The client, a national regulatory body, is responsible for ensuring pharmaceuticals and medical devices bought by the public are licensed and not counterfeit or fake. The growing online availability of prescription drugs being sold direct to customers is of particular concern.
The sheer scale and dynamism of this illegal on-line activity, inhabiting the deep and dark web as well as the much smaller surface web, dwarfed the limited technology and resources available to the client.
RED developed a Regulatory Surety Compliance (RISC) toolset using its proprietary Unique machine learning technology.
RISC is able to scan not only the surface web, but the much larger and more difficult to reach deep and dark web.
Key word searches for pharmaceutical names generates a list of URL ‘hits’ which are ranked based using both rules-based and Machine Learning approaches.
A target list of domains and associated URLs is generated. Blacklist sites are excluded, and approved (i.e. authorised) sites are flagged (as even authorised sources can be in violation of their licence).
The target list is prioritised based on the number of keyword hits against each domain and other weighting factors. High priority targets may be subject to further forensic analysis, across numerous datasets to attempt to identify the site operator and location. Alternatively the domain name may be struck off, taking down the website, by providing the registrars with appropriate documentation and supporting evidence.
Based on keywords provided by the client over 5,000 URLs of significant interest were identified over a 3 month period.
Not only did the RISC system deliver a step change in capability to search for illegal and unregulated online sales of pharmaceuticals and medical devices, but the prioritisation and forensic analysis tools enabled the client to focus their investigatory resources on the highest value targets.
The RISC technology is readily deployable in many other areas where unlicensed or illegal products are on offer on-line. Get in contact to arrange a demonstration.