SBIR-STTR Award

Direct to Phase II

Sepsis, a systemic inflammatory condition, occurs as a complication of infection and in severe cases may beassociated with acute and life-threatening organ dysfunction. In the US alone, sepsis claims ~270,000 lives eachyear among ~1.7 million patients diagnosed annually, and globally, sepsis-related mortality is estimated toaccount for 20% of total deaths. Although improvements in the treatment protocol for sepsis and timelyadministration of antibiotics have reduced mortality rates, not a single drug for sepsis has ever been successfullybrought to market, despite over 100 interventional trials, and it is treated today as 60 years ago: antibiotics andsupportive care. Sepsis is unusual in that a great deal of the immune response is actually adaptive (beneficial)vs. disease-causing (maladaptive), so reversing the inflammatory response can cause the infection to gounchecked. We believe that a treatment should reverse the maladaptive (organ-damaging) components of theimmune response, while keeping the adaptive (pathogen-fighting) components intact. We believe that to achieveimpactful progress, new approaches are required that harness immune sub-groups. In this project, we proposea precision medicine approach to subdivide sepsis patients into treatable subclasses or "endotypes"using a companion diagnostic test, HostDx-Endotypes. We anticipate that classifying sepsis patients into suchendotypes may allow us to identify improved treatment regimens, leading to the discovery of new targets orpathways for endotype-specific therapies and/or repurposing of available drugs.In Phase 1 work we already demonstrated proof-of-concept by identifying 3 sepsis endotypes (Inflammopathic,Adaptive, and Coagulopathic) and validated across multiple external data sets. We have shown that our HostDxEndotypes can stratify patients into novel, potentially treatable subgroups across 3 publications using severalretrospective cohorts, and two prospective cohorts. We have also demonstrated the clinical utility of thisparadigm with InSepTM, our robust classifier for acute infectious disease, based on our HostDx point of care testsystem platform.To bridge our proof-of-concept work to product development for HostDx-Endotypes, we will (Aim 1) employrigorous machine learning algorithms and processes to finalize and lock an optimal classifier; (Aim 2) apply aninnovative approach of drug repurposing to identify and rank-order endotype-specific drug candidates for clinicalstudies on sepsis treatment, and (Aim 3) translate the final mRNA panel to Inflammatix's qLAMP cartridge andplatform. At Phase II completion we will have produced the HostDx Endotypes research-ready cartridge, togetherwith a list of repurposed drugs for intended clinical trials, and will be ready to enter the formal productdevelopment phase; we will have initiated the FDA pre-submission. Ultimately, the goal of this product will be todefinitively link a patient sepsis endotype with a therapeutic intervention, to enable better therapy selectionand resource allocation.

Public Health Relevance Statement:
NARRATIVE Sepsis is a significant public health crisis, but despite over 100 interventional drug trials, effective sepsis treatments have proven elusive; emerging data suggests that this may be related to immune sub-groups of sepsis, wherein some components provide beneficial responses, while others are disease-causing. Inflammatix believes that to achieve impactful progress, new approaches are required that harness these immune sub- groups, and our proposed HostDx-Endotypes test offers a precision medicine approach that would subdivide sepsis patients into treatable subclasses or "endotypes". This point-of-care cartridge-based blood test will enable clinicians to make timely and precise determinations of sepsis endotype that would definitively link a patient sepsis endotype with a therapeutic intervention, to enable better therapy selection and resource allocation.

Project Terms:
Affect ; Antibiotics ; Antibiotic Agents ; Antibiotic Drugs ; Miscellaneous Antibiotic ; Biological Assay ; Assay ; Bioassay ; Biologic Assays ; Blood ; Blood Reticuloendothelial System ; Cell Line ; CellLine ; Strains Cell Lines ; cultured cell line ; Classification ; Systematics ; Clinical Research ; Clinical Study ; Clinical Trials ; Communicable Diseases ; Infectious Disease Pathway ; Infectious Diseases ; Infectious Disorder ; Complication ; Cessation of life ; Death ; Diagnosis ; Disease ; Disorder ; Pharmaceutical Preparations ; Drugs ; Medication ; Pharmaceutic Preparations ; drug/agent ; Face ; faces ; facial ; Future ; Genes ; Goals ; Blood Tests ; Hematologic Tests ; Hematological Tests ; Hematology Testing ; Heterogeneity ; Infection ; Libraries ; Methods ; mortality ; United States National Institutes of Health ; NIH ; National Institutes of Health ; Paper ; Patients ; Phenotype ; Prospective Studies ; Public Health ; Publications ; Scientific Publication ; Research ; Messenger RNA ; mRNA ; Safety ; Technology ; Testing ; Time ; Translating ; Translations ; Treatment Protocols ; Treatment Regimen ; Treatment Schedule ; Work ; Measures ; Cohort Analysis ; Cohort Analyses ; Diagnostic tests ; Resource Allocation ; Selection for Treatments ; therapy selection ; Data Set ; Dataset ; Custom ; base ; Organ ; improved ; Acute ; Clinical ; Phase ; Biological ; Series ; Link ; Training ; Failure ; Functional disorder ; Dysfunction ; Physiopathology ; pathophysiology ; Oncology ; Oncology Cancer ; Immunological response ; host response ; immune system response ; immunoresponse ; Immune response ; Therapeutic ; Inflammatory ; tool ; Supportive Therapy ; Supportive care ; machine learned ; Machine Learning ; Life ; fighting ; Immunes ; Immune ; Severities ; Clinic ; System ; success ; cohort ; Venipunctures ; Immunomodulation ; immune modulation ; immune regulation ; immunologic reactivity control ; immunomodulatory ; immunoregulatory ; immunoregulation ; novel ; Devices ; drug action ; intervention therapy ; Therapeutic Intervention ; Interventional trial ; Intervention Trial ; Modeling ; Sampling ; response ; Intervention Strategies ; interventional strategy ; Intervention ; Inflammatory Response ; Data ; Molecular Marker of Prognosis ; Prognosis Marker ; prognostic biomarker ; prognostic indicator ; Prognostic Marker ; Reproducibility ; Subgroup ; Update ; Validation ; Characteristics ; Molecular ; Process ; Development ; developmental ; point of care ; Pathway interactions ; pathway ; Gene Expression Profile ; Expression Signature ; gene expression pattern ; gene expression signature ; transcriptional profile ; transcriptional signature ; design ; designing ; Sepsis ; blood infection ; bloodstream infection ; novel strategies ; new approaches ; novel approaches ; novel strategy ; Outcome ; pathogen ; innovation ; innovate ; innovative ; transcriptomics ; Network-based ; novel diagnostics ; new diagnostics ; next generation diagnostics ; product development ; drug candidate ; Drug Targeting ; precision medicine ; precision-based medicine ; clinically actionable ; companion diagnostics ; diagnostic biomarker ; diagnostic marker ; genetic signature ; gene signatures ; patient stratification ; stratified patient ; Prospective cohort ; Retrospective cohort ; septic patients ; sepsis patients ; machine learning algorithm ; machine learned algorithm ; learning classifier ; Phase I/II Clinical Trial ; Phase 1/2 Clinical Trial ; Rapid diagnostics ; drug repurposing ; repurposing agent ; repurposing medication ; rapid test ; rapid assay ; rapid tests ; biomarker signature ; point of care testing ;