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TL-iGeneCombo: Transfer Learning for Individual Sample Specific Gene Combination Effect Prediction and Selection in Cancer Cells
TS-075184 — Problem Synthetic lethality (SL) is defined as a gene combination effect (GCE) of two genes where loss-of-function of both genes, rather than one, causes cell death. While carrying strong therapeutic potential in the treatment of cancer, SL interactions are context specific and sparse, thereby limi…
  • College: College of Medicine (COM)
  • Inventors: Li, Lang; Gökbağ, Birkan
  • Licensing Officer: Hampton, Andrew

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

Finding rare events by knowing where NOT to look
TS-051417 — Traditional regression analysis has been a staple in predicting cause-effect relationships. Counltess industries use these methods to predict rare events, from economic issues to cancer research, causality is often a desired result. Given the vast amount of potential variables it sometimes becomes…
  • College: College of Arts and Sciences (ASC)
  • Inventors: Melamed, David; Schoon, Eric
  • Licensing Officer: Hampton, Andrew

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