Neonatal septicemia is a life-threatening disease that affects roughly 2 out of every 1,000 live births in the US, where 25-30% do not survive. Caused by an infection of the newborn bloodstream either at the time of birth or soon after, the disease?s initial clinical manifestations are often non-specific, variable, at times subtle, and often common to signs of stress. Thus a core requirement to both to rule-in a bloodstream infection (BSI) and to rule- out a BSI is microbiological evidence; which is currently only possible through blood-cultures. Cultures, however, display two major weaknesses which, crucial to outcome, delay the administration of the proper antimicrobials: (1) Long turnaround time of days and (2) high prevalence of false-negative results due to maternal antibiotics and a reduced input blood volume. As time is of essence for optimal outcomes, treatment is generally initiated prior to microbial diagnosis with a cocktail of broad spectrum (i.e. not personalized) 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 facilitate a transition to an evidence-based decision making process as soon as feasible. Having met our and exceeded our Phase I Specific Aims, this Phase II proposal focuses on development of a fully-automated neonatal pathogen identification (Neo/PID) platform enabling the ?hands-free? identification of the most clinically prevalent pathogens directly from phlebotomy specimens, in roughly 2 hours, without the need to culture. The Phase II proposed diagnostic device is expected to have profound impact, both by improving outcomes by providing a means to develop an evidence driven first-line intervention, and likewise by reducing the use of excessive and unnecessary antimicrobials. In order to succeed in this endeavor, we have assembled a top-notch team including experts in assay development, artificial nucleic acids, and the implementation of automated diagnostics. Additionally, we have enlisted key advisors in clinical microbiology, surface chemistry, and pathology as well as successful entrepreneurs experienced in the commercialization of diagnostic devices. Together, we will build upon our impressive Phase I results and develop an automated platform, dedicated to neonatal BSIs, culminating in a performance assessment study with clinical specimens. Having achieved our Specific Aims, we will develop deployable instrumentation/consumables and validate our diagnostic in preparation for the pivotal clinical trial.

Public Health Relevance

Neonatal sepsis, induced by a microbial infection of the bloodstream, is a serious and life-threatening disease with high levels of morbidity and mortality. Rapid microbiological analysis is crucial to improving outcomes, but current standards rely on blood cultures, and as such are lethargic and often yield false-negative results. This delay in providing essential information prevents the administration of the evidence-based antimicrobial treatment precisely when it is maximally beneficial. HelixBind will address this problem and will develop a novel turn-key approach for early microbiological identification of newborns with bloodstream infections. In this Phase II SBIR, we build upon our highly convincing Phase I results and will develop the first fully- automated diagnostic capable of identifying the most prevalent pathogens causing inducing neonatal septicemia. This diagnostic device will operate directly from phlebotomy specimens, without prior enrichment, reducing the diagnosis time from days to just hours. The information provided would enable the clinician to apply an evidence-driven intervention from the onset of disease symptoms.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
2R44HD083971-02
Application #
9340504
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Raju, Tonse N
Project Start
2015-09-18
Project End
2019-08-31
Budget Start
2017-09-01
Budget End
2018-08-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Helixbind, Inc.
Department
Type
DUNS #
078680117
City
Marlborough
State
MA
Country
United States
Zip Code
01752