Integration of individual preclinical and clinical anti‐infective PKPD data to predict clinical study outcomes - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Clinical and Translational Science. Année : 2024

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

Amir Nutman
Jonathan Lellouche
Lena Friberg

Résumé

The AIDA randomized clinical trial found no significant difference in clinical failure or survival between colistin monotherapy and colistin–meropenem combination therapy in carbapenem‐resistant Gram‐negative infections. The aim of this reverse translational study was to integrate all individual preclinical and clinical pharmacokinetic–pharmacodynamic (PKPD) data from the AIDA trial in a pharmacometric framework to explore whether individualized predictions of bacterial burden were associated with the trial outcomes. The compiled dataset included for each of the 207 patients was (i) information on the infecting Acinetobacter baumannii isolate (minimum inhibitory concentration, checkerboard assay data, and fitness in a murine model), (ii) colistin plasma concentrations and colistin and meropenem dosing history, and (iii) disease scores and demographics. The individual information was integrated into PKPD models, and the predicted change in bacterial count at 24 h for each patient, as well as patient characteristics, was correlated with clinical outcomes using logistic regression. The in vivo fitness was the most important factor for change in bacterial count. A model‐predicted growth at 24 h of ≥2‐log 10 (164/207) correlated positively with clinical failure (adjusted odds ratio, aOR = 2.01). The aOR for one unit increase of other significant predictors were 1.24 for SOFA score, 1.19 for Charlson comorbidity index, and 1.01 for age. This study exemplifies how preclinical and clinical anti‐infective PKPD data can be integrated through pharmacodynamic modeling and identify patient‐ and pathogen‐specific factors related to clinical outcomes – an approach that may improve understanding of study outcomes.

Domaines

Pharmacologie
Fichier principal
Vignette du fichier
Integration of individual preclinical and clinical anti‐infective.pdf (2.15 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Licence

Dates et versions

hal-04645902 , version 1 (12-07-2024)

Licence

Identifiants

Citer

Vincent Aranzana-Climent, Wisse van Os, Amir Nutman, Jonathan Lellouche, Yael Dishon-Benattar, et al.. Integration of individual preclinical and clinical anti‐infective PKPD data to predict clinical study outcomes. Clinical and Translational Science., 2024, 17 (7), ⟨10.1111/cts.13870⟩. ⟨hal-04645902⟩

Collections

UNIV-POITIERS PHAR
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More