The Age of AI: Evolution of Rapid diagnostics in Hospital Acquired Infection Control
When infection prevention measures fall short or when immune compromised patients undergo invasive procedures and acquire a HAI, rapid detection is the only tool to actualize positive patient outcomes at any healthcare setting.
Rapid detection help clinicians drive early interventions regarding drug de-escalation, appropriate dosing strategies, avoid the risk of organ toxicity, contain resistant infection outbreaks. These reflect just a few of the acute needs around diagnosing hospital acquired infections, and rightly command the very latest in AST technologies to service that need. Traditionally that AST technology has been rooted in time consuming growth-based assays (48-72 hrs) but current platforms have tried to short change the
process around this basic premise using automation around sample processing, high throughput micro assays(24-36hrs+). While this class of AST device has been adopted by commercial diagnostics labs that thrive on transported patient sample volumes, the average healthcare facility with ICU patients battling HAIs is still losing time while they wait on test results to determine appropriate and effective interventions. Novel approaches to speed up the turn around time for AST test reports have been pursued by various research groups around the world using diverse platforms. one among them, seeking a 2 hr AST report led to the genesis of cAST.Ai.
Fundamentally cAST.Ai is based on teasing out the effect of antibiotics on the dynamics of bacterial nano motion and metabolism. Leveraging the advances in image processing and computer vision we are developing a phenotypic AST product designed to meet the urgent need for rapid diagnosis of resistant HAIs. In our current journey to bring the product to the point of care, we have become privy to the challenges of integrating multiple technologies in a lean fashion for an effective assay. Our assay also addresses the unique challenge of diagnosing heteroresistance (HR) in populations, HR is a minor subpopulation cell resistance feature that cannot be identified using current methods. Our algorithms are also designed on customized and curated data sets of individual urgent threat organism-antibiotic combinations to further decrease the time to results for such specific HAI infections. This will be particularly useful in hospitals at specific geographies where the burden of those infections is disproportionately high. Rapid diagnosis of such infections can initiate targeted antibiotic therapy, stop the spread of resistance in the community and prolong the life of last line antibiotics thorough informed prescription practices.
As the world’s population rises, rapid antibiotic susceptibility testing is set to be the ubiquitous future of managing and overcoming the burden of antibiotic resistance in every corner of the world.
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