015/12/4
Y1 - 2015/12/4
N2 - 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.
AB - 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.
KW - Antibiotics
KW - Autokinetics
KW - Decision support
KW - Electronic patient record
KW - Intensive care critical care
KW - Pharmacokinetics
UR - http://www.scopus.com/inward/record.url?scp=84949751881&partnerID=8YFLogxK
U2 - https://doi.org/10.5603/AIT.a2015.0061
DO - https://doi.org/10.5603/AIT.a2015.0061
M3 - Review article
C2 - 26459228
SN - 1466-609X
VL - 47
SP - 457
EP - 463
JO - Critical care (London, England)
JF - Critical care (London, England)
IS - 5
M1 - 265
ER -