Non-Coding RNA Expression Assays for Therapeutic Discovery
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Solution Overview
Problem
Current methods for discovering therapeutic applications of interventions are time-consuming and costly, requiring a detailed understanding of mechanisms and specific drug targets, which limits the identification of new indications for known therapeutic entities and prediction of pharmacological properties.
Innovation Solution
A method involving expression assays to measure the effect of interventions on non-coding RNA profiles, allowing for the analysis of correlations between different interventions and biological systems without needing to understand the mechanism of action, thereby identifying potential therapeutic applications and toxicological profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If detailed mechanistic analysis and specific drug target identification are performed, then reliability of therapeutic application is improved, but loss of time and productivity deteriorate
Solution Approach 1:
The patent creates a reference database of non-coding RNA expression profiles from biological systems with known therapeutic applications. This reference database serves as a template or copy that can be compared against test biological systems to identify potential therapeutic applications without performing detailed mechanistic analysis on each new candidate, thereby reducing time loss while maintaining reliability through pattern matching
Solution Approach 2:
The patent shifts the analytical approach from examining detailed mechanistic parameters (molecular pathways, protein interactions) to measuring non-coding RNA expression levels as surrogate parameters. This parameter change enables faster comparison and identification of therapeutic applications by focusing on observable expression patterns rather than complex underlying mechanisms
2Reliability
If detailed mechanistic analysis and specific drug target identification are performed, then reliability of therapeutic application is improved, but productivity deteriorates
Solution Approach 1:
The reference database of non-coding RNA expression profiles acts as a reusable template that accelerates the discovery process. By comparing test systems against this pre-established reference, the method enables parallel processing of multiple candidates simultaneously, thereby increasing productivity without sacrificing the reliability that comes from systematic comparison against known effective treatments
Solution Approach 2:
The non-coding RNA expression profile serves as a universal marker that can identify therapeutic applications across different biological systems and disease contexts. This multi-functional approach allows a single reference database to evaluate multiple candidates simultaneously, increasing overall productivity while maintaining reliable identification of therapeutic potentials
3Adaptability or versatility
If comprehensive expression assays on multiple interventions and biological systems are performed, then adaptability and versatility are improved, but device complexity and loss of time worsen
Solution Approach 1:
The reference database stores pre-analyzed non-coding RNA expression profiles from various biological systems and therapeutic interventions. This copied reference information enables the system to evaluate new candidates by comparison rather than requiring de novo comprehensive analysis, thereby reducing the effective complexity and time required while maintaining broad adaptability and versatility in identifying therapeutic applications
Data Source
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AI summary
There is disclosed a method comprising the steps of: carrying out a plurality of expression assays, each expression assay comprising the steps of: carrying out an intervention on a biological system, measuring an expression profile of non-coding RNAs in the biological system resulting from the intervention, and storing an expression data set derived from the measured expression profile, the said expression assays concerning either or both a plurality of different interventions and a plurality of different biological systems; and analysing the resulting expression data sets to determine correlations between the effect on the expression profile of non-coding RNAs of the respective intervention in groups of two or more expression assays concerning either or both different interventions or different biological systems.