Drug Interaction Prediction Using Structural Similarity Profiles

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Solution Overview

Problem

Current methods for predicting drug interactions, including those with food, are limited by time and cost, and lack a comprehensive approach for evaluating various types of interactions using structural information, which can lead to adverse drug effects.

Innovation Solution

A method that calculates structural similarity profiles of compounds and uses a trained model to predict interactions, outputting results in standardized sentences to describe the mechanism of action, enabling the prediction of drug-drug and drug-food interactions and identifying combinations with a low probability of adverse effects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If comprehensive evaluation of all drug-drug interactions under various conditions is conducted, then prediction accuracy and reliability are improved, but time consumption and cost increase significantly

Engineering Contradiction:

Improveprediction accuracyVSAvoidevaluation time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent pre-calculates and stores structural similarity profiles for drugs against a reference library before actual interaction prediction. This preliminary action allows the system to quickly retrieve and compare pre-computed similarity data during interaction evaluation, avoiding redundant calculations and significantly reducing prediction time while maintaining comprehensive evaluation capability

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent divides the complex drug interaction evaluation into separate modular components: structural similarity calculation, profile generation, and interaction prediction. Each component can be independently optimized and executed, allowing parallel processing and reducing overall evaluation time while maintaining comprehensive assessment

Inventive Principle:

Principle #1Segmentation

2Reliability

If comprehensive evaluation of all drug-drug interactions under various conditions is conducted, then prediction accuracy and reliability are improved, but cost increases significantly

Engineering Contradiction:

Improveprediction accuracyVSAvoidevaluation cost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent creates structural similarity profiles that serve as reusable representations of drug structures. These profile copies can be stored and repeatedly used for multiple interaction predictions without requiring repeated full structural analyses, significantly reducing computational cost while maintaining prediction accuracy

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system pre-computes structural similarity profiles against a reference library before actual interaction predictions. This preliminary computation avoids redundant calculations during subsequent predictions, reducing overall computational cost and energy consumption while enabling comprehensive interaction evaluation

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If structural similarity profiles are calculated by comparing each compound with multiple predefined compounds, then prediction comprehensiveness is improved, but calculation complexity increases

Engineering Contradiction:

Improveprediction comprehensivenessVSAvoidcalculation complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces structural similarity profiles as intermediary representations between raw chemical structures and interaction predictions. These profiles serve as a standardized medium that simplifies comparison operations and enables systematic evaluation across multiple compounds while maintaining comprehensive prediction capability

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent transforms complex structural comparison problems into standardized similarity score calculations by changing the parameter representation from raw molecular structures to numerical similarity profiles. This parameter transformation simplifies the calculation process while maintaining the ability to comprehensively evaluate multiple interaction types

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11568962B2Method for predicting drug-drug or drug-food interaction by using structural information of drug

Publication Date: 2023.01.31 KOREA ADVANCED INST OF SCI & TECH

AI summary

The present invention relates to a method for predicting a drug-drug interaction and a drug-food interaction by using structural information of a drug and, more particularly, to a method for predicting the mechanism of action and activity of a drug interaction through interaction prediction results expressed by a standardized sentence. When using a method for predicting a drug interaction according to the present invention, a drug interaction can be predicted quickly and accurately, and in particular, activity information of an unknown compound can also be predicted by expressing a prediction result by means of a sentence, and thus the method is very useful for developing a drug exhibiting desired activity without causing adverse effects.