Advanced computing methods can be used for safety monitoring and early detection of potential signals of vaccine-related adverse events. These methods work by mining open-access active-moiety databases and vast scientific literature with clinical case studies.

Life sciences companies confront increasingly stringent requirements on safety signal detection and risk management. Regulatory authorities are taking steps to further safeguard patients by requiring companies to take more comprehensive steps to assess and monitor the benefit-risk balance of their products.

This is the second in a three-part blog series on National Pharmacovigilance systems and the role of technology in bridging the gaps in pharmacovigilance of regulatory authorities around the world.

For many companies, signal detection in drug safety pharmacovigilance ranks closely behind regulatory submissions and case management as a key activity because it helps to proactively monitor a product’s risks that come to light from tracking the data submitted to internal and external drug safety databases and platforms.

ArisGlobal has created an Automation in Pharmacovigilance Knowledge Hub to help explain, in easily digestible terms, everything you need to know about automation in PV.

How far along are you in realizing benefits from automation? What is the biggest hindrance in adopting automation technologies? This two-part blog series analyzes polling responses from a recent DIA webinar and shares ArisGlobal’s thoughts on practical use cases for automation in pharmacovigilance and regulatory.

What is the greatest challenge across end-to-end pharma processes? How would you rate your automation capabilities? This two-part blog series analyzes attendee polling responses from a recent DIA webinar and shares ArisGlobal’s thinking about practical use cases for automation in pharmacovigilance and regulatory.