With these insights unlocked, our customers can:
How does it work?
The sources of Redica Systems data
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.
How Redica Systems Builds Upon FDA and Other Agency Data
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.
Turning noise into insights
The trick is making sense of this huge volume of unstructured, unnormalized data, therefore turning noise into analytical insights. We accomplish that with deduping, normalization, entity resolution, tagging, scoring, translation, categorization, and finally by assigning every discrete entity its own Redica ID, which serves as a unique identifier.
No more confusion over the vast number of permutations of a single organization or site’s name. Just one, clean, clear record.
Quality Systems Labels Model
Once the data is structured and cleansed, enrichment can begin. We apply models like our Quality Systems Labels Model and our Red Flag Risk Model 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.
No more highlighting a Form 483 to see which Quality Systems are impacted.
For insights into how Redica Systems is using AI and 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.