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AI speeds up search for new potential antibiotic candidates

New machine learning technique could revolutionize fight against superbugs


Key points from article :

AI to find potentially millions of new antibiotics in the global microbiome.

This is significant because finding antibiotics traditionally is slow and difficult.

Antibiotic resistance is an increasing concern as it causes millions of deaths every year.

Researchers looked for DNA snippets with antimicrobial activity from genomes and meta-genomes stored in public databases.

They were able to synthesize and test 100 molecules, 79% of which could kill bacteria.

Study data and code are available for anyone to use for further research.

This study successfully combined AI and human expertise to make a breakthrough.

Experts noted that AI is a great tool for scientific research but shouldn’t replace human thinking.

Research led by César de la Fuente from University of Pennsylvania, published in the journal Cell.

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Scientific journal publishing research from many disciplines within the life sciences

César de la Fuente

Professor at the University of Pennsylvania

University of Pennsylvania

Private Ivy League research university in Philadelphia, Pennsylvania.

Topics mentioned on this page:
Antibiotic Resistance, AI Drug Discovery
AI speeds up search for new potential antibiotic candidates