ABSTRACT Agency Reg Intel Report

How Does it Work?

Redica Systems is the first analytics platform to connect Quality Assurance with Regulatory Surveillance.
We structure unstructured content and data, unlocking its full potential for sophisticated analysis. With the insights we provide our customers can:

  • Manage Vendor/Supplier Risk
  • Improve Inspection Readiness
  • Oversee Postmarket Surveillance
  • Strengthen Regulatory Surveillance
  • Improve team productivity
  • And much more!
Updated sources

Redica Systems
Data Sourcing

We start with our primary data sources, which are health regulators like FDA, as well their international counterparts, including Health Canada, MHRA, EMA, and others.

We also add important data from standards bodies like PIC/S, ISO, and USP. From those sources, we ingest as many key documents as we can, through various methods.

  • Top Health Agencies
  • Other Critical Agencies
  • Standards Body & Harmonization Orgs
  • Trade Associations, Groups, etc.
noise to insight

Turning Noise Into Insights

The trick is making sense of this huge volume of unstructured, unnormalized data and turning the noise into analytical insights.

We built our own Intelligent Document Processing (IDP) system to make sense of the thousands of quality and regulatory documents we ingest daily. The data goes through deduping, normalization, entity resolution, tagging, scoring, translation, and categorization.

Redica Systems scans the document and automatically tags the relevant observations, saving you and your team time.

Enrichment tier

How Redica Systems Builds Upon FDA and Other Agency Data

Once the data is structured and cleansed, enrichment begins. We apply models like our Quality Systems Labels Model and Red Flag Risk Models to empower more sophisticated analysis. Redica Systems automatically tags all of the important metadata for you, making it easily accessible for trending and reporting purposes.

Even though the FDA is ahead of their international counterparts in publishing data, Redica Systems has far more of each document type than the FDA Data Dashboard. More importantly, the aggregated analytics that Redica Systems allows is far beyond the capabilities of any health regulator’s website.

Read more on how we go further than the FDA Dashboard.


Linking ‘Everything to Everything’

The Redica ID is a unique identifier assigned to every key entity in the Redica Systems database: Sites, Inspections, People, Documents, Organizations, and Products. This enables our customers to see the interconnections and impacts from one object to another. It reduces the amount of noise in the data by ensuring that there is only one master profile for each entity.

Read this blog post for more on how the Redica ID is different from FDA’s FEI.

483 Layers of Data Extraction and Structuring

Redica DocIQ

Redica Systems DocIQ extracts and structures machine-readable data from non-machine readable documents like PDFs of FDA Form 483s. Using AI/ML to apply ontologies and master terms, topics and themes across data can be identified. For example, Named Entity Recognition would identify a company name, and link it to the corresponding Redica ID to connect to the integrated data model.

Integrated workflows give humans the ability to verify the results and train the models to improve.

Redica DocIQ is a set of services that can be orchestrated given the needs of each specific document type.

Read this blog post for more on Redica DocIQ.

Redica Knowledge Graph

Redica Knowledge Graph

The Redica Systems knowledge graph shows the relationships between entities. It is a unique global, harmonized data model. For example, if you start with a FDA 483, it has relationships with a site, an organization, various products, an inspection event, FDA investigators, etc. Mapping those relationships helps you understand how one may impact the other.

Similar to how we create the key objects themselves (the Redica ID), relationships must be established between the Redica IDs to create knowledge and insights.

(Updated) Human Drug GMP Model Categories March 2025

Redica Ontologies

When Redica Systems utilizes AI to label agency enforcement action documents (like FDA 483s and Warning Letters), it follows our ontologies, like this one for Human Drug GMP.

This results in an unprecedented level of tagging and labeling detail, allowing you to answer questions like, “are Quality Unit observations trending up in North America over the past year?”.

The Future of AI in Quality and Regulatory

For insights into how Redica Systems is using Artificial Intelligence (AI) and Machine Learning (ML) in our app roadmap and how we think it will impact Quality and Regulatory for life sciences companies, watch this video of our CEO’s presentation at a recent industry conference.

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Our Quality and Regulatory Intelligence (QRI) platform helps more than 200 leading life sciences companies of all sizes solve their complex GxP compliance challenges.

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