Can AI beat antibiotic resistance? Inside the future of drug discovery

Antibiotic resistance is one of the most urgent challenges in global healthcare, driving the need for faster, more effective approaches to drug discovery.
As innovation accelerates, organizations are also looking for ways to communicate their role in tackling this challenge to highly engaged scientific audiences.
A recent Nature Technology Feature on Antibiotic Discovery/AI explores how artificial intelligence is transforming antibiotic discovery, helping researchers identify promising new compounds and rethink traditional development pathways.
Science has come a long way since Alexander Fleming discovered penicillin on a contaminated Petri dish.
For one thing, there are many more classes of antibiotics for doctors to choose from — and thanks to their overuse, plentiful pathogens that are immune to them. But the arms race between bacteria and biopharma continues and on the biopharma side, artificial intelligence is playing an ever-larger role.
Nature Technology Features provide a trusted editorial platform where complex scientific advances are explored in depth, reaching a global audience of researchers, clinicians and decision-makers.
They also offer organizations an opportunity to align their research with high-impact scientific storytelling, building visibility and credibility in a highly relevant context.
Read the full article to explore how AI is accelerating antibiotic discovery →
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About Nature Technology Features:
Nature Technology Features are special features published in Nature spotlighting scientists and the technologies they choose. Organizations are invited to collaborate and advertise their technologies alongside the Nature features.
Each feature provides essential insights that can be readily implemented in laboratories around the world, making it the perfect platform for your brand to shine.
This year’s topics include:
Technologies to Watch, PhD survey/AI, Self-driving labs, MPRAs, Antibiotic Discovery /AI, Virtual cells/systems biology/PhysiCell (Fertig), Epigenome editing (ie, CRISPR and variants), Quantum Computing in Biology, What Can’t We Do With Genome Editors?,
Cell-free protein expression.