# Rapid Automated High-Throughput Radiation Biodosimetry

> **NIH NIH U19** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $703,456

## Abstract

Project 1 focuses on fully-automated ultra high-throughput biodosimetry, made possible by the RABiT-II
approach of complete automation of sample preparation and imaging in commercial robotic platforms. Its goals
are “Assay Development”, “Beyond Simple Exposures”, “Beyond Model Systems” and “Optimized Biomarker
Integration”, all motivated by the very wide variety of different exposure scenarios and countermeasure needs.
Assay Development: The goal here is a major decrease in time-to-result of the high-throughput RABiT-II
assays. While throughputs of the micronucleus and dicentric assays in our automated systems are extremely
high (>10,000 samples per day), these assays require ~54 hours for cell culture. A 6-hour Premature
Chromosome Condensation (PCC) dicentric assay with completely automated sample preparation and imaging
in multiwell plates is being developed, and will result in a major reduction in time-to-result.
Beyond Simple Exposures: There are a wide variety of different exposure scenarios to which individuals will
be exposed after an IND, including mixed neutron+photon exposure, very high dose rate, variable low dose
rate and partial body exposure. This CMCR uses unique irradiation facilities for each of these scenarios, and
these will be used to assess whether the quantitative high-throughput biomarkers that were developed using
photons at intermediate dose rates can reconstruct the dose in these very different scenarios - and also
whether the biomarkers can be used to identify these different exposure scenarios.
Beyond Model Systems: addresses issues which underlie all radiation biodosimetry / biomarker studies, but
have not yet been systematically addressed, either for photons or for neutrons. Radiation biodosimetry is
intended to assess in-vivo human exposures, but biodosimetric assay development / testing is typically
performed either with ex-vivo irradiated human blood or in-vivo in animals. Thus a major knowledge gap exists
regarding the validity of transferring biodosimetry results to in-vivo human exposures. The in-vivo animal 
human extrapolation cannot be directly evaluated, and neither can the human ex-vivo  in-vivo extrapolation.
So the goal here is to separate out and address independently the ex-vivo  in-vivo issue (in mice and in NHP)
and the NHP  human issue (ex-vivo, humans vs. NHP), both for photons and for neutrons.
Optimized Biomarker Integration: The three different biomarker systems investigated in this CMCR program
(Project 1: cytogenetics; Project 2: transcriptomics, Project 3: metabolomics) all reflect different balances of
capabilities in terms of throughput, time-to-result, signal lifetime, dose reconstruction, exposure scenario
identification and individual radiosensitivity prediction. Our common goal is to identify their optimal integrated
usage in each of a wide variety of different possible large-scale exposure scenarios. As results emerge from
this Project, they will be “fed” to the Biostatistics Core...

## Key facts

- **NIH application ID:** 9940229
- **Project number:** 2U19AI067773-16
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** DAVID JONATHAN BRENNER
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $703,456
- **Award type:** 2
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9940229

## Citation

> US National Institutes of Health, RePORTER application 9940229, Rapid Automated High-Throughput Radiation Biodosimetry (2U19AI067773-16). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9940229. Licensed CC0.

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