Drug safety and pharmacovigilance are critical aspects of drug development. To understand and monitor potential risks for pharmaceuticals, researchers use many different strategies to uncover evidence of real-world reports of adverse events and patient-reported outcomes.
At the upcoming Linguamatics Text Mining Summit, there are three talks on text mining strategies that improve our understanding of drug-related adverse reactions.
Nina Mian from AstraZeneca will present research on text mining adverse event data both from FDA drug labels (derived from clinical trial data), and also from real world data from PatientsLikeMe. Eric Lewis from GSK will discuss applications of I2E for clinical safety and pharmacovigilance – particularly the problems of identifying potential “new signals” and distinguishing signal from noise. And Stuart Murray from Agios will present workflows for automated identification of potential drug safety events.
These talks, from industry specialists, demonstrate the value of text mining to access and understand the complex world of drug safety and safety signals.
The timing is opportune, as Linguamatics recently released a new OnDemand content source, I2E OnDemand FAERS. FAERS (FDA Adverse Event Reporting System) contains over nine million reports of adverse events submitted to the FDA, and reflects data from 1969 to the present day.
FAERS can be used to assess real-world data for drug adverse events in a wider population, and the individual adverse event reports can be searched and analyzed to find information about:
- Low frequency drug reactions
- Long-term effects
- Potential effects in high-risk groups
- Drug–drug and drug–food interactions
- Early detection of serious adverse events
Access to I2E OnDemand FAERS index and queries help you gain a competitive advantage by reducing the time required to find the information you need and enabling comprehensive and accurate results across these valuable data.