Back

LEAF- 4L6715 enhances oxygenation in patients with acute respiratory distress syndrome (ARDS) due to severe COVID-19: Final results of a phase I/II clinical trial

Mertes, P.-M.; Delabranche, X.; Coliat, P.; Roche, A.-C.; Collange, O.; Voegelin, M.; Bernard, A.; Dhindsa, N.; Xu, H.; Geng, B.; Niyikiza, C.; Moyo, V.; Bourbon, C.; Villa, P.; Detappe, A.; Pivot, X.

2022-09-10 respiratory medicine
10.1101/2022.09.07.22279668 medRxiv
Show abstract

LEAF-4L6715 is a liposomal formulation encapsulating transcrocetin (TC) developed to enhance the diffusion of oxygen in the body. Here, we report the final results of the phase I/II clinical trial (NCT04378920; EUDRACT2020-001393-30) initiated to identify an optimal regimen and to assess the activity of TC in the context of acute respiratory distress syndrome (ARDS). More specifically, LEAF-4L6715 was developed to treat patients with ARDS due to severe SARS-CoV-2 infection who have a ratio of partial arterial pressure to inspired fraction of oxygen (PaO2/FiO2 ratio) <200 treated with artificial ventilation support in an intensive care unit. A total of 37 patients were treated (across 6 dosing cohorts) with LEAF-4L6715 given as an intravenous infusion for over 90 minutes. The dose of LEAF-4L6715 was increased until the transaminase levels were elevated and 4 grade 3 events occurred among 8 patients. The recommended dosage was determined to be a fixed concentration of 300 mg administered every 12 hours. An improvement in the PaO2/FiO2 ratio and SOFA score was observed. The overall 28-day survival rate of 81%. This study identified the recommended dose for LEAF 4L6715 and the dose-limiting toxicity and showed an overall favorable risk/benefit profile. These preliminary findings are promising for the activity of LEAF-4L6715 but will require confirmation in a randomized phase III trial.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.