Predicting treatment response to vancomycin using bacterial DNA load as a pharmacodynamic marker in premature and very low birth weight neonates: A population PKPD study

Abstract

Background: While positive blood cultures are the gold standard for late-onset sepsis (LOS) diagnosis in premature and very low birth weight (VLBW) newborns, these results can take days, and early markers of possible treatment efficacy are lacking. The objective of the present study was to investigate whether the response to vancomycin could be quantified using bacterial DNA loads (BDLs) determined by real-time quantitative polymerase chain reaction (RT-qPCR).Methods: VLBW and premature neonates with suspected LOS were included in a prospective observational study. Serial blood samples were collected to measure BDL and vancomycin concentrations. BDLs were measured with RT-qPCR, whereas vancomycin concentrations were measured by LC-MS/MS. Population pharmacokinetic–pharmacodynamic modeling was performed with NONMEM.Results: Twenty-eight patients with LOS treated with vancomycin were included. A one-compartment model with post-menstrual age (PMA) and weight as covariates was used to describe the time PK profile of vancomycin concentrations. In 16 of these patients, time profiles of BDL could be described with a pharmacodynamic turnover model. The relationship between vancomycin concentration and first-order BDL elimination was described with a linear-effect model. Slope S increased with increasing PMA. In 12 patients, no decrease in BDL over time was observed, which corresponded with clinical non-response.Discussion: BDLs determined through RT-qPCR were adequately described with the developed population PKPD model, and treatment response to vancomycin using BDL in LOS can be assessed as early as 8 h after treatment initiation.

Integration of individual preclinical and clinical anti‐infective PKPD data to predict clinical study outcomes

“…The PKPD model predictions should be seen as a proxy of treatment response related to the outcome, which may also be valuable for comparing treatment strategies based on preclinical data before clinical information, is available. In future studies, measurements of circulating bacterial DNA as a biomarker of bacterial burden 24 could be used to connect the PKPD model predictions and clinical outcomes. Other extensions of the pharmacometric framework could include linking the predicted bacterial growth to the transitions in a multi‐state model describing clinical and/or microbiological outcomes over time, 25 or to a model of repeated measurements of SOFA scores.…”