Diagnostic For Predicting Hospital-Acquired Infections And Identifying Causative Organisms

SUMMARY

The technology is a fecal microbiome metabolite profile that can predict hospital-acquired infections and identify the causative organisms. This method efficiently measures specific chemical metabolites produced by bacteria in the stool microbiome. It provides actionable information for clinicians, guiding antibiotic treatment and identifying patients who might benefit from microbiome therapies, thus improving infection management and addressing drug-resistant infections.

Unmet Need: Accurate, non-invasive diagnostic for predicting hospital-acquired infections

• Hospital-acquired infections (HAIs) present a significant challenge in healthcare settings, contributing to increased morbidity, prolonged hospital stays, and higher healthcare costs. Traditional diagnostic methods, such as bacterial cultures and genomic sequencing, are often slow and expensive, limiting their utility in timely clinical decision-making. There is a pressing need for faster, cost-effective diagnostic tools that can predict HAIs and guide appropriate treatment strategies, especially in an era of rising antibiotic resistance.

• Current approaches to predicting and diagnosing HAIs suffer from several limitations. Advanced genomic sequencing, while highly accurate, is both time-consuming and costly, making it impractical for routine clinical use. Bacterial cultures, another common method, can take several days to yield results, delaying critical treatment decisions. These methods also fail to provide a comprehensive picture of the microbial ecosystem, focusing only on the presence or absence of specific pathogens rather than their relative abundance and interactions within the microbiome. This lack of broader microbial context hampers the ability to predict which patients are at higher risk for HAIs and to tailor antibiotic therapies effectively. Moreover, existing technologies do not account for the dynamic nature of the microbiome, where shifts in microbial populations can precede the onset of infection, further limiting their predictive power.

The proposed solution: Simple method for predicting risk of hospital-acquired infections by fecal microbiome metabolite profiling

• The faculty inventor identified a fecal microbiome metabolite profile which may be used to predict whether a patient is at increased risk of developing a HAI and also the likely organism that will cause the HAI. This critically important information will guide clinicians on whether to start antibiotic treatment and which specific antibiotic would be most effective.

• Additionally, the metabolite profile is likely to identify patients who have abnormal microbiomes and who are likely to benefit from a microbiome therapy. While these microbiome therapies are currently under investigation, it is likely they will be developed in the coming years. As these therapies develop, a microbiome/metabolome profile tool could be used to identify patients that are most likely to benefit from the microbiome therapy.

ADVANTAGES

ADVANTAGES

• Predicts the relative abundance of organisms and provides broader microbial context

• Faster and more cost-effective actionable information for clinicians

• Guides antibiotic treatment and selection

• Addresses the challenge of drug-resistant infections

APPLICATIONS

• Clinical diagnostics
• Infection management
• Microbiome-based therapeutics
• Research tools

PUBLICATIONS

• Christopher J. Lehmann, Nicholas P. Dylla, Matthew Odenwald, Ravi Nayak, Maryam Khalid, Jaye Boissiere, Jackelyn Cantoral, Emerald Adler, Matthew R. Stutz, Mark Dela Cruz, Angelica Moran, Huaiying Lin, Ramanujam Ramaswamy, Anitha Sundararajan, Ashley M. Sidebottom, Jessica Little, Eric G. Pamer, Andrew Aronsohn, John Fung, Talia B. Baker, Aalok Kacha,Fecal metabolite profiling identifies liver transplant recipients at risk for postoperative infection, Cell Host & Microbe, Volume 32, Issue 1, 2024, Pages 117-130.e4, ISSN 1931-3128, https://doi.org/10.1016/j.chom.2023.11.016.

July 19, 2024

Proof of concept

Patent Pending

Licensing,Co-development

Eric Pamer