Life Science — Document Classification for Regulatory Compliance

Overview

The Document Classification for Regulatory Compliance DAG is designed to streamline the process of categorizing documents within the life sciences sector, particularly for pharmaceutical companies. Its primary purpose is to ensure that all documents are appropriately classified according to their content and intended use, thereby enhancing compliance with regulatory standards. The DAG ingests various data sources, including clinical trial documentation, regulatory submissions, and internal polic

The Document Classification for Regulatory Compliance DAG is designed to streamline the process of categorizing documents within the life sciences sector, particularly for pharmaceutical companies. Its primary purpose is to ensure that all documents are appropriately classified according to their content and intended use, thereby enhancing compliance with regulatory standards. The DAG ingests various data sources, including clinical trial documentation, regulatory submissions, and internal policy documents. The ingestion pipeline utilizes robust data extraction techniques to gather relevant information from these inputs. Once the data is ingested, the processing steps involve applying machine learning algorithms to identify document intentions and categories. This includes natural language processing (NLP) techniques to analyze the text and classify documents into predefined categories. Quality controls are implemented to ensure that the classification is accurate, with alerts configured to flag any documents that do not meet compliance standards. The outputs of this DAG include a compliance register that logs each document's classification status, ensuring that all documents are easily accessible for audits. Monitoring KPIs include the accuracy of classifications, the number of non-compliant documents flagged, and the time taken for classification. The business value of this DAG lies in its ability to reduce manual classification efforts, minimize compliance risks, and ensure that documents are readily available for regulatory review, ultimately supporting the organization's operational efficiency and regulatory adherence.

Part of the Knowledge Portal & Ontologies solution for the Life Science industry.

Use cases

• Enhances regulatory compliance and reduces audit risks
• Increases efficiency by automating document processing
• Improves accuracy of document categorization
• Facilitates faster response to regulatory inquiries
• Supports better data governance and management practices