Amer Soc Microbiology

ASM Microbe 2024: AI could speed antibiotic selection for sepsis

June 28, 2024

The current diagnostic standard for life-threatening sepsis infection relies on culture growth, which typically takes 2 to 3 days, yet mortality risk increases up to 8% every hour without effective treatment.

In a study presented at ASM Microbe, the American Society for Microbiology's annual meeting held June 13-27 in Atlanta, GA, a team from Day Zero Diagnostics unveiled a novel approach to antimicrobial susceptibility testing using artificial intelligence. The system, Keynome gAST, or genomic Antimicrobial Susceptibility Test, bypasses the need for culture growth by analyzing bacterial whole genomes extracted directly from patient blood samples.

“The result is a first-of-its-kind demonstration of comprehensive and high-accuracy antimicrobial susceptibility and resistance predictions on direct-from-blood clinical samples,” said Jason Wittenbach, Ph.D., Director of Data Science at Day Zero Diagnostics and lead author on the study. “This represents a critical demonstration of the feasibility of rapid machine learning-based diagnostics for antimicrobial resistance that could revolutionize treatment, reduce hospital stays and save lives.”

• Interim findings are based on studies that collected blood samples from patients suspected of bacteremia at four Boston-area hospitals between July 2023 and March 2024.
• Unlike traditional methods that rely on known resistance genes, the machine learning algorithms autonomously identify drivers of resistance and susceptibility based on data from a continuously growing large-scale database of more than 75,000 bacterial genomes and 800,000 susceptibility test results (48,000 bacterial genomes and 450,000 susceptibility test results at the time of this study). This allows for rapid and accurate predictions of antimicrobial resistance, revolutionizing sepsis diagnosis and treatment.
• Researchers say that further study is needed, given the limited sample size, but the findings could contribute to significant advancements in patient outcomes amid rising antimicrobial resistance and the need for rapid diagnosis and treatment of sepsis.

Source:

(2024, June 14). American Society for Microbiology. AI Enables Faster, More Effective Antiobiotic Treatment of Sepsis. https://asm.org/press-releases/2024/june/ai-enables-faster,-more-effective-antibiotic-treat