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Updated: Jul 20, 2025
A Novel Method to Determine the Longitudinal Antibacterial Activity of Drug-Eluting Materials
Published on: March 3, 2023
Feasibility of individualised patient modelling for continuous vancomycin infusions in outpatient antimicrobial
J Nolan1,2, K McCarthy3,4, A Farkas5,6
1The Royal Brisbane and Women's Hospital, Herston, Australia. j.nolan@uq.edu.au.
Background:
The area under the curve (AUC) to minimum inhibitory concentration (MIC) ratio is proposed as a therapeutic drug-monitoring parameter for dosing vancomycin continuous infusion in methicillin-resistant Staphylococcus aureus (MRSA) infection. Individualised pharmacokinetic-pharmacodynamic (PK/PD) calculation of AUC24 may better represent therapeutic dosing than current Therapeutic Drug Monitoring (TDM) practices, targeting a Steady State Concentration of 15-25 mg/L.
Aim:
To compare real world TDM practice to theoretical, individualised, PK/PD target parameters utilising Bayesian predictions to steady state concentrations (Css) for outpatients on continuous vancomycin infusions.
Method:
A retrospective single centre study was conducted at a tertiary hospital on adult patients, enrolled in an outpatient parenteral antimicrobial therapy (OPAT) program, receiving vancomycin infusions for MRSA infection. Retrospective Bayesian dosing was modelled to target PK/PD parameters and compared to real world data.
Results:
Fifteen patients were evaluated with 53% (8/15) achieved target CSS during hospitalisation, and 83% (13/15) as outpatient. Median Bayesian AUC/MIC was 613 mg.h/L with CSS 25 mg/L. Patients suffering an Acute Kidney Injury (33%) had higher AUC0-24/MIC values. Retrospective Bayesian modelling demonstrated on median 250 mg/24 h lower doses than that administered was required (R2 = 0.81) which achieved AUC24/MIC median 444.8 (range 405-460) mg.h/L and CSS 18.8 (range 16.8-20.4) mg/L.
Conclusion:
Bayesian modelling could assist in obtaining more timely target parameters at lower doses for patients receiving continuous vancomycin infusion as part of an OPAT program, which may beget fewer adverse effects. Utilisation of personalised predictive modelling may optimise vancomycin prescribing, achieving earlier target concentrations as compared to empiric dosing regimens.
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