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Technology Innovation Spotlight - Reading Disease Signals from the Gut: An East Carolina University platform for fecal protein bioprofiling in inflammatory and neurological disorders

May 23, 2026 Susan Van Vactor

Methods and compositions for identifying fecal protein bioprofiles and treating inflammatory and neurological disorders

Technology Transfer Spotlight is a new MedSurgPI (MSPI) feature designed to translate academic innovation into clear industry opportunity. This first spotlight highlights an East Carolina University (ECU) invention published as WO2025155794A1, focused on subject-specific fecal protein bioprofiles, risk assessment, longitudinal monitoring, and kit-enabled use across inflammatory, neurological, neurodegenerative, and aging-associated disorders.

THE OPPORTUNITY: Inflammatory, neurological, and aging-associated disorders are biologically complex and often recognized only after meaningful disease progression. Developers and clinicians need biomarker approaches that are non-invasive, repeatable, and capable of capturing more than a single signal. ECU’s published application is directed at that gap by using stool as an accessible matrix for disease-related host-protein analysis.

THE INNOVATION: The invention establishes a subject-specific fecal protein bioprofile by extracting proteins from fecal material, determining relative abundance, grouping proteins by biological pathway, and generating a unique profile. The published application further describes using protein pathway enrichment scores to assess risk for inflammatory, neurological, neurodegenerative, and aging-associated disorders, and to monitor disease progression over time. The abstract also expressly includes kits for carrying out the method.

WHY IT MATTERS: First, it is non-invasive and well suited to serial sampling. Stool collection is better suited to repeated monitoring than many conventional approaches, which makes it attractive for patient-friendly screening and follow-up. Second, the signal is pathway-based rather than single-analyte based, creating room for broader biological interpretation, including immune activity, gut inflammation, and host-response patterns that may not be apparent from a single marker. Third, the same platform framework is positioned across inflammatory disorders, neurological disease, neurodegeneration, and aging-associated conditions an unusually broad span for one early translational asset.

TECHNOLOGY TRANSFER PERSPECTIVE: The intellectual property links sample collection, host-protein profiling, scoring logic, monitoring, and kitenabled deployment in one framework. That creates multiple partnering angles, including diagnostics, clinical biomarker strategy, proteomics service models, and remote disease-monitoring workflows. Those commercial pathways are an inference from the profiling, kit, and dashboard concepts described in the published application.

STRATEGIC INSIGHT: Many biomarker programs solve only for signal generation. This ECU asset addresses how a real-world workflow could function: collect the sample, isolate the relevant signal, interpret the biology, and potentially report changes over time through a usable platform. That combination supports positioning as a scalable translational platform rather than only a discovery-stage assay.

CALL TO ACTION: For additional information or partnership discussions, contact the ECU Office of Licensing & Commercialization. ECU contact Carlyle Rogers, Director of Licensing and Commercialization, innovation@ecu.edu.

PRACTICAL POINTER: The platform value of an academic invention increases when the IP covers not just the biomarker signal, but also the collection method, scoring framework, and deployment model.

Technology Snapshot

Institution: East Carolina University

IP Asset: WO2025155794A1 | WIPO (PCT) PCT/US2025/011987

Status/Dates: Published Jul 24, 2025 | Priority Jan 17, 2024 | Filed Jan 17, 2025

Inventors: Tonya Nicole Zeczycki, Stefan Clemens, Whitney Gabrielle Bond

Modality: Stool-based host-protein bioprofiling

Use Cases: Risk assessment, monitoring, kit-enabled testing

Classification: Go1N33/68

Partner Fit: Diagnostics, proteomics, digital health, CRO / biomarker partners

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