Pharmacodynamic Relation Modeling for Therapeutic and Side-Effect Scoring
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Solution Overview
Problem
Existing methods for analyzing drug-disease relevance relations, such as drug repositioning based on comprehensive similarity measures and two-way random walk algorithms, fail to accurately distinguish therapeutic and side-effect relations, leading to inaccurate drug selection for disease treatment.
Innovation Solution
A pharmacodynamic relation model is constructed using vector space data and an evaluation function ƒ(d,r,s)=∥MR×dv−MR×sv−vR∥² to analyze drug-disease relevance relations, including therapeutic and side-effect relations, by optimizing a target function L to ensure a pre-defined margin γ, enabling accurate drug and disease relevance scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods (comprehensive similarity measures and two-way random walk algorithms) are used to analyze drug-disease relevance, then the analysis can be performed, but the accuracy of distinguishing therapeutic and side-effect relations deteriorates
Solution Approach 1:
The patent segments the drug-disease relevance analysis into two distinct components: therapeutic relations and side-effect relations. By constructing separate evaluation functions ƒ(d,r1,s) for therapeutic relations and ƒ(d,r0,s) for side-effect relations, the system can accurately distinguish between beneficial and harmful drug effects, thereby improving both measurement precision and reliability of drug selection.
2Ease of operation
If a single evaluation function is used for drug-disease relevance, then the analysis process is simplified, but the ability to distinguish between therapeutic and side-effect relations deteriorates
Solution Approach 1:
The patent divides the evaluation process into separate functions for therapeutic and side-effect relations. This segmentation maintains operational clarity while significantly improving the precision of relation classification, allowing the system to accurately identify whether a drug-disease pair represents a beneficial or harmful interaction.
3Reliability
If drug doses are increased to ensure therapeutic effect, then the therapeutic effect is improved, but the side effects in patients' bodies worsen
Solution Approach 1:
The patent implements a feedback mechanism by evaluating both therapeutic and side-effect relations simultaneously through separate evaluation functions. This allows the system to provide comprehensive feedback on drug performance, enabling optimization of drug dosing to achieve maximum therapeutic effect while minimizing harmful side effects through balanced consideration of both relation types.
Data Source
AI summary
A method for processing a drug-disease relevance relation includes receiving drug information; analyzing the drug information and different disease information to obtain a disease in different diseases in the different disease information that has a relevance relation with a drug in the drug information, the relevance relation including a therapeutic relation between the drug and the disease and/or a side-effect relation between the drug and the disease; and outputting the disease having the relevance relation with the drug.