Biomarker Analysis System for Radiation Triage Using Primate Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies lack a reliable point-of-need radiation biodosimeter to effectively triage individuals exposed to ionizing radiation, as there is limited data on human radiation response and ethical constraints prevent direct human studies.
Innovation Solution
A method and apparatus using a panel of biomarkers (e.g., AMY1, FLT3L, MCP1) to determine radiation exposure by analyzing biomarker concentrations in human subjects, with a test statistic threshold derived from non-human primate data, allowing for rapid classification of radiation exposure levels in humans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a radiation biodosimeter is developed for point-of-need triage, then the ability to provide timely and effective medical treatment is improved, but the reliability is worsened due to limited human radiation response data and ethical constraints preventing direct human studies
Solution Approach 1:
The patent uses non-human primate (NHP) data as an intermediary to develop test statistic thresholds for human radiation biodosimetry. Since direct human radiation response data is limited and ethical constraints prevent conducting such studies, the invention applies machine learning models trained on NHP biomarker data to predict human radiation exposure levels, thereby bridging the gap between animal studies and human application.
Solution Approach 2:
The patent performs preliminary actions by collecting and analyzing biomarker data from NHP subjects under controlled radiation exposure conditions before applying the model to human samples. This preliminary data collection and model training enable rapid triage of human radiation exposures without requiring direct human radiation response studies.
2Reliability
If direct human radiation response studies are conducted to improve reliability, then the accuracy of biodosimetry is improved, but ethical constraints prevent such studies
Solution Approach 1:
The patent uses non-human primate (NHP) data as an intermediary to develop test statistic thresholds for human radiation biodosimetry. Since direct human radiation response data is limited and ethical constraints prevent conducting such studies, the invention applies machine learning models trained on NHP biomarker data to predict human radiation exposure levels, thereby bridging the gap between animal studies and human application.
Solution Approach 2:
The patent creates a computational model that copies the radiation response patterns observed in NHP subjects and applies this copied knowledge to human biodosimetry. The machine learning model replicates the relationship between biomarker concentrations and radiation exposure levels from NHP studies, enabling human radiation assessment without direct human experimentation.
3Measurement precision
If multiple biomarkers are analyzed to improve accuracy of radiation exposure assessment, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent segments the radiation biodosimetry function into multiple independent biomarker measurements (e.g., different proteins or genetic markers). Each biomarker is measured separately using lateral flow assay technology, and the individual measurements are then integrated through a machine learning model to produce the final radiation exposure assessment. This segmentation allows for improved precision while maintaining relatively simple individual measurement components.
Solution Approach 2:
The patent employs a universal machine learning model that can process data from multiple different biomarkers through a single integrated analysis framework. The test statistic threshold model is designed to accommodate various biomarker combinations, allowing the same device and algorithm to analyze different sets of biomarkers depending on the specific application, thereby reducing overall system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables timely and accurate triage of radiation exposure in humans, facilitating effective medical treatment and resource allocation following nuclear events, without requiring direct human radiation response data.
Implementation Method 1
a port for receiving a test strip that supports lateral flow of a fluid sample along a lateral flow direction
Implementation Method 2
a reader configured to obtain separable light intensity measurements from the plurality of zones
Data Source
AI summary
Method and systems are described comprising receiving a plurality of human subject biomarker concentration values associated with a human subject, wherein the plurality of human subject biomarkers is associated with a condition, determining, based on the plurality of human subject biomarker concentration values, a human subject test statistic, comparing the human subject test statistic to a test statistic threshold, wherein the test statistic threshold is derived based on non-human primate (NHP) subject data, and, determining, based on the human subject test statistic exceeding the test statistic threshold, that the human subject has the condition.