Antimicrobial resistance (AMR) is a growing global threat that undermines the effectiveness of existing therapies and demands new approaches to antibiotic discovery. The application of computational science and artificial intelligence (AI) to antibiotic discovery and development has opened unprecedented opportunities to combat AMR.  

This Keystone Symposia conference on Progress in Antibiotic Discovery and Development will spotlight innovative strategies that integrate microbiology, chemical biology, and computational biology, including antibiotic design, pathogen surveillance, and predictive modeling for resistance. Attendees will gain insights into emerging tools and strategies for addressing AMR and accelerating antimicrobial drug development. 

The conference will bring together diverse expertise, including microbiologists, bioengineers, computational biologists, synthetic biologists, and immunologists, to share the latest advances developed to address this urgent health challenge. To further promote cross-disciplinary interaction, this meeting is co-located with the Keystone Symposia Conference on Cell Biology and Metabolism Dynamics of the Host-Pathogen Interaction.

The rapid evolution of machine learning techniques, coupled with greater computational power and more extensive biological datasets, makes this the ideal moment to convene experts and discuss AI-based solutions. These recent innovations in algorithm development, data analytics, and computational biology have the potential to accelerate and transform how new treatments are identified, tested, and brought to market. The emphasis on integrating AI-enabled discovery with experimental validation distinguishes this meeting as a forward-looking forum for antibiotic development.