Predictive Response Biomarker Discovery Using TCR and Gene Profiles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current therapeutic interventions for diseases such as cancer, autoimmune diseases, and neurodegenerative diseases are only effective in a portion of patients, leading to financial burden and potential harm for those who do not benefit, highlighting the need to identify a proper patient population for specific treatment regimens.
Innovation Solution
A method to identify predictive response biomarkers (PRBs) by comparing TCR clonotypes and gene expression profiles in pre-treatment and post-treatment samples, using T-cell-targeted immunomodulatory therapies like anti-PD-1 antagonists, to predict treatment response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If T-cell-targeted immunomodulatory therapy is administered to all cancer patients, then some patients may experience treatment effects, but many patients will not benefit and may suffer harm while incurring financial burden
Solution Approach 1:
The patent applies preliminary action by performing single-cell profiling of T cells from patient tumor samples before treatment to identify predictive biomarkers. This pre-treatment characterization allows clinicians to predict which patients are likely to respond to T-cell-targeted immunomodulatory therapy, enabling informed treatment decisions that prevent harm to non-responders while maintaining effectiveness for responders.
2Adaptability or versatility
If T-cell-targeted immunomodulatory therapy is administered to all cancer patients, then treatment coverage is maximized, but resource waste increases due to ineffective treatments
Solution Approach 1:
The patent performs single-cell profiling and biomarker identification before treatment initiation, allowing for patient stratification based on predicted treatment response. This preliminary characterization enables selective treatment assignment, ensuring that expensive T-cell-targeted immunomodulatory therapies are administered only to patients with high probability of response, thereby maximizing resource efficiency while maintaining broad adaptability through personalized medicine approaches.
3Measurement precision
If comprehensive single-cell profiling and biomarker analysis are performed, then treatment selection accuracy is improved, but diagnostic complexity and cost increase
Solution Approach 1:
The patent extracts and focuses on specific predictive biomarkers from the comprehensive single-cell profiling data, such as genes differentially expressed in T cells with expanding versus non-expanding TCR clonotypes. By identifying and measuring only these key predictive markers rather than analyzing all single-cell parameters, the method maintains high measurement precision for treatment prediction while reducing diagnostic complexity and making the approach more clinically feasible.
Data Source
AI summary
The invention described herein provides a method to identify predictive response biomarkers (PRBs) for a treatment regimen. The PRBs can be used to identify suitable or unsuitable) patient population for the treatment regimen.