# PHASE I AWARD - AN ORGAN-ON-VASCULARNET MODEL FOR IN VITRO EVALUATION OF RADIATION AND DRUG THERAPIES

> **NIH NIH N43** · CHROMOLOGIC, LLC · 2024 · $399,975

## Abstract

There is an urgent need for near physiological organ-on-chip models that can replace testing in animals for human drug development. The Organ-on-VascularNet platform is a 3D organoid tissue model with selfassembled vascular networks that enables pharmaceutical testing in both normal and malignant tissues. Organ-on-VascularNet models will be exposed to a combination of x-ray irradiation and interferon â (IFN-â) treatment, and the cellular and molecular responses will be compared to the outcomes observed in vivo. We expect that the Organ-on-VascularNet model will allow for the near-physiological interactions of components of the circulating immune system with the resident tissue, which characterize the responses observed in vivo. Thus, IFN-â treatment should protect normal intestinal tissue for radiation-induced damage and should sensitize tumors to immune checkpoint inhibitor therapy. Successful recapitulation of the in vivo responses suggests a role for the Organ-on-VascarNet model in drug development. We will discuss the potential of this technology with the FDA under their Drug Development Tool (DDT) and Innovative Science and Technology Approaches for New Drugs (ISTAND) programs.

## Key facts

- **NIH application ID:** 11191354
- **Project number:** 75N91024C00068-0-9999-1
- **Recipient organization:** CHROMOLOGIC, LLC
- **Principal Investigator:** CLAUDE ROGERS
- **Activity code:** N43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $399,975
- **Award type:** —
- **Project period:** 2024-09-16 → 2025-09-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11191354

## Citation

> US National Institutes of Health, RePORTER application 11191354, PHASE I AWARD - AN ORGAN-ON-VASCULARNET MODEL FOR IN VITRO EVALUATION OF RADIATION AND DRUG THERAPIES (75N91024C00068-0-9999-1). Retrieved via AI Analytics 2026-06-02 from https://api.ai-analytics.org/grant/nih/11191354. Licensed CC0.

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