PLGF Biomarker Stratification for Renal Cell Carcinoma Therapy
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Solution Overview
Problem
There is a need for a method to predict which renal cell carcinoma (RCC) patients are likely to benefit clinically from treatment with a combination of a VEGFR inhibitor and an Ang2 inhibitor, as current approaches lack effectiveness in identifying suitable candidates.
Innovation Solution
A method involving the comparison of a patient's placental growth factor (PLGF) concentration with a PLGF concentration parameter, where a lower PLGF concentration indicates a statistically increased likelihood of clinical benefit from treatment with a VEGFR inhibitor and an Ang2 inhibitor, allowing for personalized treatment decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current approaches are used to identify treatment candidates, then treatment can be administered, but the effectiveness in identifying suitable candidates is insufficient
Solution Approach 1:
The patent performs preliminary stratification of RCC patients based on PLGF concentration levels before administering combination therapy. By measuring PLGF concentrations and comparing them to established thresholds, the system identifies patients most likely to benefit from VEGFR inhibitor and Ang2 inhibitor combination treatment, thereby improving prediction accuracy and preventing loss of patient stratification information
Solution Approach 2:
The patent establishes a feedback mechanism where PLGF concentration measurements provide predictive information about treatment response. This feedback loop allows clinicians to adjust treatment strategies based on individual patient PLGF levels, improving the reliability of treatment outcome predictions while preserving critical patient-specific information
2Reliability
If PLGF concentration measurement and comparison is performed, then patient stratification is achieved, but additional testing requirements are introduced
Solution Approach 1:
The patent extracts the critical predictive information (PLGF concentration) from complex patient data and isolates it as a single measurable parameter. By focusing on this specific biomarker and comparing it to established thresholds, the system achieves accurate patient stratification without requiring analysis of multiple complex parameters, thereby reducing overall testing procedure complexity
Solution Approach 2:
The patent transforms the complex problem of predicting treatment response into a simple parameter comparison task. By establishing fixed PLGF concentration thresholds that predict treatment benefit, the system converts a complex multi-factor prediction problem into a straightforward single-parameter assessment, reducing device and procedure complexity while maintaining high reliability
Data Source
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AI summary
Methods and compositions are disclosed for predicting and treating the clinical benefit to a human renal cell carcinoma patient prior to their treatment with a VEGFR inhibitor and an Ang2 inhibitor.