Kinase Activity Phosphorylation Profiling NSCLC Treatment Prediction
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Solution Overview
Problem
Current methods lack accuracy and efficiency in predicting the response of non-small cell lung cancer (NSCLC) patients to targeted pharmacotherapy, particularly in distinguishing between responders and non-responders before treatment, due to the variability and poor predictivity of existing biomarker-based methods.
Innovation Solution
Measuring kinase activity in NSCLC samples by comparing phosphorylation profiles in the presence and absence of a medicament, specifically using protein kinase substrates to determine differential phosphorylation levels, which predict the patient's response to targeted pharmacotherapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing biomarker-based methods (EGFR expression, c-K-ras gene mutations) are used for prediction, then the screening can be performed, but the measurement precision and reliability are poor due to high variability
Solution Approach 1:
The patent changes the measurement parameter from static biomarker detection (gene mutations, protein expression levels) to dynamic kinase activity measurement through phosphorylation profiling. This parameter change enables real-time assessment of drug-target interaction, significantly improving both measurement precision and reliability of response prediction
Solution Approach 2:
The patent replaces the mechanical/biochemical detection system (immunohistochemistry, PCR) with a phosphoproteomics-based system using mass spectrometry or phospho-specific antibodies. This substitution provides more sensitive and accurate quantification of kinase activity states, resolving the contradiction between measurement precision and reliability
2Productivity
If targeted pharmacotherapy is administered without accurate prediction, then treatment can proceed, but the loss of time and productivity occurs due to ineffective treatment and delayed response
Solution Approach 1:
The patent performs preliminary kinase activity profiling and in silico drug screening before administering targeted pharmacotherapy. This preliminary action identifies the most likely effective drug, preventing wasted time on ineffective treatments and accelerating the path to effective therapy
Solution Approach 2:
The patent implements a feedback mechanism where baseline kinase phosphorylation profiles are measured, predicted response is determined, treatment is administered, and then response is monitored. This closed-loop feedback system continuously optimizes treatment selection, improving productivity while minimizing time loss through data-driven decision making
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
This approach provides a robust and reliable method for predicting the response to targeted pharmacotherapy, enabling more accurate selection of suitable treatments and improving patient outcomes by differentiating between responders and non-responders.
Implementation Method 1
measuring the kinase activity of a sample, obtained from the non-small cell lung tumor from said patient, in the presence and in the absence of said medicament, thereby providing the phosphorylation level of phosphorylation sites present in said peptide markers
Data Source
Figure 1
AI summary
The present invention relates to a method for determining or predicting the response of a patient diagnosed with non small cell lung cancer to targeted pharmacotherapy. The present invention also aims to provide methods and devices for predicting the response of patients diagnosed with non small cell lung cancer to specific medicaments. More specifically, the present invention provides methods which measure kinase activity by studying phosphorylation levels and profiles and inhibitions thereof by drugs in samples of said patients.