A novel machine learning model for prediction of ICI responsive patients based on ICI pharmacokinetics
TS-075183 — Problem
Current eligibility biomarkers for Immune checkpoint inhibitors (ICIs) poorly predict patient’s response. Drug clearance, both at baseline and over time, is a stronger predictor of ICI effectiveness, however the current non-linear mixed effects modeling (NLME) approach for estimating …
- College: College of Pharmacy
- Inventors: Phelps, Mitchell "Mitch"; Adeluola, Adeoluwa; Coss, Christopher; Kim, Kyeongmin; Mo, Xiaokui "Molly"; Owen, Dwight
- Licensing Officer: Hampton, Andrew
EmitGCL: Prediction of Future Metastasis based on Graph Contrastive Learning
TS-075168 — Problem
Metastasis is the primary driver of cancer-related deaths, yet accurately predicting its onset is a major clinical challenge. Current diagnostic tools often fail to detect occult metastatic cells and metastatic precursor cells, resulting in either overdiagnosis, with unnecessary treatments,…
- College: College of Medicine (COM)
- Inventors: Ma, Qin; Wang, Xiaoying
- Licensing Officer: Hampton, Andrew
Convolutional Neural Network to Assess Phayngeal and Laryngeal Pathology and Function on Nasopharyngolaryngoscopy
TS-063154 — Worldwide, 686,000 new head and neck (H&N) cancers are diagnosed yearly, and 375,000 people will die annually. Human papillomavirus (HPV) is responsible for an increasing subset of H&N malignancies called oropharyngeal squamous cell carcinomas (OPSCC). Although it has a better prognosis than…
- College: College of Engineering (COE)
- Inventors: Krening, Samantha; Gifford, Ryan; Jhawar, Sachin; VanKoevering, Kyle
- Licensing Officer: Hampton, Andrew
Transforming PAH Management with PHORA: Empowering Physicians for Better Patient Care
TS-062764 — The Pulmonary Hypertension Outcomes Risk Assessment (PHORA): a PAH risk stratification tool.
Pulmonary Arterial Hypertension (PAH) demands precise risk stratification for effective patient management. Clinical decision support tools can help inform treatment decisions made by physicians and other healthcare providers, usually at the point of care.
The Need
Current methods for assistin…
- College: College of Medicine (COM)
- Inventors: Benza, Ray; Lin, Shili; Mathur, Puneet
- Licensing Officer: Hampton, Andrew
An AI Solution for Mobile Stroke Detection for TeleMedicine, Hospital and Paramedic Use
TS-060782 — Problem Statement:
Diagnosis of arterial occlusion and an associated stroke can be lengthy, delaying patient access to treatment. As large vessel occlusions account for 24 to 46% of acute ischemic strokes and may require treatment in a comprehensive stroke center, early diagnosis is key.
Solution:…
- College: College of Engineering (COE)
- Inventors: Yilmaz, Alper; Gulati, Deepak Kumar
- Licensing Officer: Hampton, Andrew
Metabolite-Based Diagnostics for Joint Infection
TS-059537 — An untargeted NMR-based metabolomics approach to identify metabolic compounds as signatures of bacterial joint infections and methods for the treatment and prevention thereof.
Pseudomonas aeruginosa, a biofilm-producing pathogenic bacterium, exhibits resistance to many antibiotics. This leads to acute and chronic joint infections that are difficult to treat. Accordingly, a critical need exists for accurate biofilm diagnosis, prevention, and treatment. While culture-free…
- College: College of Medicine (COM)
- Inventors: Stoodley, Paul "DECEASED"; Bruschweiler, Rafael; Leggett, Abigail
- Licensing Officer: Hampton, Andrew
Automated Detection of Tumor Budding in Colorectal Cancer
TS-039267 — A non-invasive and automated tumor budding image analysis system for colorectal cancer. This program can detect tumor buds in traditional H&E stained sections without the need for manual assessment.
Colorectal cancer is the third most commonly diagnosed cancer in the United States. With a survival rate of less than 65%, early detection and treatment are key factors in survival. Tumor budding, associated with higher tumor stage, lymph node metastasis, and decreased disease-free survival, has e…
- College: College of Medicine (COM)
- Inventors: Gurcan, Metin; Ahmad Fauzi, Mohammad Faizal; Chen, Wei "Wei"; Frankel, Wendy
- Licensing Officer: Hampton, Andrew
