Product Data Harmonization for Regulatory Compliance

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Solution Overview

Problem

Current systems fail to efficiently manage and report complex product-related data across multiple entities and formats, particularly in compliance with regulations like SCIP/REACH, due to the complexity of product information and lack of coordination between suppliers, manufacturers, and regulators.

Innovation Solution

A computer system processes product information data collections by harmonizing and identifying terms, performing queries, and comparing data to generate a term-identified evaluation submission dataset, which includes lexical and semantic terms, to identify errors, relationships, and potential compliance issues, facilitating regulatory submissions and risk assessments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual data gathering and coordination is performed across multiple suppliers and manufacturers, then compliance accuracy can be maintained through human review, but the time and resources required increase significantly

Engineering Contradiction:

Improvecompliance accuracyVSAvoiddata gathering time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically collecting, harmonizing, and validating product information data from multiple sources before regulatory submission deadlines. The computer system proactively gathers data from suppliers and manufacturers, performs term identification and data harmonization, and prepares compliance documentation in advance, eliminating the need for last-minute manual data gathering while ensuring accuracy through systematic processing.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If complex product information data is processed without automated harmonization, then data integrity can be maintained through careful manual review, but the complexity of coordination between multiple entities increases

Engineering Contradiction:

Improvedata integrityVSAvoidcoordination complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The computer system acts as an intermediary between multiple suppliers, manufacturers, and regulatory bodies. It automatically performs data harmonization by identifying and standardizing terms across different data formats and sources, resolving inconsistencies without requiring direct coordination between all parties. The system mediates the complexity by centralizing the harmonization process and automatically managing the coordination requirements.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system applies parameter changes by transforming product information data into a standardized format through automated term identification and data harmonization. It changes the state of raw, unstructured data from multiple sources into harmonized, structured data that meets regulatory requirements, automatically adjusting parameters such as term standardization, data formatting, and compliance criteria without manual intervention.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If automated processing is implemented without advanced NLP and semantic analysis, then processing speed increases, but the ability to accurately identify errors and relationships in complex data decreases

Engineering Contradiction:

Improveprocessing speedVSAvoiderror identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system replaces traditional mechanical data processing methods with advanced artificial intelligence including natural language processing (NLP) and semantic analysis. Instead of simple keyword matching or rule-based processing, the system uses AI models to understand the meaning and context of product information data, accurately identify errors, detect relationships between data elements, and assess compliance risks while maintaining high processing speeds through automated AI-driven analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11568423B2Multi-dimensional product information analysis, management, and application systems and methods

Publication Date: 2023.01.31 ASSENT INC

AI summary

Disclosed here are methods of analyzing product-related datasets using a computer system including a product data collection; receiving a product-related data submission; identifying system-identified terms in the submission; generating a query dataset comprising search elements, such as lexical vector(s), semantic vector(s), or both; querying the product data collection and identifying datasets that sufficiently match aspect(s) of the query dataset; comparing the content of the submission and matching datasets to provide an output such as a determination of an error or omission in the submission, identifying a relationship between the submission product and a product associated with an identified dataset; or assessing one or more product status characteristics; and optionally performing additional applications, such as generating a regulatory authority submission based on the determination that the submission product is subject a regulatory requirements based on the comparison of the submission with the identified datasets.