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September 21, 2018
Automation, AI and Analytics are key to enhancing pharmacovigilance processes and improving patient safety
By: April Davis

Over the past several years, pharmaceutical and biotech companies have paid increasing attention to pharmacovigilance (PV)—the practice of monitoring the safety of drugs and prevention of adverse effects on patients. Companies across the industry have invested in proofs of concept and seen firsthand the value PV can bring to the broader R&D organization, as well as bringing insights into patient safety data. The next step is to understand how to apply the lessons learned, and at scale.

At a recent PV Automation roundtable hosted by Accenture, attendees from a number of pharma companies shared their experiences and insights, and discussed their aspirations for the coming year. They spoke of:

  • Their desire for cross-company alignment to move to the new and pivot to the patient.
  • Their requirement for a high quality, cost effective PV solution that would enable to them to work with multiple vendors.
  • The key importance of cost containment paired with developing a solid value proposition for stakeholders.
  • Their desire to engage with regulators to ensure compliance.
  • Their current efforts in automation, artificial intelligence (AI) and robotic process automation (RPA), or their thinking about first steps.

A common theme was their desire to converge across clinical and safety by data and organizationally, with a prioritization on case intake, language translation and patient support programs. Other PV imperatives included:

  • More effective and efficient operations.
  • Increased focus on safety science and insight.
  • Increased value for stakeholders.

The biggest challenge companies face in their PV journey is around the regulatory impact on data and how to satisfy regulatory requirements. Keeping patient data safe is of utmost importance. But validation and ethical concerns, particularly when companies use automation and AI, is also critical, and one of the reasons companies have been hesitant to pursue these technologies more vigorously.

However, the attendees see automation and AI as a priority if they are to make progress on surveillance and apply advanced digitization earlier in the PV process. Real-time AI, machine learning and advanced operational and scientific analytics need to be embedded in each step of the PV process—from case intake, case processing, follow-up, medical review and quality review, to regulatory reporting and distribution.

For companies that want to understand and manage the risks of new products better and earlier, automation of pharmacovigilance processes could enable them to focus more attention on product safety and patient outcomes, engage with regulators more effectively and enhance profitability.

If you would like to learn how Accenture supports companies in their PV automation efforts, or you are interested in attending a future roundtable, please contact me directly to learn about the PV services we offer.

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