Digital & Technology

Mitigate risk, maximize efficiency: How pharma compliance teams can get started with AI

March 12, 2024 | Article | 3-minute read

Mitigate risk, maximize efficiency: How pharma compliance teams can get started with AI

Automation. Specific business use cases. Operational and ethical challenges. These are just a few topics that arise when pharmaceutical compliance experts discuss how they can leverage AI. As the field increasingly focuses on AI’s risks and opportunities, we recently gathered three industry leaders to talk about how compliance teams can responsibly use this technology. We were joined by Gary Del Vecchio, healthcare compliance officer at Johnson & Johnson Innovative Medicine; Anisa Dhalla, chief ethics and compliance officer at UCB; and Emily Mason, vice president of worldwide compliance and business ethics at Amgen. You can watch the full discussion in the video below and check out these three key takeaways from the session:

1. Focus on the most relevant business cases

AI can affect nearly every area of an organization, making it important for leaders to consider which use cases are most relevant and beneficial for them. As they make these decisions, they should also think about a particular use case’s level of risk. Use cases AI can help with include:

  • Data discovery and classification
  • Audit analytics
  • Generating executive reports
  • Risk monitoring
  • Producing insights from unstructured guidance documents
  • Creating personalized and curated compliance insights

“Using AI to provide personalized and curated insights on what compliance staff needs to know, when they need to know it and ways to deliver information is intriguing,” Mason said. “These insights could essentially act as a personalized navigator.”

Again, compliance organizations shouldn’t expect to use AI to immediately improve each and every one of these processes. Rather than trying to have an outsized, instant impact, focus on using AI where it makes the most sense.


“AI is a broad topic with so many different applications, but people are looking at it as this monolith,” Del Vecchio said. “(To get started), it’s important to take the use cases that have the lowest risk and prioritize them.”

2. Encourage everyone to get involved

AI’s rapid rise to mainstream consciousness, coupled with the regulated nature of the pharmaceutical industry, means there are very few people within compliance organizations who understand generative AI well. That’s why experts in individual areas of application should review potential business use cases, rather than relying on a single governance structure.


Given the cautious nature of many compliance team members, it’s not a surprise some may be apprehensive about using AI in their work. But now is the time for them to experiment and learn how AI can help complete tasks and develop insights.


“It’s important to upskill compliance teams on AI,” Del Vecchio said. "The current bottleneck is knowledge limitation and lacking a true understanding of generative AI, making it important for use cases to be reviewed by experts in individual areas of application.”

3. Choose the right framework for your organization

While AI’s promise is exciting, it does present a new set of challenges and considerations. One of them is which framework to use to evaluate potential use cases and analyze risks. There are many available and choosing the right framework can enable governance committees to weigh risks and rewards to make better decisions faster. Mason shared that Amgen uses a framework for trustworthy AI from the National Institute for Standards and Technology.


“Choosing a framework is a challenging first step, but it will help you determine what the risks are and how you think about them,” Mason said.


Dhalla said she’s excited to see AI’s potential in the coming years.


“We need to lean in and embrace what’s possible, while also making sure we have the confidence and controls in place for successful generative AI implementation,” Dhalla said.


Explore their full discussion below.

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