Emerging therapies against infections due to free-living amoebae.

Authors

Ruqaiyyah Siddiqui, Sutherland K Maciver, David Lloyd, Naveed Ahmed Khan

Published in

Expert review of anti-infective therapy. Aug 14, 2026. Epub Aug 14, 2026.

Abstract

Pathogenic free-living amoebae, including Naegleria fowleri, Acanthamoeba spp. and Balamuthia mandrillaris, are rare but frequently fatal opportunistic pathogens associated with severe central nervous system and ocular infections, and cutaneous infections. Despite advances in understanding their biology and pathogenesis, therapeutic options remain limited, mortality rates remain high, and delayed diagnosis continues to compromise clinical outcomes and public health responses.
Recent literature, with emphasis on studies published during the past decade, was reviewed using PubMed and Google Scholar, focusing on therapeutic advances against pathogenic free-living amoebae, including novel antiamoebic compounds, drug repurposing, nanotechnology-enabled delivery systems, and emerging diagnostic approaches. Recent progress in high-throughput screening, artificial intelligence-assisted drug discovery, and predictive therapeutic modeling is highlighted. The impact of climate change and environmental adaptation on the expanding geographic distribution of amoebic infections is also discussed.
Improved outcomes in free-living amoebic infections depend on early diagnosis, rapid therapeutic intervention, and improved understanding of host-pathogen interactions and pharmacokinetic barriers limiting effective drug delivery to the central nervous system. Given the rarity of these infections and the limited clinical datasets available, artificial intelligence-assisted approaches may become particularly important for accelerating antiamoebic drug discovery, therapeutic prediction, and precision treatment strategies. Emerging advances in nanotechnology-enabled drug delivery systems, theranostics, and computational therapeutic modeling may provide promising opportunities to improve management of these devastating infections.

PMID:
42601790
Bibliographic data and abstract were imported from PubMed on 15 Aug 2026.

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