BACKGROUND:

Communities and infrastructure owners currently lack effective tools to estimate wildfire spread and resulting damage at the community scale, particularly within the wildland-urban interface (WUI). Existing wildfire models often focus on large-scale fire behavior or wildland environments andD do not adequately capture fire propagation through built environments. This limitation constrains the ability of planners, utilities, and emergency responders to conduct proactive mitigation, scenario planning, and real-time decision-making. There is a critical need for modeling tools that can simulate wildfire behavior within communities to better inform risk assessment and resilience strategies.

TECHNOLOGY OVERVIEW:

This University at Buffalo technology introduces SWUIFT, a simulation-based wildfire spread modeling tool designed to capture fire propagation within communities. The model represents both urban fuels (e.g., buildings and infrastructure) and vegetation within a unified computational framework, enabling estimation of fire arrival times, spread dynamics, and potential damage. SWUIFT incorporates efficient computational methods and accounts for uncertainties in environmental and structural conditions, allowing for robust scenario-based analysis. The platform supports detailed modeling of fire behavior as it transitions from wildland areas into densely built environments, providing actionable insights for community-level wildfire risk assessment.

https://buffalo.technologypublisher.com/files/sites/7768_in-part_image.jpg

SE Viera Photo, https://stock.adobe.com/uk/images/359013282, stock.adobe.com

ADVANTAGES:

This technology provides one of the first explicit simulation frameworks for modeling wildfire spread within communities, addressing a key gap in existing wildfire modeling approaches. By integrating both urban and wildland fuels, it offers a more realistic representation of fire behavior in the wildland-urban interface. The model demonstrates efficient computational performance, enabling practical use in planning and decision-support contexts. It also incorporates uncertainty analysis, allowing users to evaluate a range of possible fire scenarios and outcomes, improving risk-informed decision-making.

APPLICATIONS:

This technology can be applied in decision-support software for utilities, municipalities, and emergency management agencies to support wildfire risk assessment, mitigation planning, and emergency preparedness. It is suitable for scenario-based planning tools, infrastructure resilience analysis, and post-fire damage assessment. The platform can also be integrated into broader geospatial and climate risk modeling systems, as well as used in research and policy development related to wildfire management and community resilience.

INTELLECTUAL PROPERTY SUMMARY:

Provisional patent application 63/965,917 filed January 22, 2026.

STAGE OF DEVELOPMENT:

Technology Readiness Level 8 (TRL 8)

LICENSING STATUS:

Available for licensing or collaboration

ADDITIONAL INFORMATION:

• Irina Balyasnikova*
  • Northwestern University Feinberg School of Medicine, Department of Neurological Surgery
• Joseph Duffy

• Improved immunotherapy for glioblastoma: Enhances patient response to targeted T-cell therapy.
• Gene-targeted therapy: Facilitates combination approaches with MAPK inhibitors.
• Personalized treatment strategies: Enables tailored interventions based on tumor gene expression.

• Enhances immunotherapy response: Boosts T-cell efficacy by modulating MAPK pathway activity.
• Overcomes tumor resistance: Disrupts a key component in GBM resistance mechanisms.
• Enables combinatorial treatment: Compatible with existing immunotherapeutic and targeted regimens.
• Validated approach: Demonstrated proof-of-concept with CRISPR knockout experiments.

PUBLICATIONS

IP STATUS
US Patent Pending (18/776,064)

CATEGORY/INDUSTRY PIPELINE
Therapeutics; Biomarkers & Biomedical Research Tools

KEYWORDS
GBM, Immunotherapy, SEC61 complex, MAPK, T-cell therapy, glioblastoma, cancer, oncology, resistance

• Irina Balyasnikova (Feinberg School of Medicine, Department of Neurological Surgery)*
• Isabelle Le Poole (Feinberg School of Medicine, Department of Dermatology)*

SHORT DESCRIPTION
A bispecific T cell engager that targets CD3+ T cells and TYRP1-expressing melanoma cells.

BACKGROUND
Melanoma is the deadliest form of skin cancer with an estimated 105,000 new cases and around 8,430 deaths expected in the United States in 2025. It is a UV-promoted form of skin cancer that readily metastasizes, and in patients in which metastasis has occurred, the survival rate is only 65% when the disease has spread to lymph nodes and 25% when distant spread has occurred. Current treatments for melanoma face high costs, poor specificity, limited effectiveness, and significant side effects; therefore, there is a clear unmet need for improved methods to target melanoma while minimizing adverse side effects.  Melanoma is commonly infiltrated by T cells, a phenomenon known as a “hot tumor" which refers to cancer that has already triggered a strong immune response, has been infiltrated by immune cells like T cells, and is likely to respond well to immunotherapy. Bispecific T cell engagers (BiTEs) are a new type of immunotherapy which, when a tumor-specific cell surface antigen can be identified, can brings a patient's T-cells close to the cancer cells and activate the T-cells to kill the cancer. Tyrosinase-related protein 1 (TYRP1) is the most abundant protein expressed by melanocytic cells, and in melanoma tumor cells, the protein was recently shown to be partially trafficked to the cell surface. A novel therapeutic approach that exploits these characteristics of melanoma could address this unmet need and significantly improve clinical outcomes for patients.

ABSTRACT
Northwestern researchers have developed a BiTE designed to target CD3ε expressed on the surface of T cells and TYRP1 expressed on the surface of melanoma cells. This innovative approach has been shown to trigger potent cytotoxic responses against melanoma cells with minimal damage to healthy tissues in vitro and in vivo evaluation in preclinical models have demonstrated its ability to mediate effective tumor cell killing. This therapeutic modality supports a simpler streamlined manufacturing process for an off-the-shelf product.

DEVELOPMENT STAGE
Early Preclinical - In Vivo PoC Data Available.

APPLICATIONS

• Immunotherapy for melanoma: Applicable to both cutaneous and metastatic melanoma, including brain metastases.

ADVANTAGES

• Improved specificity and safety: Minimizes potential side effects through targeted action.
• Overcomes immune evasion: Activates T cells independent of traditional activation pathways.
• Potent immune response: Induces strong cytotoxicity against melanoma cells, including bystander killing.
• Fast manufacturing: Simplifies production with an off-the-shelf format for rapid deployment.

PUBLICATIONS

IP STATUS
US patent pending (19/103,495).

CATEGORY/INDUSTRY PIPELINE
Therapeutics

KEYWORDS
Therapeutics, cancer, oncology, melanoma, immunotherapy, bispecific T cell engager, TYRP1, CD3, targeted therapy, off-the-shelf, biologic

Novel therapeutic strategy targeting Bergmann glia inflammation using JNK inhibition for treatment of spinocerebellar ataxia type 1 (SCA1) and other neurodegenerative disorders.

INVENTORS

• Puneet Opal*
  • Northwestern University Feinberg School of Medicine, Professor of Neurology
• Chandrakanth Edamakanti

NU Tech ID  NU 2021-060

IP STATUS

US Patent Issued (12,414,981)

DEVELOPMENT STAGE

TRL-3 Experimental Proof-of-Concept: Animal model studies reduced inflammation and improved motor function.

BACKGROUND

Spinocerebellar ataxia type 1 (SCA1) is a rare and debilitating adult‑onset neurodegenerative disorder that causes progressive cerebellar and brainstem dysfunction leading to progressive loss of motor coordination, severe disability, and premature death. Current treatment options are limited and focus mainly on symptom management and supportive approaches like physiotherapy and occupational and speech therapy. The high cost and low efficacy of available treatments highlight a critical need for novel therapeutic approaches that address underlying neuroinflammatory mechanisms.

ABSTRACT

Northwestern researchers have  developed a JNK inhibitor strategy to reduce neuroinflammation by targeting Bergmann glia in SCA1. Researchers observed a unique JNK-dependent c-Jun phosphorylation in Bergmann glia using human SCA autopsy samples. In an SCA1 mouse model, JNK inhibition decreased this inflammatory marker and led to significant improvements in both pathology and behavior. The results suggest that blocking the JNK pathway addresses a key contributor to neurodegeneration in SCA1 and potentially in other ataxic syndromes.

APPLICATIONS

• Therapeutic intervention for spinocerebellar ataxia: Offers a targeted treatment for SCA1 patients.
• Neuroinflammation reduction: Addresses inflammation in Bergmann glia across various neurodegenerative disorders.
• Preclinical research tool: Supports studies on JNK pathway modulation in animal models.
• Combination therapy potential: Can be paired with existing treatments to enhance clinical outcomes.

ADVANTAGES

• Targets a specific inflammatory pathway: Focuses on the JNK-dependent phosphorylation in Bergmann glia.
• Improves pathological and behavioral outcomes: Validated in an SCA1 mouse model.
• Fills an unmet clinical need: Provides a novel approach where current therapies are limited.
• Potential for broader application: May benefit other ataxic syndromes with similar neuroinflammatory profiles.

PUBLICATIONS

• Puneet Opal et al., Reactive Bergmann glia play a central role in spinocerebellar ataxia inflammation via the JNK pathway, J Neuroinflammation. May 26, 2023.

CATEGORY/INDUSTRY PIPELINE

Therapeutics

KEYWORDS

JNK inhibitor, neuroinflammation, spinocerebellar ataxia, SCA1, Bergmann glia, neurodegeneration, therapeutic, small molecule, neurodegenerative disease, CNS, rare disease

SHORT DESCRIPTION

Synthetic IL-23 receptors for cell engineering to enable real-time sensing and drive precise autoimmune and cancer immunotherapy interventions.

• Joshua Leonard*
  • McCormick School of Engineering, Department of Chemical and Biological Engineering
• Aaron Morris
• William Corcoran

NU 2024-093

IP STATUS

US Patent Pending (19/237,257)

DEVELOPMENT STAGE

TRL-3 Experimental Proof-of-Concept: In vitro demonstration validates the core function of synthetic IL-23 receptors.

BACKGROUND

Immune system dysfunction, particularly autoimmunity, affects millions worldwide. Interleukin 23 (IL-23) is an inflammatory cytokine secreted by activated immune cells that plays a key role in the development of inflammation, autoimmune disease, and the onset and progression of cancer. Several biologic drugs targeting IL-23 have been developed for treating autoimmune diseases including psoriasis and Crohn’s disease. Although effective, these drugs are systemic in nature, only target one element of the inflammatory cascade, and require frequent injection, thus resulting in limited efficacy and imposing a high burden on patients. Cell therapies are a promising alternative for durable treatment of autoimmunity given they can be longer acting, can target and infiltrate specific tissues, and can be genetically engineered to deliver therapeutic products in response to specific environmental cues. However, for these therapies to fulfill that promise, the development of new receptors for cell engineering capable of sensing soluble cues and relaying that detection through orthogonal mechanisms independent of native pathways to trigger specific therapeutic functions is needed.

ABSTRACT

Northwestern researchers have engineered synthetic receptors for interleukin-23 that convert natural soluble cytokine detection into a controlled, orthogonal signaling event. This technology converts human cytokine receptors into self-contained biosensors, preserving native ligand specificity while signaling through insulated, non-native pathways for safer, more programmable cell therapies. Its robust, modular architecture is tolerant to expression-level variability, supports multiplexed soluble-cue sensing and Boolean logic, and integrates cleanly with CARs and other effectors, thus reducing tuning burden and accelerating translation across cell types and delivery modalities. These receptors function in mammalian cells, demonstrate robust in vitro activity, and lay the groundwork for engineering tunable biosensors to program cellular responses in autoimmune and cancer immunotherapy applications.

APPLICATIONS

• Integration into CAR T cell therapies to enhance cell-based immunotherapies
• Programmable cell therapies to enable controlled therapeutic responses
• Biosensing to provides real-time monitoring of cytokine levels
• Research tool for cytokine signaling to facilitate studies on immune modulation

ADVANTAGES

• Enhances specificity by offering orthogonal signaling that minimizes crosstalk with native pathways
• Durable response for long-lasting cell therapy effects compared to transient drug delivery
• Flexible design with adaptable architecture for diverse cytokine targets and applications
• Scalable manufacturing and integration ease into existing cell therapy production pipelines

PUBLICATIONS

• Joshua Leonard et al., "Conversion of natural cytokine receptors into orthogonal synthetic biosensors", Nature, August 22, 2025
• Joshua Leonard et al., "Synthetic extracellular interleukin 23 biosensors", Northwestern Engineering News, August 22, 2025

CATEGORY/INDUSTRY PIPELINE

Biomarkers & Biomedical Research Tools; Therapeutics

KEYWORDS

synthetic receptor, IL-23, cytokine biosensor, cell therapy, autoimmunity, autoimmune disease, immunology, immunotherapy, orthogonal signaling, cell engineering, synthetic biology, targeted therapy, precision medicine

An engineered probiotic that senses intestinal inflammation via calprotectin and locally releases therapeutic antibodies in the gastrointestinal tract only during inflammatory flares.

• Arthur Prindle*
  • McCormick School of Engineering, Department of Chemical and Biological Engineering
• Jonathan Xia

NU 2023-131, NU 2024-047

IP STATUS

Multiple US Patents pending (18/775,012; 19/198,291)

DEVELOPMENT STAGE

TRL-5 Prototype Validated in Relevant Environment: Calprotectin sensor performance has been confirmed using a DSS-induced colitis murine model.

BACKGROUND

Inflammatory bowel disease (IBD), including Crohn’s disease and ulcerative colitis, is a chronic autoimmune condition marked by recurrent inflammation of the gastrointestinal (GI) tract, requiring long‑term management, which is associated with substantial morbidity, impaired quality of life, increased colorectal cancer risk, and significant healthcare costs. Globally, IBD affects an estimated 4.9 million people, with prevalence rising. While effective therapies exist, they are typically delivered systemically and can cause significant side effects due to prolonged immunosuppression. At the same time, disease monitoring relies on invasive or slow diagnostic methods, which can delay timely intervention during inflammatory flares. There is a critical need for therapeutic approaches that both detect intestinal inflammation noninvasively and deliver treatment locally, only when disease activity is present. 

ABSTRACT
Northwestern researchers have developed an engineered probiotic capable of detecting markers indicative of active inflammation in the GI tract and releasing therapeutic antibodies in response for treatment of IBD. This invention integrates synthetic biology with microbial diagnostics. E. Coli Nissle 1917 (EcN)—a probiotic with established safety in humans—was engineered to produce and selectively release therapeutic antibodies in the GI tract only in the presence of calprotectin, the clinical gold standard biomarker of IBD. In both in vitro settings and a DSS-induced murine colitis model, the probiotic showed high sensitivity and specificity to inflammation. The platform distinguished active IBD from remission by quantifying reporter signals that track with clinical calprotectin levels. For disease management, the engineered probiotic can subsequently release a therapeutic antibody, such as anti-TNF-α.  

APPLICATIONS

• IBD Disease Activity Monitoring: Enables noninvasive tracking of gut inflammation.
• Early Intervention Strategies: Supports timely identification of IBD flares to prevent complications.
• IDB Disease Management: Enables precise, inflammation‑responsive medication delivery within the gastrointestinal tract.

ADVANTAGES

• Noninvasive and rapid: Eliminates the need for colonoscopies while providing fast results.
• Highly sensitive and specific: Reduces systemic immunosuppression from IV infusions by enabling local, calprotectin-induced delivery of antibody therapeutics.
• Cost-effective: Reduces overall diagnostic expenses by streamlining monitoring processes.
• Real-time disease tracking: Supports immediate clinical decisions and proactive patient care.

PUBLICATIONS

• Xia, J. Y.; Hepler, C.; Tran, P.; Waldeck, N. J.; Bass, J.; Prindle, A. Engineered Calprotectin-Sensing Probiotics for IBD Surveillance in Humans Proceedings of the National Academy of Sciences, 2023

CATEGORY/INDUSTRY PIPELINE

Healthcare Devices, Tools & IT; Biomarkers & Biomedical Research Tools; Therapeutics

KEYWORDS

Inflammation, immunology, IBD, calprotectin, engineered probiotics, non-invasive monitoring, biosensor, synthetic biology, gut inflammation, diagnostics, autoimmunity, biologic, cell therapy, therapeutics

Background: 

Microwave ablation (MWA) has emerged as the preferred thermal ablation modality for treating non-surgical patients with primary and metastatic liver malignancies. The clinical success of thermal ablation depends critically on image guidance to ensure sufficient ablation margins while minimizing collateral thermal damage. Traditional image guidance, using modalities such as computed tomography (CT) and ultrasound, is constrained by limited soft tissue contrast and relies on surrogate markers of the ablation zone progression that do not reliably capture true ablation margins. These limitations reduce procedural precision and hinder real-time assessment of thermal dose delivery. Magnetic resonance imaging (MRI)-guided MWA addresses these shortcomings by providing superior soft tissue visualization and enabling real-time, non-invasive temperature monitoring through MR thermometry. This combination enhances targeting accuracy, intra-procedural monitoring, and treatment control, positioning MRI-guided MWA as a highly promising modality for minimally invasive tumor management. 

However, broader clinical adoption of MRI-guided MWA remains limited by electromagnetic interference (EMI) emitted from MWA systems during active operation. EMI contaminates MRI data, obscuring visualization of the microwave antenna, tissue structures, and ablation zone boundaries — increasing the risk of incomplete treatment or collateral thermal damage. Beyond MWA, EMI poses challenges whenever insufficiently shielded powered devices are introduced into the MRI scanner room, constraining the range of MRI-conditional tools and monitoring equipment that can be used during procedures. Existing EMI mitigation approaches rely on specialized hardware modifications (e.g., additional shielding layers or in-line filters) or require suspending energy delivery during image acquisition. These approaches increase system complexity, disrupt therapeutic protocols, and are impractical for routine clinical workflows. Therefore, there is a critical need for a streamlined solution that enables reliable EMI suppression and integrates seamlessly into clinical workflows for MRI-guided interventions.

Innovation: 

To overcome the limitations of existing EMI mitigation approaches, researchers at UCLA have developed a software-based active EMI suppression (AES) framework that restores MRI signal integrity without requiring specialized hardware modifications or workflow disruptions. The framework leverages an unloaded body array coil—an existing clinical MRI system component—to capture raw EMI signatures independently of primary imaging data. This architecture enables seamless integration into existing MRI infrastructure without interfering with image acquisition or procedural workflow. The system characterizes and models the EMI signal on a frame-by-frame basis and adaptively subtracts it from the primary imaging coil data, enabling dynamic, real-time EMI suppression during active microwave ablation.

In controlled testing environments, the technology achieved a 40-fold signal-to-noise ratio (SNR) improvement in phantoms and a 13-fold improvement in vivo, with an EMI suppression rate exceeding 92%. These gains restore image fidelity sufficiently to enable consistent intra-procedural MRI visualization of anatomical details and ablation zone boundaries. The AES framework also preserves thermometric accuracy, maintaining a mean absolute temperature error of <1.4 °C in heated regions and <0.3 °C in non-heated tissue. This level of accuracy supports thermal dose monitoring and helps protect surrounding healthy structures. By eliminating the need for specialized shielding hardware or procedural workarounds, this software-driven AES solution directly addresses key infrastructure and workflow barriers and could facilitate broader clinical adoption of MRI-guided MWA and other MRI-guided interventions affected by EMI. 

Potential Applications:

●    MRI-guided Thermal and Non-Thermal Ablation
     ○    MWA, radiofrequency ablation, laser interstitial thermal therapy, focused ultrasound, cryoablation, pulsed field ablation, histotripsy
●    MRI-Guided Surgical & Robotic Interventions
●    Interventional Oncology & Cardiology 
●    Neuromodulation & Brain Interventions 
●    High-Risk Anatomical Interventions (e.g., proximity to critical structures) 
●    Relaxed MRI Suite Shielding Requirements 
●    Expanded MRI-Conditional Device Integration (e.g., monitors, tools, implants) 
●    Point-of-Care & Low-Field MRI Environments

Advantages:

●    Streamlined Clinical Workflow
     ○    Continuous, real-time visualization
     ○    No pre-training or separate calibration needed
●    Seamless Hardware and Software Integration
     ○    Leverages standard, existing MRI receiver coils — no custom hardware
     ○    Software-only solution, readily integrable into vendor or open-source reconstruction pipelines
●    Superior Intra-procedural Image Quality Preservation
●    Enhanced Patient Safety During Interventional Procedures
●    Reliable Real-time MRI and MR Temperature Monitoring 

Development-To-Date:

First successful demonstration of the invention in controlled gel phantom and in vivo pig liver model

Related Papers:
●    Dai, Qing, et al. “Active Electromagnetic Interference Suppression for Real-Time MR Thermometry During MR-Guided Microwave Ablation.” Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2025, Honolulu, Hawai’i, USA, 0677.

Reference:

UCLA Case No. 2026-217

Lead Inventor:

Holden H. Wu
 

SHORT DESCRIPTION

A bispecific lipid nanoparticle that bridges tumor-associated myeloid cells (TAMCs) and glioma cells by dual checkpoint blockade and simultaneously reprograms TAMCs into antitumor effectors via targeted delivery of a STING agonist.

• Maciej Lesniak*
  • Northwestern University Feinberg School of Medicine, Department of Neurological Surgery
• Peng Zhang

NU 2022-151

IP STATUS

 US Patent filed (19/122,639).

DEVELOPMENT STAGE

TRL-5 Prototype Validated in Relevant Environment: Preclinical murine studies demonstrate significant antitumor efficacy when combined with radiotherapy.

BACKGROUND

Glioblastoma is the most common and highly aggressive primary malignant brain tumor, accounting for roughly half of all malignant brain tumors and about 12,000 new cases annually in the U.S. Standard-of-care remains maximal safe surgical resection followed by radiotherapy and temozolomide-based chemotherapy; however, with a 5‑year survival around 6–7% and median overall survival at about 12–18 months, glioblastoma remains the leading cause of brain tumor–related death and is responsible for the majority of deaths among primary brain tumor patients. Current glioblastoma treatments, including radiation therapy, often trigger immune resistance and promote tumor evasion through immune checkpoint upregulation, contributing to near-universal recurrence, and face challenges such as high treatment costs and limited efficacy, underscoring a critical need for new and more effective treatment strategies.

ABSTRACT

Northwestern scientists developed a bispecific lipid nanoparticle (B-LNP) that targets tumor-associated myeloid cells (TAMCs) and glioma cells via dual ligation of CD47 and PD-L1. The nanoparticle blocks these immune checkpoints and delivers a STING agonist (diABZI) to reprogram TAMCs into antitumor effectors. In preclinical murine models, the B-LNP, when combined with radiotherapy, increased phagocytosis and T cell activation leading to significant tumor regression.

APPLICATIONS

• Glioblastoma treatment: Enhances antitumor immune responses in brain tumors.
• Combination therapy with radiotherapy: Boosts radiation efficacy through immune reprogramming.
• Targeted immunotherapy: Delivers STING agonists directly to tumor-associated myeloid cells.
• Nanoparticle-mediated drug delivery: Improves precision and safety in immune checkpoint blockade.

ADVANTAGES

• Enhances immune cell phagocytosis: Blocks dual immune checkpoints for focused antitumor activity.
• Synergizes with radiotherapy: Amplifies tumor regression when used with standard treatments.
• Promotes durable responses: Reprograms myeloid cells to sustain long-term antitumor immunity.
• Precision delivery: Targets specific immune cells, reducing off-target effects and improving safety.

PUBLICATIONS

•   Maciej Lesniak et al., STING agonist-loaded, CD47/PD-L1-targeting nanoparticles potentiate antitumor immunity and radiotherapy for glioblastoma. Nature Communications. Mar 23, 2023.

CATEGORY/INDUSTRY PIPELINE

Healthcare Devices, Tools & IT; Therapeutics

KEYWORDS

Cancer, oncology, glioblastoma, brain cancer, bispecific lipid nanoparticles, immunotherapy, tumor-associated myeloid cells, STING agonist, immune checkpoint blockade, radiotherapy, nanoparticle, drug delivery, targeted therapy

SHORT DESCRIPTION

An annexin-based biological therapeutic that enhances the body's natural cell membrane repair process to reduce skeletal muscle, cardiac, and neuronal cell death and preserve tissue function.

INVENTORS

• Elizabeth McNally*
  • Feinberg School of Medicine, Department of Medicine (Cardiology Division)
• Alexis Demonbreun
  • Feinberg School of Medicine, Department of Pharmacology
• Robert Vassar
  • Feinberg School of Medicine, Department of Neurology
• Dominic Fullenkamp
• Katherine Sadleir

NU Tech ID:  NU 2018-119, 2022-008

IP STATUS

Multiple US Patents pending (17/416,018, 18/838,195) and several OUS Patents granted (3897689) and pending (CA, AU, CN, JP). 

DEVELOPMENT STAGE

TRL-3 - Experimental Proof-of-Concept Active R&D: Key functionalities have been validated in preclinical models.

BACKGROUND

Cell membrane integrity is critical for cell survival and function, and its disruption in excitable tissues such as muscle, cardiac, and neuronal cells, disturbs ionic homeostasis, signaling, and cell survival.  When repair mechanisms are impaired or defective, membrane disruption drives tissue loss and organ dysfunction and contributes to the development of various chronic conditions including Duchenne and Becker muscular dystrophies, ischemic injury, and membrane‑fragility cardiomyopathies, and neuropathies resulting from traumatic brain injury, spinal cord injury, and post‑cardiac arrest brain injury. Together, these conditions affect millions of people each year. Existing therapies focus on slowing disease progression and improving downstream consequences, but leave the initial membrane injury and defective repair largely unaddressed, and currently there are no broadly approved therapies aimed at enhancing of plasma membrane repair. The high cost and limited efficacy of current treatments demonstrate the need for improved membrane repair solutions

ABSTRACT

This technology developed by Northwestern researchers provides compositions and methods for treatment of cellular membrane injury. Annexins are essential for the calcium-dependent process of sealing membrane breaches. This invention entails administering a recombinant version of the annexin A6 protein to directly bolster the endogenous membrane repair machinery in cardiac, neuronal, and muscle tissues. Preclinical studies in animal models reveal that annexin A6 rapidly localizes at injury sites to form repair caps. The technology leverages both intracellular and extracellular mechanisms to enhance membrane resealing. These results support its potential to restore cellular integrity and function following injury.

APPLICATIONS

• Cardiac repair: Treatment following acute myocardial injury.
• Neurological repair: Management of traumatic brain and spinal cord injuries.
• Muscular dystrophy management: Enhancing membrane repair in chronic muscle disorders.
• Preventive therapy: Reducing cell damage in high-risk patients.

ADVANTAGES

• Accelerates membrane repair: Rapidly localizes to injury sites to reduce repair time.
• Reduces long-term tissue damage: Minimizes secondary cell loss post injury.
• Enhances recovery: Supports cell survival and functional recovery.
• Broad applicability: Serves both acute and chronic conditions across multiple tissues.

PUBLICATIONS

• Demonbreun AR, Bogdanovic E, Vaught LA, Reiser NL, Fallon KS, Long AM, Oosterbaan CC, Hadhazy M, Page PG, Joseph PRB, Cowen G, Telenson AM, Khatri A, Sadleir KR, Vassar R, McNally EM, A conserved annexin A6-mediated membrane repair mechanism in muscle, heart and nerve, JCI Insight, 2022 Jul 22.

CATEGORY/INDUSTRY PIPELINE

Therapeutics; Biomarkers & Biomedical Research Tools

KEYWORDS

Annexin, membrane repair, cardiac injury, neuronal injury, recombinant protein, therapeutic agent, acute therapy, chronic disorder, cell membrane, cardiovascular, muscular dystrophy, TBI, SCI, DMD, MI, reperfusion injury, rare disease

Background

Blood pressure (BP) monitoring is a cornerstone of cardiovascular health management, as hypertension is a leading risk factor for heart disease, stroke, and other serious conditions. Traditionally, BP is measured intermittently using inflatable cuffs, which can be uncomfortable and impractical for continuous monitoring. The growing prevalence of wearable health devices, such as smartwatches, has driven demand for non-invasive, continuous BP monitoring solutions that are comfortable, unobtrusive, and suitable for everyday use. Continuous BP monitoring can provide valuable insights into an individual’s cardiovascular health, enable early detection of hypertension, and support personalized healthcare interventions. As such, there is a significant need for wearable technologies that can deliver accurate, reliable, and equitable BP measurements across diverse populations.

Current approaches to wearable BP monitoring predominantly rely on photoplethysmography (PPG), an optical technique that estimates BP by analyzing blood volume changes in the microvascular bed of tissue. However, PPG-based systems face several critical limitations. Their accuracy is often compromised in individuals with darker skin tones due to reduced optical penetration and weaker light-artery interactions, leading to biased readings and inequitable healthcare outcomes. Additionally, PPG sensors are highly susceptible to motion artifacts, which can distort measurements during daily activities and reduce reliability. Integration of PPG sensors into wearable devices also requires precise alignment and intimate skin contact, which can be uncomfortable and limit user compliance. These challenges highlight the need for alternative, robust, and equitable BP monitoring methods that can overcome the shortcomings of current optical and contact-based technologies.

Technology Description

This technology is a smartwatch-integrable, low-power wearable system designed for continuous, non-invasive blood pressure monitoring using radio frequency (RF) bioimpedance and artificial intelligence. By repurposing a standard inverted F-type Wi-Fi antenna from a commercial smartwatch and mounting it on a 3D-printed nylon substrate within a watch strap, the system operates in a non-contact manner to measure the reflection parameter (S11) of an RF signal at the tissue-artery interface. This allows it to detect changes in arterial bioimpedance, which correlate with blood flow and blood pressure. The system extracts both frequency and time-domain features from these bioimpedance signals and processes them with an AdaBoosted Decision Tree regressor to estimate systolic and diastolic blood pressure. The approach is robust to variations in skin color, less susceptible to motion artifacts than optical methods, and is easily integrated into existing smartwatch infrastructure, achieving accuracy comparable to medical-grade photoplethysmography (PPG) sensors and meeting BHS/AAMI standards.

What differentiates this technology is its unique combination of RF bioimpedance sensing and AI-driven analysis, which overcomes significant limitations of current wearable blood pressure monitors, particularly those relying on PPG. Unlike PPG, which can be biased by skin pigmentation and is sensitive to motion, this RF-based solution provides equitable, reliable measurements across diverse populations and in real-world conditions. Its non-contact design enhances user comfort and device durability, while leveraging existing smartwatch hardware simplifies manufacturing and integration, reducing cost and complexity. Preliminary studies demonstrate that its accuracy rivals medical-grade devices, with mean absolute errors well within clinical standards. The platform’s adaptability to other wearable forms, such as rings, and its potential for broader health monitoring applications—ranging from stress and mood detection to pharmaceutical studies—further distinguish it as a transformative advancement in wearable health technology.

Benefits

• Continuous, non-invasive blood pressure monitoring integrated into a smartwatch form factor
• Robust to skin color variations, eliminating bias common in optical PPG-based devices
• Non-contact measurement enhances user comfort and reduces need for precise sensor placement
• Lower power consumption suitable for wearable, continuous monitoring
• Reduced susceptibility to motion artifacts compared to optical and radar methods
• Utilizes existing smartwatch Wi-Fi antennas for simplified integration and reduced system complexity
• Achieves clinically relevant accuracy meeting BHS and AAMI standards
• Potential for expansion to other health monitoring applications such as stress, hydration, and pharmaceutical effects

Commercial Applications

• Continuous blood pressure monitoring
• Remote hypertension management
• Equitable health tracking wearables
• Population health analytics
• Pharmaceutical effect monitoring

Additional Information

This wearable system continuously monitors blood pressure non-invasively. It repurposes a smartwatch Wi-Fi antenna to measure radio frequency bioimpedance (S11) at the tissue-artery interface. Extracted frequency and time-domain features from these signals are processed by an AdaBoosted Decision Tree regressor to estimate systolic and diastolic BP. This RF-based approach offers robustness to skin color and motion artifacts.

Intellectual Property

PCT/US2025/039271

• Strategy games / grand strategy games / 4X games
• AI in games
• AI agents
• Open-source games
• Video game development

Advantages: 

• Improved decision making in games
• Evolving game design with AI
• Enhanced user experience in games
• Opportunities for human–AI interaction during gameplay

Background:
Traditional artificial intelligence infrastructures depend heavily on continuous internet connectivity and advanced, energy-demanding hardware, restricting their deployment in rural or underdeveloped regions. Additionally, many areas lack the necessary infrastructure to support such systems, leading to limited access to AI-driven solutions. There is a growing need to create efficient, low-cost, and eco-friendly AI platforms that can operate autonomously in off-grid settings without compromising performance or privacy. This technology was developed to address these challenges by rethinking AI deployment in ways that are sustainable, inclusive, and adaptable to existing hardware resources.

Technology Overview:  
This innovation introduces a modular edge AI architecture capable of running entirely off-grid through integration with renewable energy sources like solar and wind power. It benchmarks distributed AI inference across a range of hardware platforms, including single-board computers and GPU-accelerated devices, to optimize the balance between budget constraints, available computational resources, energy consumption, and processing performance. A distinguishing feature is its platform-agnostic design, enabling the use of legacy smartphones repurposed as sensor interfaces. This not only reduces electronic waste but also enhances user privacy by minimizing data transmission over networks. The system supports multiple deployment modes to adapt to varied operational scenarios and resource availability. Its versatility has been proven through field trials in diverse environments like the Adirondacks, highlighting its potential for real-world applications. By enabling intelligent data processing at the edge without reliance on constant connectivity, this technology facilitates equitable access to AI capabilities while promoting environmental sustainability. 

https://suny.technologypublisher.com/files/sites/adobestock_857930286.jpeg
Photo for reference only, not a depiction of the invention.

Advantages:  
•    Energy Efficiency: Operates entirely on modular renewable energy sources, reducing dependence on fossil fuels and grid power.
•    Platform Agnostic: Compatible with a wide range of hardware, including repurposed legacy devices, ensuring broad accessibility and cost-effectiveness.
•    Reduced E-Waste: Extends the usable life of existing devices, minimizing environmental impact and resource consumption.
•    Enhanced Privacy: Localized data processing limits exposure of sensitive information by reducing the need for cloud connectivity.
•    Flexible Deployment: Supports multiple modes to adapt to different hardware capacities and deployment environments.
•    Validated in Real-World Conditions: Proven effectiveness through field trials in remote and resource-constrained locations. 

Applications:  
•    Education: Enabling AI-driven educational tools and resources in remote areas lacking stable internet access.
•    Agriculture: Supporting smart farming practices through localized data analysis and sensor integration.
•    Emergency Response: Facilitating autonomous and reliable AI systems for disaster and wilderness survival scenarios.
•    Environmental Monitoring: Deploying edge AI to collect and analyze ecological data in off-grid natural reserves.
•    Rural Development: Providing infrastructure-independent intelligent solutions to improve quality of life and economic opportunities. 

Intellectual Property Summary:
Proprietary know-how; patent strategy pending

Stage of Development:
TRL 4

Licensing Status:
This technology is available for licensing.

This hardware-based security gateway for Internet of Things (IoT) and wireless sensor networks protects data by shifting security processing from software to a secure module, enabling faster, lower-latency communication and thermal performance while strengthening security. Globally, more than 29 billion devices are connected to the internet, many of them operating as resource-constrained sensors and edge nodes. These heterogeneous devices often rely on software-only security, which increases processor load, power use, and delay and exposes keys to malware and physical tampering. As deployments expand to dynamic, infrastructure-intensive environments such as industrial and remote sites, gateways must secure increasingly large data streams between device networks, edge systems, and cloud services. However, traditional software-only gateways fail to secure communication without degrading performance.

Researchers at the University of Florida developed a hardware-based security gateway for IoT and wireless sensor networks that integrates a dedicated hardware security module (HSM) to isolate cryptographic operations from the main processor. By implementing hardware-based encryption, key storage, and tamper detection, the system improves performance while enhancing security across heterogeneous IoT deployments. This security gateway has been validated in infrastructure-intensive environments such as construction sites and supports broader industrial and edge computing applications.

Application

Secure, low-latency edge gateway that protects IoT sensor data and control traffic for construction sites and other industrial edge computing environments

Advantages

• Off-loads security processing to dedicated hardware, reducing network latency and network connection time by nearly 6% compared to software-based security
• Lowers encryption time by 44% and decryption delay by 57%, enabling faster data transfer to edge and cloud analytics platforms
• Shifts cryptographic processing to hardware, lowering gateway operating temperature and improving long-term system reliability
• Protects cryptographic keys in isolated hardware, preventing extraction even if software is compromised
• Detects physical tampering at the gateway level, enabling automatic alerts that support real-time responses to hardware attacks and intrusion attempts
• Secures IoT communications in remote and infrastructure-heavy environments, supporting deployment in construction and other industrial settings

Technology

This hardware-based security system for IoT and wireless sensor networks secures data by integrating a hardware security module (HSM) into an IoT gateway that connects diverse devices to edge and cloud networks. The gateway software manages device communication, while the HSM performs all cryptographic operations, including key generation, secure storage, encryption, decryption, and digital signing, independent of the main processor. The gateway routes incoming device data through the HSM, which enforces encryption and authentication before transmission beyond the local network. The security module generates and stores cryptographic keys entirely within hardware, preventing exposure to system memory or application software. The HSM also monitors physical integrity, enabling detection of tampering or unauthorized access.

• Educational platforms for formative and summative assessment
• Military and professional training simulations
• Esports player skill evaluation and development
• Corporate training and certification programs
• Gamified learning environments and serious games

• Non-invasive integration with existing applications without source code access
• Multimodal data capture including video, audio, and interaction logs
• Advanced AI techniques for accurate skill recognition and semantic mapping
• Personalized skill tracking through user-specific knowledge graphs
• Real-time and post hoc analysis capabilities
• Privacy-preserving mechanisms including data anonymization and encryption
• Seamless credential issuance and external system integration

Background:
Ambulatory ECG monitoring systems often require bulky hardware, frequent battery changes, or off board signal processing that causes data gaps, missed alerts, and degraded signal fidelity. Noise, motion artifacts, and static transmission schemes further reduce reliability, while few devices integrate real time analytics with adaptive power management in a discreet, wearable patch.

Technology Overview:
This invention is a flexible two lead ECG patch powered by a CR2032 battery and implemented on a TI CC2640 microcontroller under TI RTOS. It acquires ECG at 400 Hz and performs real time artifact rejection using dynamic baseline matching and amplitude and frequency gating, followed by R peak detection and calculation of instantaneous heart rate and four time domain HRV metrics. Valid ECG segments and derived parameters are transmitted over secure BLE using ECC key exchange and AES 128 encryption, with dynamic transmit power control based on RSSI. Four power saving modes govern data transmission and sleep intervals, including event triggered modes that suppress artifact intervals and extend operating life to approximately 250 hours.

Advantages:

• Provides continuous autonomous ECG monitoring with onboard analytics
• Improves signal fidelity using real time noise and motion artifact rejection
• Extends battery life through adaptive duty cycling and dynamic BLE power control
• Reduces data transmission volume by suppressing artifact segments
• Enhances security with ECC based key exchange and AES 128 encryption
• Improves comfort via a thin flexible two lead adhesive patch design
• Calculates HRV metrics on device to minimize external processing needs
• Supports low cost disposable deployment with simple coin cell power

Applications:

• Remote patient monitoring
• Ambulatory arrhythmia detection
• Clinical research and drug safety trials
• Athlete training and recovery tracking
• Industrial worker health and safety monitoring

Intellectual Property Summary:

• United States 11,883,176 - Issued 01/30/2024

Stage of Development:
Prototype validated under continuous monitoring conditions

Licensing Status:
This technology is available for licensing.

Licensing Potential:
Strong potential for adoption by medical device manufacturers, digital health platforms, and remote monitoring providers seeking low power, real time cardiac analytics in a comfortable, long duration wearable format.

Additional Information:
Prototype performance validation data and continuous monitoring results available upon request.

Inventors:
Kanad Ghose, Sandeep Mittal

Background:
Mobile robots and smart devices have difficulty using human-oriented floor plan images because these maps are not machine-readable and require extensive preprocessing. Existing systems depend on structured digital maps or environment-specific training, and they often fail to interpret complex spatial relationships or large open spaces. As a result, robots and assistive devices cannot reliably generate navigation plans directly from raw map images, limiting their usefulness in real-world environments.

Technology Overview:
The invention applies Vision Language Models to parse floor plan images and produce navigation instructions from combined visual and textual prompts. A floor plan image and a task description containing start and goal locations are provided to the VLM, which generates a multi-step action sequence for reaching the goal. The approach achieves high accuracy on navigation tasks, performing especially well on small and moderately complex maps. It leverages commercially available VLMs such as GPT-4o and Claude 3.5 to reason over unstructured map images without specialized preprocessing.

Advantages:

• Enables VLMs to interpret raw floor plan images for navigation
• Achieves high accuracy in multi-step navigation tasks
• Integrates visual and textual reasoning for flexible task specification
• Eliminates dependency on structured or preprocessed digital maps
• Adapts to mobile robots and consumer devices without environment-specific training
• Improves accessibility by supporting natural language interaction
• Extends to robotics, urban planning, and emergency response use cases
• Provides a competitive advantage in autonomous indoor navigation systems

Applications:

• Mobile robotics navigation
• Smartphone-based indoor navigation
• Assistive navigation for visually impaired users
• Indoor/outdoor navigation in dynamic environments
• Emergency response planning
• Urban infrastructure mapping

Intellectual Property Summary:

• United States 63/884,317 Provisional Filed 09/18/2025 Status Filed

Stage of Development:
Prototype

Licensing Status:
This technology is available for licensing.

Licensing Potential:
Strong potential for robotics developers, navigation software providers, and assistive technology companies seeking flexible, map-agnostic navigation solutions powered by AI-driven visual and language reasoning.

Additional Information:
Additional technical details and evaluation results available upon request.

Inventors:
Jeremy Blackburn, David DeFazio, Hrudayangam Mehta, Shiqi Zhang

Background:
Large-scale surveillance networks produce overwhelming volumes of video data that are difficult to analyze in real time, especially when operators have only general descriptions rather than precise identifiers. Centralized systems that transmit raw video create latency, scalability limits, and privacy concerns, while supervised biometric tools such as facial recognition are insufficient for vague queries and raise ethical issues. As a result, current systems struggle to provide efficient, privacy-preserving search capabilities for mission-critical environments.

Technology Overview:
The invention is an interactive surveillance system operating on an edge–fog–cloud architecture. Edge nodes perform human pose estimation to locate keypoints and crop body regions before extracting initial color features. Fog nodes receive only these features and apply clustering to determine dominant colors and map RGB centroids to human-readable labels through a predefined dictionary. Operators issue high-level queries such as clothing color, which are matched against extracted features to return relevant frames and camera IDs in under two seconds. The system uses a containerized microservices design for scalability and minimizes privacy risk by avoiding transmission of raw video.

Advantages:

• Enables real time querying using high level semantic descriptions
• Preserves privacy by eliminating raw video transmission
• Reduces network load through edge based feature extraction
• Improves scalability with microservices architecture
• Delivers sub two second query response for mission critical use
• Operates effectively on low cost edge hardware
• Supports decentralized processing for system resilience
• Allows flexible searching without biometric identifiers

Applications:

• Public infrastructure security
• Private facility security and loss prevention
• Emergency search and rescue
• Smart city forensic search
• Industrial safety monitoring

Intellectual Property Summary:

• United States 12,211,277 - Issued 01/28/2025

Stage of Development:
Prototype

Licensing Status:
This technology is available for licensing.

Licensing Potential:
Strong potential for adoption by security system providers, smart city developers, and infrastructure operators seeking real-time, privacy-preserving video analytics with reduced bandwidth and scalable edge deployment for mission-critical environments.

Additional Information:
Prototype system demonstrations and performance validation details available upon request.

Inventors:
Yu Chen, Seyed yahya Nikouei

Background:
Real-time 360-degree video communication requires transmitting full spherical video frames even though users view only a small portion at any moment, wasting bandwidth and degrading viewport quality. Low-latency requirements prevent the use of buffering, complex prediction models, or heavy processing borrowed from on-demand streaming, and existing real-time communication frameworks are not designed to optimize 360-degree content. This leads to inefficient transmission, poor visual fidelity in the user’s field of view, and difficulty meeting real-time performance constraints.

Technology Overview:
The invention uses content-adaptive oriented projection techniques to dynamically reshape 360-degree video frames so that pixel density is concentrated in a user’s current viewing direction. Real-time viewport feedback and network conditions determine projection parameters, which are applied using GPU-accelerated transformations for low-latency processing. Projection metadata is transmitted using RTP header extensions, allowing receivers to accurately reverse the transformation and display high-quality viewport content while minimizing transmission of unviewed pixels.

Advantages:

• Improves viewport visual quality through dynamic projection
• Reduces bandwidth consumption by minimizing unviewed pixel transmission
• Achieves real-time performance using GPU-accelerated transformations
• Integrates seamlessly with existing WebRTC workflows
• Enhances user experience with adaptive content and bitrate control

Applications:

• Immersive video conferencing
• Industrial telepresence and remote inspection
• Real-time medical telementoring
• Interactive immersive content delivery

Intellectual Property Summary:

• United States – 63/090,273 – Provisional – Filed 10/11/2020 – Issued 10/12/2020 – Status: Converted
• United States – 17/449,893 – US20220116441A1 – Patent No. 11,785,069 – Utility – Filed 10/4/2021 – Issued 10/10/2023 – Status: Patented

Stage of Development:
Prototype

Licensing Status:
This technology is available for licensing.

Licensing Potential:
Strong potential for adoption by video communication platforms, immersive media providers, and telepresence solution developers seeking bandwidth-efficient, low-latency, and high-quality 360-degree streaming technologies.

Additional Information:
Additional technical details and implementation information available upon request.

Inventors:
Yao Liu, Shuoqian Wang

Background:
Continuous arrhythmia monitoring with wearable ECG sensors is limited by the large data volumes required to transmit raw or compressed waveforms, which consume significant power and shorten device lifespan. Battery-powered wearables struggle to support long-term operation because frequent recharging interrupts monitoring, reduces compliance, and burdens users. Existing compression techniques still demand substantial computation or sacrifice diagnostic detail, making it difficult to achieve reliable real-time detection under tight energy and bandwidth constraints.

Technology Overview:
The invention uses a Smart ECG Patch that acquires ECG signals, detects R-peaks, removes artifacts, and encodes each cardiac cycle into 14 integer parameters representing QRS morphology and instantaneous heart rate. This compact representation is transmitted via low-power Bluetooth to a host device, where a BiLSTM-based classifier performs real-time arrhythmia detection across seven categories. The system incorporates adaptive power management and secure transmission using ECC cryptography and AES-128 encryption, enabling efficient, continuous monitoring.

Advantages:

• Reduces data transmission through compact ECG feature encoding
• Extends battery life by minimizing wireless communication demands
• Supports real-time arrhythmia detection using a lightweight encoded signal
• Lowers computational load on wearable hardware
• Maintains diagnostic accuracy using a BiLSTM classifier trained on encoded features
• Enables efficient continuous monitoring on small, battery-powered devices

Applications:

• Remote cardiac monitoring
• Wearable health and fitness tracking
• Military physiological monitoring
• First-responder physiological monitoring
• Athletic performance tracking
• Recovery tracking

Intellectual Property Summary:

• United States US 2024-0188876 – Pending

Stage of Development:
Prototype demonstrated under continuous monitoring conditions

Licensing Status:
This technology is available for licensing.

Licensing Potential:
Strong potential for wearable medical device manufacturers, digital health platforms, and remote patient monitoring providers seeking energy-efficient, real-time cardiac monitoring solutions with extended battery life and reduced data transmission requirements.

Additional Information:
Information available upon request.

Inventors:
Kanad Ghose, Sandeep Mittal

This technology delivers an objective, data‑driven PTSD assessment based on heart activity, addressing the absence of standardized physiological criteria and reducing dependence on subjective self‑reports.

Key Benefits

• Uses measurable physiological signals rather than self-reported symptoms.
• Employs non-invasive electrocardiography or wearable sensors for heart activity data collection.
• Machine learning-based classifier enhances diagnostic reliability and long-term monitoring of illness severity.

Market Summary

PTSD affects millions of individuals globally, with particularly high prevalence among military and veteran populations and a significant presence in the broader public. Despite its impact, PTSD diagnosis and ongoing assessment still rely largely on subjective self-reporting and clinical judgment, increasing the risk of missed or inaccurate diagnoses and suboptimal care. As healthcare delivery expands across clinical, military, and virtual environments, there is growing demand for objective, scalable solutions that support accurate screening and continuous monitoring. Tools that deliver reliable physiological insights can enable earlier identification, support personalized treatment decisions, and ultimately improve long-term outcomes for individuals living with PTSD.

Technical Summary

Emory researchers have developed a system utilizing a novel heart rate-based window segmentation strategy that analyzes RR interval data — the time between two consecutive R-waves — on an electrocardiogram (ECG) from electrocardiography or similar heart activity measurements. It identifies quiescent segments of RR intervals to extract heart rate variability (HRV) features, which reflects overall variability in heartbeats and autonomic nervous system function. These features are compared against a machine learning classifier trained on data from individuals with and without PTSD, enabling determination of PTSD status or severity.

Development Stage

Validated using ECG recordings from human subjects.

Publication Reinertsen, E., et al. (2017). Heart rate-based window segmentation improves accuracy of classifying posttraumatic stress disorder using heart rate variability measures. Physiological Measurement, 38(6), 1061–1076. https://doi.org/10.1088/1361-6579/aa6e9c

Example: The National Cancer Institute (NCI) seeks research co-development partners and/or licensees for a collection of T-cell receptors (TCRs) that specifically target the mutated KRAS antigen.

This technology encompasses a DNA methylation–based diagnostic platform designed to improve the accuracy and consistency of cancer classification, with demonstrated utility for tumors of the central nervous system, kidney, and hematopoietic system. By identifying disease-specific methylation signatures, the approach reduces interobserver variability and enhances diagnostic confidence. The central nervous system (CNS) classifier is built from a curated reference set of 16,567 methylation profiles and organizes tumors into 22 families and 133 clinically relevant diagnostic classes, including 21 newly developed methylation classes not represented in other existing tools. Across multiple independent validation cohorts (n = 5,875), the classifier demonstrated robust performance, and in a clinical-impact analysis of 1,204 NIH validation cases, methylation profiling materially influenced final diagnosis in 74.4% of cases by refining, increasing precision, or reclassifying. The CNS classifier was deployed as a user-facing software tool, MethylScape Analysis, which streamlines methylation-based classification workflows for CNS tumors (https://methylscape.ccr.cancer.gov/). The development of multiple specialized classifiers supports a more granular understanding of tumor biology and  informed clinical decision-making.

Description of Technology:

Accurate CNS tumor classification can be challenging when tumors show overlapping histology, limited tissue or atypical features. A meaningful fraction of cases remains unclassified or assigned with limited confidence with current molecular tools. These diagnostic ambiguities directly affect subtype and grade assignment which, in turn, influence treatment planning, prognosis, and clinical trial eligibility. Variability across observers and institutions can lead to additional testing, delays, and inconsistent diagnoses.

The NCI/Bethesda classifier addresses this gap using DNA methylation patterns as a robust molecular fingerprint. It applies a stratified machine learning framework to extend diagnostic coverage and improve assignment confidence for CNS tumors. The classifier was developed from a rigorously curated reference set of over 16k methylation profiles, structured into 22 tumor families and 133 clinically relevant diagnostic classes and includes 21 recently developed methylation classes not represented in existing tools. The approach has been validated across multiple independent cohorts (n = 5,875) and supports deployment through MethylScape, a public web-based portal that streamlines classifier execution for broad accessibility. In an NIH validation cohort analysis of 1,204 high-confidence matches with pre-methylation diagnoses available, methylation profiling confirmed the initial diagnosis in 25.6% of cases while driving clinically meaningful diagnostic evolution in the remainder, including refined diagnosis (subtyping) in 14.6%, new diagnosis with increased precision in 54.7%, and substantial diagnostic reclassification in 5.0%—changes that are expected to affect patient management in the reclassification subset.

Renal neoplasms present a parallel diagnostic challenge due to morphologic and molecular heterogeneity, overlapping microscopic features, and interobserver variability. As a result, a subset of cases are unclassifiable even after immunohistochemical, mutation and cytogenetic workups. To address this, the Kidney Classifier component of this platform leverages genome-wide DNA methylation profiling (feasible on formalin-fixed paraffin-embedded tissue using robust array-based methods). It was developed through examination of methylation signatures from over 2,000 renal neoplasms, identifying 23 coherent methylation groups that correlate with known tumor types and reveal clinically relevant novel subtypes. A machine learning classifier trained on 1,284 samples was externally tested on 287 renal neoplasms, demonstrating >90% concordance between expected neoplasm type and high-score methylation-based classification, with discordant cases highlighting opportunities for diagnostic reclassification and improved precision in challenging renal tumor evaluations.

Licensing and collaboration opportunities include commercial development of methylation-based diagnostic tests and/or software-enabled classification solutions for clinical laboratories, reference labs, and diagnostic companies. Partners may engage in external validation (retrospective and prospective), assay standardization, integration into pathology workflows and reporting systems, and extension of classifier coverage to additional tumor types and multi-institutional datasets. Consistent with consensus recommendations for complementary classifiers, the inventors are also interested in collaborations that: (1) operationalize multi-classifier strategies (concordant/complementary prediction to increase confidence; (2) leverage discordance to trigger orthogonal follow-up) and (3) accelerate clinical translation through scalable deployment models- including CLIA laboratory workflows and regulated diagnostic pathways.

Potential Commercial Applications:

• Molecular classification and diagnosis of CNS and kidney tumors, including difficult-to-classify and low-confidence cases
• Diagnostic subtyping aligned to WHO-guided entities
• Reference-lab and hospital-lab deployment
• Clinical trial stratification and translational research cohort harmonization
• Multi-classifier diagnostic decision support
• Cancer treatment development

Competitive Advantages:

• Developed from a rigorously curated, large reference set of methylation profiles
• Clinically relevant CNS diagnostic
• CNS tumor methylation classes not represented in existing tools, expanding diagnostic coverage
• Clinical-impact analysis creating superior diagnostic precision
• Superior classifier for kidney cancer
• Superior classifiers for multiple solid, difficult-to-diagnose tumors
• Integrative into clinical workflows, improving diagnostic practices and enhancing patient care

SHORT DESCRIPTION
A pulsed-laser synthesis method for making advanced metastable materials, including metal carbides and nitrides.

• Bryan Hunter*
• Alexis Magana
• Christopher Nowak

NU 2025-190

IP STATUS

Provisional Application Filed (joint with Harvard University)

DEVELOPMENT STAGE

TRL-3 - Experimental Proof-of-Concept: Active R&D is initiated and key functions have been validated in a lab environment.

BACKGROUND
Metal carbides are a broad class of compounds containing metal-carbon bonds, endowing them with extreme durability, high melting points, and unique electronic properties that make them amenable to a variety of technological applications. Carbides are often employed at extreme temperatures and pressures for this reason. Despite their value, carbide synthesis presents many challenges, and certain metals do not form well-defined carbides at all. Current synthesis methods rarely yield new binary compounds, especially for metals like lead that poorly dissolve carbon. Conventional high-temperature and chemical protocols often require extreme conditions and incur high costs. There remains a need for innovative processes capable of producing advanced refractory materials.
 

ABSTRACT
Northwestern researchers report the synthesis of lead(II) carbide (Pb₂C) using pulsed-laser synthesis (PuLS) in an unsaturated liquid hydrocarbon. PuLS accesses the “impossible carbide” by reaching extreme temperatures and pressures. Lead(II) carbide was characterized as a layered, hexagonal methide with paramagnetic behavior at room temperature using microscopy and spectroscopy. This technology enables further exploration of previously inaccessible compounds and opens new avenues for discovering novel carbides with unique structural and electronic properties.

APPLICATIONS

• Synthesis of many metastable materials, including nitrides and carbides (difficult to manufacture)
• Lead carbide in itself has not been explored (e.g. magnetic properties/superconductivity), though other lead compounds have seen huge utility (e.g. perovskites) 
• Potential applications in high-temperature components, catalytic reactors, electronic contacts, and optical coatings

ADVANTAGES

• Provides a general method to produce nanoparticles of unique composition and structure (PuLS) 
• Produces metastable materials
• Uses a new flow-through technology that maximizes product formation

CATEGORY/INDUSTRY PIPELINE
Materials and Industrial Processes; Engineering & Technology

KEYWORDS
pulsed-laser synthesis, lead carbide, refractory materials, high-temperature synthesis, nanomaterials, metal carbides

INVO CONTACT 

Anne-Isabelle Henry Baruch, PhD

Senior Invention Manager

(847) 491-4629

a-henry@northwestern.edu

​

Connection of STM head to transfer mechanism in RT chamber

Invention Summary:

Traditional scanning probe microscopy (SPM) systems face a range of significant technical and operational challenges that hinder performance and flexibility. Rigid, hard-wired connections restrict head configurations, while probe transfers between chambers risk compromising vacuum integrity. Large instrument footprints and cumbersome navigation systems make operation in confined ultra-high vacuum (UHV) and high magnetic field environments particularly difficult. Cryogen-free STM setups are further hampered by pulse tube-induced vibrations that degrade imaging quality, and conventional large vertical translation stages add maintenance burden, higher operating costs, and extended pump-down times. The lack of multi-modal capability within a single instrument limits experimental versatility, while vacuum leaks and dead space introduced during probe translation create additional inefficiencies that slow research progress.

Rutgers inventors have developed a novel modular SPM head featuring a unique weak spring and pin electrical connection system that allows easy mechanical and electrical coupling. This design supports in situ switching among scanning tunneling microscopy (STM), atomic force microscopy (AFM), and magnetic force microscopy (MFM) modes and facilitates transfer between atmospheric pressure, UHV chambers, and cryogenic or high magnetic field environments without breaking vacuum. The compact probe transfer mechanism replaces bulky traditional translation stages with a small-footprint, flexible design that shuttles probes between spatially separated sites within UHV systems, significantly reducing system size, pump down times, and leakage risks while improving measurement precision under demanding experimental conditions.

Market Applications:

• Advanced materials & nanotechnology labs requiring compact, modular, multi-modal SPM solutions.
• Low-temperature, high magnetic field & cryogen-free research facilities demanding atomic-resolution STM imaging.
• Quantum materials & surface science research requiring precise, reliable probe exchange in controlled environments.
• Academic, industrial R&D & cryogenic instrumentation manufacturers seeking flexible, vibration-sensitive SPM upgrades.

Advantages:

• Modular plug-and-play design enables flexible multi-modal integration across multiple UHV systems, supporting effortless switching between STM, AFM, and MFM without breaking vacuum.
• Compact all-in-one architecture integrates movement and vibration isolation into a reduced footprint, enabling atomic-resolution STM imaging in cryogen-free cryostats.
• Enhanced reliability and stability through automatic height locking, separate vacuum seals, and real-time sensors minimizing experimental disruptions.

Publications:

• • Coe, Angela M., Guohong Li, and Eva Y. Andrei. "Cryogen-free modular scanning tunneling microscope operating at 4-K in high magnetic field on a compact ultra-high vacuum platform." Review of Scientific Instruments 95.8 (2024). https://doi.org/10.1063/5.0212244
• • Coe, Angela M., Guohong Li, and Eva Y. Andrei. "Flexible internal transporter with gravity-assisted mechanism for vertical transfer of microscope head." Review of Scientific Instruments 96.5 (2025). https://doi.org/10.1063/5.0264135

Intellectual Property & Development Status:   Issued U.S. patents: US12098026B2, US11474127B2, US12360136B2. Pending U.S. divisional application: US20250033878A1.  Pending U.S. non-provisional application. Available for licensing and/or research collaboration. For any business development and other collaborative partnerships, contact:  marketingbd@research.rutgers.edu

This vegetation anchoring device secures plants used for coastal restoration projects. Coastal wetlands and shorelines provide important ecological services, including storm protection, improved water quality, and habitat for wildlife. However, erosion, storm activity, and rising sea levels are degrading many of these environments, increasing the need for effective coastal restoration strategies. The global coastal protection systems market size reached $18 billion USD in 2024 and is expected to reach $46 billion USD by 2033, with a compound aggregate growth rate of 12.60%. Coastal restoration projects often involve planting vegetation using landscape plugs, which are small, containerized plants with established roots that are easy to transport and plant in large quantities. Existing erosion control methods can help stabilize shorelines, but they are not designed to hold individual plant plugs. Additionally, currents and sediment movement can dislodge newly planted vegetation in coastal environments before roots have fully developed. There is a need for anchoring devices specifically designed to withstand harsh coastal environmental conditions.

Researchers at the University of Florida are developing a carrier for plants to help secure and anchor vegetation used in coastal restoration. The device is designed specifically to hold landscape plant plugs in place in coastal substrates where traditional stakes or containers are ineffective due to soft sediments and harsh environmental conditions.

Application

Anchors plant plugs in place, reducing the risk of displacing newly planted vegetation used in coastal restoration and shoreline stabilization projects

Advantages

• Keeps newly planted vegetation in place, enabling root systems to establish themselves in the surrounding substrate
• Includes openings for water circulation, supporting root growth into the surrounding sediment
• Designed for installation without specialized equipment, enabling manual deployment in restoration sites
• Manufactured using biodegradable material, ensuring the anchors do not persist in the aquatic environment

Technology

The system uses three primary components—a perforated basket, a thread cap, and an insertion spike—function together to secure a landscape plant plug in coastal substrates. The perforated basket holds the plant plug and its growing medium while allowing water movement and root growth through the surrounding openings. The threaded cap then attaches to the basket and secures the plug in position, enabling it to remain stable during environmental exposure. Finally, extending from the bottom of the basket is an insertion spike that penetrates the coastal substrate and anchors the device in place. The anchor is required only during the time the plant establishes a root system; therefore, the anchors are produced using biodegradable materials to ensure they do not persist in the aquatic environment. The device gradually breaks down after the vegetation becomes established.

• Enhancing security and performance of Concentrated Solar Power plants with real-time IoT data aggregation
• Deployment in 6G-enabled Industrial IoT networks requiring robust, low-latency communication
• Integration into smart grid energy management systems
• Use in critical infrastructure monitoring where resilience against signal interference is mandatory

• AI-based differentiation between legitimate sensor data and malicious interference using binary hypothesis testing
• Dynamic threshold adjustment through reinforcement learning for optimized attack detection sensitivity
• Secure enrollment phase for reliable node registration and baseline profiling
• Power allocation strategy minimizing errors under power constraints
• Hierarchical defense combining signal fingerprinting, adaptive beamforming, and node ejection protocols
• Experimental validation proving significant improvements in data aggregation and attack detection

The rising levels of atmospheric carbon dioxide (CO2) present a critical global challenge, significantly contributing to climate change and ocean acidification. Current CO2 sequestration methods, such as geological storage, face numerous hurdles, including leakage risks, high costs, and the need for extensive monitoring. An emerging method involves the formation, compaction, sealing, and disposal of CO2 hydrates on the seabed. CO2 hydrates are solid, ice-like structures that form under high-pressure, low-temperature conditions unique to the ocean floor. This method offers several advantages over traditional storage techniques, including increased stability, reduced risk of leakage, and the potential for long-term, large-scale CO2 storage. However, the artificial synthesis of CO2 hydrates is slow, hindered the development of hydrate-based industrial technologies. The fastest reported CO2 hydrate formation rate is 20 g/L/hr, insufficient for large-scale carbon sequestration. Therefore it is crucial to promote faster hydrate growth in order to achieve gigascale CO2 sequestration through hydrate formation.

Technology Overview: 

This technology provides a comprehensive solution for the formation, compaction, sealing, and disposal of CO2 hydrates on the seabed, addressing the major challenge of slow hydrate formation. The process begins with the rapid formation of CO2 hydrates in a bubble column reactor, where CO2 is recirculated to enhance the formation rate. This approach significantly accelerates hydrate formation (800 g/L/hr), overcoming the limitations of traditional methods. Once formed, the CO2 hydrates are compacted into dense plugs, ensuring stability and ease of handling. These plugs are then sealed to prevent dissociation and leakage during transport. The sealed CO2 hydrate plugs are transported to the seabed, leveraging natural oceanic conditions to maintain their stability. Finally, the plugs are disposed of on the seabed, where the high-pressure, low-temperature environment ensures their long-term stability and prevents CO2 from escaping back into the atmosphere. This method offers a scalable and efficient approach to CO2 sequestration, providing a viable solution for reducing atmospheric CO2 levels and mitigating the impacts of climate change. 

Benefits 

• This method utilizes a bubble column reactor with CO2 recirculation to significantly speed up CO2 hydrate formation to rates of 800 g/L/hr, overcoming the slow rates that hinder traditional methods.  

• The method is designed for large-scale application, making it feasible to achieve gigaton-scale carbon sequestration. 

• The sealing process prevents CO2 hydrate plugs from breaking down during transport, ensuring safe delivery to the seabed. 

Applications  

• Oil and gas 

• Carbon sequestration 

• Chemical manufacturing 

Opportunity 

• This novel method for CO2 hydrate formation is scalable and the fastest reported rate in the industry, making it feasible to achieve gigaton-scale carbon sequestration. 

• Available for licensing