Back

Macrophage Therapy for Acute Liver Injury (MAIL): a Phase 1 Randomised, Open-Label, Dose-Escalation Study to Evaluate Safety, Tolerability, and Activity of Allogeneic Alternatively Activated Macrophages in Patients with Paracetamol-induced Acute Liver Injury.

Humphries, C.; Addison, M.; Aithal, G.; Boyd, J.; Briody, L.; Campbell, J. D.; Candela, M. E.; Clarke, E.; Coulson, J.; Downing-James, N.; Fontana, R. J.; Geddes, A.; Grahamslaw, J.; Grant, A.; Heye, A.; Hutchinson, J. A.; Jones, A.; Mitchell, F.; Moore, J.; Riddell, A.; Rodriguez, A.; Thomas, A.; Tucker, G.; Walker, K.; Weir, C. J.; Woods, R.; Zahra, S.; Forbes, S. J.; Dear, J.

2024-05-28 toxicology
10.1101/2024.05.28.24306936 medRxiv
Show abstract

IntroductionAcute Liver Failure (ALF) has no effective treatment other than liver transplantation, and is commonly caused by paracetamol overdose. New treatments are needed to treat and prevent ALF. Alternatively activated macrophages (AAMs) can promote resolution of liver necrosis and stimulate hepatocyte proliferation. Using AAMs in unscheduled care requires the use of an allogeneic product. A clinical trial is needed to determine the safety and tolerability of allogeneic AAMs. Methods and analysisA single centre, open-label, dose-escalation, phase 1 randomised trial to determine whether there is dose-limiting toxicity of AAMs in patients with paracetamol-induced acute liver injury. Randomisation will occur at higher doses. Ethics and disseminationThe trial will be conducted according to the ethical principles of the Declaration of Helsinki 2013 and has been approved by North East - York Research Ethics Committee (reference 23/NE/0019), NHS Lothian Research and Development department, and the UK Medicines and Healthcare products Regulatory Agency. When the trial concludes, results will be shared by presentation and publication. Trial registration number: ISRCTN 12637839.

Published in BMJ Open (predicted rank #1) · training set

Matching journals

The top 1 journal accounts 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.