Life Science — AI Model Compliance Registry Automation

Overview

The purpose of this DAG is to streamline the creation and maintenance of a compliance registry specifically for AI models used in the life sciences sector. By integrating data from both internal systems, such as clinical trial databases and external sources like regulatory bodies, this workflow ensures comprehensive compliance tracking. The ingestion pipeline begins with the extraction of relevant data, followed by transformation and validation processes. These processes include quality controls

The purpose of this DAG is to streamline the creation and maintenance of a compliance registry specifically for AI models used in the life sciences sector. By integrating data from both internal systems, such as clinical trial databases and external sources like regulatory bodies, this workflow ensures comprehensive compliance tracking. The ingestion pipeline begins with the extraction of relevant data, followed by transformation and validation processes. These processes include quality controls that verify the traceability of scientific evidence, ensuring that all models are backed by robust documentation. Regular audits are incorporated to continuously assess compliance with current regulations. The outputs of this DAG include a fully updated compliance registry, audit reports, and alerts for any discrepancies found during processing. Monitoring key performance indicators such as the number of registered models and the time taken for registry updates provides valuable insights into operational efficiency. In case of failures, alert mechanisms are in place to trigger manual interventions, thereby minimizing risks associated with non-compliance. The business value of this DAG lies in its ability to enhance regulatory adherence, reduce manual efforts, and improve the overall integrity of AI model management in life sciences.

Part of the Enterprise Search solution for the Life Science industry.

Use cases

• Ensures regulatory compliance for AI models in life sciences
• Reduces time and effort in manual compliance processes
• Enhances the reliability of scientific evidence documentation
• Improves operational efficiency through automation
• Facilitates timely updates to compliance requirements