Bloodstream infections caused by bacteria are a leading cause of death in the US and accounts for almost 50% of all hospital deaths. Given that this disease accounts for 25% of all ICU usage, it is not only fatal but it is by far the costliest disease to the American healthcare system, inducing an economic burden of $30B annually. Considering the rate at which the disease develops, early and targeted antibiotic treatment is the most crucial factor for improving patient outcome. The reality of the current situation, however, is troublesome: while proper treatment options are readily available, targeted antibiotic therapy is seldom administered early enough in the disease's time course to be of maximal benefit due to a lack of timely information. This is largely due to current diagnostic standards which require multiple time-consuming culturing steps, ultimately leading to a diagnostic delay as long as 2-5 days. As a consequence, physicians often resort to empirically designed broad-spectrum antibiotic 'cocktails' which are cost-intensive, less effective, increase complications, and significantly increase the prevalence of drug resistant pathogens. We have developed and validated with clinical specimens a Pathogen Identification (PID) assay that allows species-level identification of >90% of bacteremia-inducing pathogens directly from blood, thus removing the culturing barrier. Our PID assay employs a unique sample-preparation methodology combined with the innovative use of a synthetic nucleic acid analogue with unmatched kinetics and target detection capabilities. This application focuses on the automation of the entire workflow into a fully-integrated, sample-to-answer consumable enabling the completely automated identification of pathogens directly from phlebotomy specimens, in under 2 hours. We anticipate that the PID system we propose will have a profound clinical impact, both by providing a means to develop a hypothesis driven first-line intervention days faster than currently possible and by reducing the excessive and unnecessary use of antimicrobials. In order to succeed in this endeavor, we have put together a top-notch team including experts in assay development, synthetic nucleic acid analogues, the design & implementation of sample-to-answer diagnostics, and biomedical instrumentation. Additionally, we have enlisted key strategic advisors in clinical microbiology, surface chemistry, and nucleic acid analogues as well as successful entrepreneurs experienced in the commercialization of diagnostic devices. Together, we will build upon our impressive initial results, and develop an automated and culture-free PID system culminating in a performance assessment study with clinical specimens in collaboration with Tufts Medical Center. 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

Bacteremia is one of the leading causes of death with over 200,000 mortalities in the US every year. It is widely accepted that the key to better treatment is rapid and accurate diagnosis which would enable targeted therapy. The current 'gold standard' requires up to 5 days and is too slow to meet clinical requirements. HelixBind has developed a new turn-key approach for the detection of bacteremia inducing pathogens. In this Phase II, we propose to develop the first fully-integrated, sample-to-answer diagnostic capable of identifying the most prevalent pathogens directly from phlebotomy samples. The information provided would enable the clinician to apply a more targeted, and hence more effective, first-line treatment from the onset of symptoms.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
5R44AI124726-02
Application #
9307692
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ritchie, Alec
Project Start
2016-07-01
Project End
2019-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
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