Technology can help change that perception. Advanced solutions can already automatically extract, code, and process AE data. Soon, more PV operations will adopt AI to produce earlier, clearer, and more granular accounts of safety issues. That means they’ll have more opportunities to influence prescribers in a positive and proactive manner. Emerging tools will also encourage greater openness across the industry and promote impartial comparisons of alternative products. This will drive more trust, collaboration—and ultimately fewer ADRs.
Transforming the science at the heart of pharmacovigilance
There’s been a lot of progress in developing a scalable and sustainable PV operating model for the industry. Companies are creating solutions that apply AI across the entire information value chain for end-to-end case
processing, aggregate reporting, and signal detection/ evaluation automation. At Genpact, for example, we’re helping several life sciences companies transform their PV operations. We’re doing this using an AI-based product that integrates optical character recognition, robotic process automation, natural language processing, and machine learning technologies.
This AI-led PV system automatically extracts and codes AE data from multiple source formats to reduce case processing effort and increase the sensitivity and speed of signal detection. These same AI technologies are transforming the science at the heart of the PV analytics challenge. Signal-management tools of the future will scrape the web for meaningful data related to a particular drug. The system will automatically identify analogues based on logical constructs like drug class and therapeutic area, as well as less intuitive factors. In addition, data features of historical safety issues with other drugs will help predict future safety issues associated with new drugs.