An automated platform for direct-from-specimen identification of pathogens common in endocarditis

PROJECT SUMMARY Infective Endocarditis (IE) is a life-threatening disease that affects roughly 45,000 Americans annually. IE is characterized by microbial vegetations on the endocardial surface which induce serious heart damage and persistent bloodstream infections (BSIs) leading to sepsis. Left untreated IE is fatal. Among the criteria to establish IE and treat patients most effectively, blood cultures are indispensable to identify the etiologic agent. Cultures, however, display two major weaknesses which delay the administration of the proper antimicrobials: (1) High turnaround time of days or even weeks and (2) high prevalence of false-negative results due to either pre-treatment with antibiotics or the presence of difficult to culture pathogens. As time is of essence for optimal outcomes with minimal complications, treatment is often initiated prior to diagnosis with a cocktail of broad spectrum (i.e. not targeted) antimicrobials, leaving the majority of patients treated inappropriately and those without the disease treated unnecessarily. It is therefore critical to advance innovative diagnostic approaches, which do not rely on culturing, in order to rapidly transition to personalized antimicrobial interventions. To address this unmet need, HelixBind will develop the first culture-free diagnostic assay capable of identifying pathogens which induce IE in under 2 hours. Our approach is particularly suited to the detection of fastidious pathogens and unculturable pathogens associated with IE, which today’s diagnostic standard frequently fail to detect. HelixBind’s RaPID (Resistance and Pathogen Identification) diagnostic platform leverages multiple novel innovations from sample-to-answer to accurately characterize infections directly from specimen. Having met our and exceeded our Phase I Specific Aims, in this Phase II proposal we will focus on development of a fully- automated test, RaPID/IE, enabling the ‘hands-free’ identification of the most clinically prevalent pathogens and resistance genes associated with IE directly from phlebotomy specimens. RaPID/IE is expected to have a profound clinical impact by enabling the physician to apply a personalized and evidence-driven intervention within a few hours, rather than days; ultimately improving both outcomes and antimicrobial stewardship. In order to succeed in this endeavor, we have assembled a team of experts in the development of automated diagnostics supported by world-class advisors with expertise in pathology, infectious diseases, and clinical microbiology. Together, we will build upon our successful Phase I and deliver an automated assay, dedicated to IE, culminating in a blinded study in collaboration with our clinical partners. Having achieved our Specific Aims, we will begin verification and validation efforts under an ISO 13485 Quality System, scale manufacturing, and complete clinical trials for regulatory clearance.PROJECT NARRATIVE Infective Endocarditis (IE) is a serious and life-threatening disease and a significant economic burden due to prolonged intensive treatment. Early microbiological diagnosis is crucial to improving outcomes, but current standards employing blood cultures are lethargic and often yield false-negative results. This delay in crucial information prevents the administration of the evidence-based antimicrobial treatment precisely when it is maximally beneficial. HelixBind will address this problem and develop a novel turn-key approach for early microbiological IE-diagnosis. In this Phase II SBIR, we propose to further our Phase I feasibility work and develop the first fully-automated diagnostic capable of identifying the most prevalent pathogens causing IE, including those difficult or impossible to detect by standard methods, directly from phlebotomy specimens, without prior enrichment, reducing the diagnosis time from days or even weeks to just hours. The information provided would enable the clinician to apply an evidence-driven intervention from the onset of disease symptoms.