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Practical Use Cases of Automation in Pharmacovigilance and Regulatory E-2-E Productivity: Part 2 of 2: How Far Along the Road Are You in Realizing Benefits from Automation in Safety? In Your Organization, Which Areas Would Create Maximum Value?

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.

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Practical Use Cases of Automation in Pharmacovigilance and Regulatory E-2-E Productivity – Part 1 of 2: What Is Your Greatest Challenge Across the E-2-E Process? How Would You Rate Your Automation Capabilities?

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.

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Extracting Safety Signals from Social Media through Artificial Intelligence

Whether companies like it or not, consumers are discussing their products in social media forums. Comments about adverse events exist on patient forums, and on more generic social forums such as Facebook and Twitter. While much of what is said is not relevant or verifiable, there are safety signals that companies should be paying attention to, and that go to the heart of pharmacovigilance and social media.

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Lifting the Tedium of Medical Literature Monitoring with Automation

One of the key roles of pharmacovigilance departments is to understand the benefit-risk profile of a drug. But departments are often bogged down by manual tasks that can absorb time, which might be better spent on value-centric activities. Perhaps the most tedious pharmacovigilance activity is medical literature monitoring (MLM), and as we discussed in our last blog, manual, repetitive tasks are a primary cause of employee dissatisfaction.

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