CRS Biomarker Profiling for CAR T Cell Risk Stratification
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Solution Overview
Problem
There is a need for methods and biomarkers to predict a patient's risk of developing severe cytokine release syndrome (CRS) associated with CAR T cell therapy, which is a potentially life-threatening adverse side effect.
Innovation Solution
The method involves evaluating the level or activity of biomarkers such as soluble gp130 (sgp130) or soluble IL6 receptor (sIL6R) in a subject to determine the risk of developing severe CRS, allowing for early intervention and potential adjustments to treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAR T cell therapy is administered to treat refractory hematologic malignancies, then complete remission rates improve (up to 90%), but the risk of severe cytokine release syndrome (CRS) increases
Solution Approach 1:
The patent measures sgp130 and sIL6R biomarker levels before CAR T cell therapy administration to identify patients at high risk for severe CRS. This preliminary assessment allows for preventive stratification, enabling clinicians to take preemptive actions (such as prophylactic treatments or modified dosing) for identified high-risk patients before the adverse event occurs, thereby reducing the incidence or severity of CRS while maintaining the therapeutic benefits of CAR T cell therapy
2Reliability
If biomarker measurement methods are developed to predict CRS risk, then patient safety improves, but diagnostic complexity increases
Solution Approach 1:
The patent extracts and measures specific biomarkers (sgp130 and sIL6R) from patient samples using established immunoassay techniques. By focusing on these two key predictive biomarkers rather than analyzing entire cytokine profiles or complex molecular signatures, the method achieves accurate CRS risk prediction while maintaining diagnostic simplicity and utilizing readily available laboratory technologies
Solution Approach 2:
The patent utilizes changes in biomarker parameters (sgp130 and sIL6R levels) as predictors of CRS risk. By monitoring quantitative changes in these specific protein levels rather than relying on complex multi-parameter genomic or proteomic profiles, the method achieves predictive accuracy through simple, measurable parameter changes that can be assessed using standard clinical laboratory methods
Data Source
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AI summary
The present disclosure relates to the identification and use of biomarkers (e.g., analytes, analyte profiles, or markers (e.g., gene expression and/or protein expression profiles)) with clinical relevance to cytokine release syndrome (CRS).