Columbia Technology Ventures

3D organoids for modeling squamous epithelial pathology and personalized medicine

This technology is a method to generate squamous epithelial 3D organoids that can mimic the natural physiology of tissues and be used as a personalized pathology model.

Unmet Need: Platform for predicting patient-specific treatment outcomes in squamous epithelia

Current in vitro platforms for personalized medicine include using patient-specific organoids to understand patient-specific genetic and molecular makeup. However, most of these organoids have limited capability to predict treatment responses in diseases involving squamous epithelia. These limitations create a gap in personalized drug testing, disease modeling, and clinical decision-making for conditions like esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). A robust 3D squamous epithelial organoid platform is needed to understand the disease progression and improve personalized treatment strategies.

The Technology: 3D squamous epithelial organoids for personalized and predictive medicine

This technology describes a method to generate squamous epithelial 3D organoids, capable of mimicking native epithelial gastrointestinal physiology. These organoids can be created within 14 days from patient-derived tissues and provide a predictive platform for personalized medicine. This technology can serve as an experimental platform to study genetic and environmental factors in the development and progression of diseases occurring in squamous epithelia for individual patients.

This technology has been validated with human and mouse tissue.

Applications:

  • Drug screening
  • Disease modeling for squamous epithelial diseases
  • Research tool for esophageal adenocarcinoma (EAC), esophageal squamous cell carcinoma (ESCC), and esophageal organogenesis

Advantages:

  • Patient-specific models
  • Fast generation time
  • Clinically relevant physiology
  • Multi-species compatibility
  • Rapid in vitro drug evaluation
  • Versatility in disease modeling

Lead Inventor:

Anil K. Rustgi, M.D.

Patent Information:

Patent Pending (US20250066739)

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