Automation in Pharmacovigilance
PV Automation
Pharmacovigilance (PV) is the function in drug development that ensures safe and high-quality medicinal products are released to the market. The World Health Organization describes how PV achieves this through “the science and activities relating to the detection, assessment, understanding, and prevention of adverse effects or any other drug-related problem.”
Though specific PV processes can vary from organization to organization, there are global requirements that must be addressed, including signal detection, risk management, adverse event reporting, and other activities. Some of these processes create repetitive, manual tasks, which often are not only time-consuming but also extremely costly for the organization.
Utilizing automation technologies – including natural language processing and machine learning – to streamline manual PV processes enables organizations to realize greater efficiency, while freeing up precious resources to allow drug safety teams to focus on higher order tasks.
What is Pharmacovigilance Automation?
Automation includes everything from basic rule-based automation to more advanced levels including artificial intelligence (AI), machine learning (ML), deep learning, natural language processing. In short, cognitive computing, is changing the pharmacovigilance world as we know it. Every day, more organizations are realizing the powerful impact PV automation can have on the quality of work and the speed at which manual tasks are automated.
As its use cases further develop, automation promises to be a game-changer in pharmacovigilance. By decreasing the cost of case processing and improving data quality, automation allows PV experts to focus on areas where they can truly add value, including; signal detection in drug safety, pharmacovigilance analytics, and benefit-risk assessment.
Repetitive and routine manual tasks such as adverse event case intake and data entry can be automated and tackled by AI in a sophisticated and seamless way. These tasks, for which we have coined the term “pharmacovigilance” – in other words, the due diligence of collecting and processing data – are not strategic in the same way as activities such as benefit-risk assessment.
By building AI into adverse event case processing (focused on tasks such as automated duplicate check, coding, validity assessment, and triage) and allowing pharmacovigilance resources to focus on strategic activities, life sciences companies can realize better outcomes. That’s because safety departments can work smarter and faster with reliable data at their fingertips.
ArisGlobal’s LifeSphere MultiVigilance is the industry’s first end-to-end safety system with production-ready automation. We’ve developed this solution hand-in-hand with leading life sciences organizations, ensuring that it’s ready to tackle real-world automation use cases out-of-the-box. LifeSphere MultiVigilance leverages cognitive computing technologies such as natural language processing and machine learning and provides a single, global database that supports automation of all adverse event processing.
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