Rapid, point-of-care assessment of radiation exposure in human blood

This technology is a biodosimeter capable of rapidly detecting and assessing the degree of radiation exposure using human blood samples that can be used at the point of care.

Unmet Need: Effective dosimetry to triage populations following large-scale nuclear events

Following a large-scale radiological or nuclear event, large numbers of people may be exposed to ionizing radiation and require rapid and dose-dependent medical treatment. Current biodosimetry methods are time-intensive and difficult to scale up to meet the demands of such events. Therefore, there is a need for a more effective tool capable of identifying and measuring human exposure to ionizing radiation that can scale up to quickly assess larger sample sizes.

The Technology: Point-of-care dosimeter for rapid assessment of radiation exposure

This technology is an ELISA-based immunoassay platform that rapidly detects and quantifies a panel of radio-responsive protein biomarkers in blood lymphocytes that can be found in the blood of individuals recently exposed to ionizing radiation. The presence of these proteins can be used to accurately predict the degree of radiation exposure up to one week post-exposure. A custom machine learning module integrates measurements from multiple biomarkers, including intracellular proteins (BAX, DDB2) and plasma proteins, along with cell counts and viability data, to classify radiation exposure and predict absorbed dose. The system categorizes exposure into clinically relevant dose ranges that correspond to specific treatment decisions, enabling medical providers to rapidly triage patients and initiate appropriate interventions. The technology is capable of testing 40 samples in ~4 hours or 400 samples in ~15 hours, ensuring same-day diagnosis and thereby allowing medical providers to more quickly address the exposure and begin treatment.

This technology has been validated in ex vivo human blood models and non-human primate models.

Applications:

  • Mass-screening of individuals who may have been exposed to radiation after a radiological event
  • Machine learning-based dose prediction provides clinically relevant dose categorization
  • Biomarkers for radiation research
  • Biomarkers for the analysis of radiation therapy effectiveness
  • Biomarkers to predict tumor radio-resistance and radiation-induced toxicity

Advantages:

  • Can quickly scale up to analyze large populations
  • Allows measurement of radiation dosage in individuals exposed to ionizing radiation
  • Easily accessible at the point of care
  • Potential to be engineered into a simplified, in-field tool to further increase the speed and efficiency of radiation exposure triaging after radiological events

Lead Inventor:

Helen Turner, Ph.D.

Patent Information:

Patent Pending (WO/2025/217542)

Related Publications:

Tech Ventures Reference: