Abstract
The European Society for Blood and Marrow Transplantation (EBMT), established in 1974, is the leading scientific society for professionals involved in haematopoietic stem-cell transplantation (HSCT).
The 2016 EBMT Annual Meeting, held in Valencia, Spain, brought together over 4,500 scientists, physicians, nurses, biologists, pharmacists, technicians and patients to discuss scientific data across a wide range of topics. New for this year was the 1st EBMT Pharmacists’ Day, viewing therapies from the pharmacist’s perspective, with the objective of achieving maximum clinical benefit. Here, and across the entire meeting, a major focus was invasive fungal infections (IFI). Despite the availability of three classes of antifungals (AFs) to treat IFI (including polyenes, azoles and echinocandins), mortality in haemato-oncology patients remains unacceptably high. Across the EBMT 2016 sessions, key opinion leaders highlighted the urgent need to improve management of IFI, and the bioavailability (BA) of azoles. Current strategies include the new tablet formulation of posaconazole, administered once a day (o.d.) without food; the extended half-life of the new prodrug isavuconazole; use of combination therapy; and personalized therapy such as dosing voriconazole according to CYP2C19 genotype. Looking to the future experimental strategies, including developing agents that destroy the biofilm which prevents AFs from reaching intracellular targets and loading neutrophils with azoles, were presented.Keywords: Antifungal, aspergillosis, EBMT, invasive fungal infections, mortality, posaconazole.
Graphical Abstract
Call for Papers in Thematic Issues
An Overview of Drugs for Multiple Targets and Variants of SARS-CoV-2 Through Artificial Intelligence, Machine Learning, Deep Learning, and Experimental Analysis
The emergence and rapid evolution of SARS-CoV-2 variants have posed significant challenges in the ongoing fight against the COVID-19 pandemic. The development of effective treatments for multiple viral targets and variants demands innovative approaches, including artificial intelligence (AI), machine learning (ML), and deep learning (DL) techniques. This special issue aims ...read more
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