FRANCE – Deloitte and Sanofi have collaborated on a next-generation, artificial intelligence (AI) software-as-a-service adverse events case intake platform aimed to revolutionize pharmacovigilance (PV) and address some of the industry’s most pressing operational safety issues.
With the amount of data and the number of sources growing at an exponential rate, many companies have begun to test and integrate machine analysis tools into their pharmacovigilance workflows.
A pharmacovigilance workflow includes a variety of data sources, such as patient cases, healthcare reports, scientific literature, and even social media.
Deloitte and Sanofi have been working together for more than two years to design, develop, and implement a comprehensive solution and approach that combines Deloitte’s ConvergeHEALTH Safety Platform with knowledge from Sanofi and Deloitte.
The Future of Health, as well as the rapid pace of technological innovation, require pharmaceutical companies to evolve their PV capabilities. Companies can establish a true center for safety intelligence across the entire product lifecycle by shifting from a reactive to a proactive, evidence-based, and patient-centric approach.
Sanofi has already improved case quality and case processing efficiencies within PV as a result of the initial deployment by automating the case intake process.
The automation has allowed Sanofi to focus resources on the rest of the adverse event (AE) case process as well as optimizing the benefit-risk profiles of their medicines.
“This collaborative initiative is a shining example of using advanced technologies in a highly-regulated area that not only leads with innovation and accelerates quality/efficiencies but allows pharmacovigilance to focus on what’s most important — the safety of our patients,” said Anand Ramanathan, Sanofi’s head of Digital Pharmacovigilance.
PV market trends
This, along with an increase in the number of adverse drug reactions (ADRs), is primarily driving market growth. Furthermore, the sudden outbreak of COVID-19 has resulted in an urgent need for a vaccine, creating numerous opportunities for market participants.
Furthermore, several key manufacturers are introducing advanced platforms to ensure automated ADR reporting, which will contribute to market growth even further.
Aside from that, various pharmaceutical companies are increasingly outsourcing pharmacovigilance operations to third parties in order to increase internal resource flexibility and productivity over shorter time periods.
Many pharma companies are now using machine learning tools to automate the process of identifying adverse events in scientific literature.
Scientific literature, particularly in XML format, is easier for text analytics tools to consume and interpret than other data sources.
This has been the starting point for many companies in automating parts of their pharmacovigilance workflow.
GSK Japan was able to automate the process of searching for phrases that suggest adverse events within the text by leveraging SciBite’s TERMite Expressions (TExpress) module. This automated workflow resulted in ultra-fast text processing and accurate identification of adverse events.