Artificial intelligence (AI), machine learning, deep learning, natural language processing – in short, cognitive computing, is changing the pharmacovigilance world as we know it. While there’s a lot of talk about how AI will affect jobs, where it will have the most powerful impact is on the quality of work and the speed at which manual tasks can be accomplished. This promises to be a game-changer for pharmacovigilance, decreasing the cost of case reporting and improving data quality to allow area experts to focus on where they 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 reporting can be automated and tackled by AI in a very sophisticated and seamless way. These tasks, for which we have coined the term ‘pharmacodiligence‘ — 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 the adverse event case processing and allowing pharmacovigilance resources to focus on strategic activities, life sciences companies will realize better outcomes. That’s because safety departments can work smarter and faster with reliable data at their fingertips. That, in turn, means more time can be freed up for important activities such as benefit-risk assessment and more resources can be committed to higher human intelligence activities that are vital for the scientific interpretation of patient data.
Automation in Pharmacovigilance Data Processing – Do You Trust Artificial Intelligence?
May 16, 2017