As the technology becomes more ingrained within the Pharma industry’s processes, experts believe that regulation covering the use of AI is coming.
While the technology has been around for several years now, 2023 is the year the AI became a mainstream topic. For the general public, the conversation focused on generative AI, or programs that can generate responses, images, and videos based on user prompts. For the life sciences industry, however, the use of this technology goes beyond that.
In 2023, pharma companies fully embraced the used of AI, both in generative form and as highly complex data sorting algorithms. These programs were implemented across the spectrum of the industry, being included as part of the process from everything to marketing, drug development, and even finding patients for clinical trials.
Scott Snyder, chief digital officer at EVERSANA, spoke with Pharmaceutical Executive about a variety of technology trends he sees for 2024. Regarding AI, he says, “As the calendar turns to 2024, there’s a technological revolution ahead that will continue to change how companies work and are structured. Next year will further shape the future of healthcare and demand a reevaluation of customer experiences as well as business and operating models to capture the full benefits.”
Robert Wells, a healthcare regulatory attorney and shareholder at Baker Donelson, also spoke with Pharmaceutical Executive about AI, focusing on how regulatory concerns may impact the coming years.
“We have seen a lot of consideration of practical uses of AI, both from a drug development and commercialization strategy point of view (with our focus being on the latter),” says Wells. “We’ve also seen considerations related to some equity issues in connection with identifying potential trial patients. Like most people in the industry, we expect for there to be some FDA regulatory guidance around using AI tools and what limitations should be in place for how they can be used and controlled.”
Wells does note that while he optimistically hopes that the regulatory guidance will come this year, he realistically expects it take longer. Part of the issue, according to him, is that the technology and the way that it’s used is so complex and constantly evolving that developing comprehensive regulations can be difficult. At the very least, he does expect there to be significant progress for what the regulatory environment will look like by the end of the year.
“I would expect that the regulatory framework around AI would put some limitations on the utilization of the technology related to the exercise of clinical judgement,” he says. “For devices that are used that cross over into making these judgements, I would expect that the FDA will come up with a scheme to regulate that and get prior approval for those types of tools, similar to what is done with other diagnostic tools.”
He also expects to see growing or increased regulation related to cybersecurity and privacy. As the industry becomes more and more digitized, more patient data is being used to feed AI algorithms. While this creates a lot of opportunity, it also creates a risk that patient privacy may be violated.
“Cybersecurity and privacy are important for patient safety,” Wells says. “The patients should know how information they provide is being used as part of an aggregated database, and if it’s used to generate AI. It’s going to be important that they know that whatever information is provided is appropriately disclosed and protected.”
Wells explains that there could be some concern that AI could be used to make treatment decisions, which would fall under the regulatory umbrella of fraud and abuse. These types of decisions could potentially be used to stop or limit care or access to medication.
“I don’t expect the adoption of AI to slow down in the coming year,” Wells says. “It appears that big pharma is investing even more in AI. I expect the adoption and utilization of AI products in the life sciences to increase, especially using AI to better measurewhat products are being used who they are being used for, and who is using the products to facilitate the marketing and commercialization of products.”
The use of AI and machine learning has allowed the pharma industry to gain more control over its data. AI allows people working in the industry to manage this data in ways that makes it easier to sort and find the relevant info they need. In the coming year, it’s likely the pharma companies will continue to add AI to whatever processes that can benefit from it. As such, this will likely lead to regulatory agencies providing guidance over how and when AI can be used.