In today’s challenging economic climate, every company is tasked with achieving more with limited resources. During this timely roundtable discussion, The Coming AI-Enabled Pharma Revolution, sponsored by Boundless Life Sciences Group, industry leaders explored the transformative potential of AI to enhance clinical and commercial processes, boost productivity, maximize ROI and ultimately improve the lives of patients.

As AI becomes smarter and more applicable to many sides of the business, the experts on the panel evaluated how the industry has embraced analytics and discussed how they are utilizing AI and ML in their marcomms and sales practices.

Pharma marketers aren’t lacking in the right tools or skills, but a mindset shift is required to use data to drive business decisions. Smaller biotech and startup pharma companies, panelists felt, have been quicker to embrace analytics because they can build their systems from the ground up. They also agreed that the newness of the technology can scare off many marketers who have grown accustomed to operating a specific way in a conservative industry.

Buy-in from C-suite is key

A critical hurdle that needs to be overcome is educating the C-suite on what can be accomplished with more sophisticated AI and ML tools. “In pharma, there’s a strong desire to have an ROI with everything you’re investing in,” noted Adam Remiszewski, associate director, regulatory affairs at AbbVie. “For AI, it’s hard to prove the ROI and to get senior management to see the value in it. That’s the biggest impediment to invest in AI.”

Curren Katz, head of strategic business transformation at Johnson & Johnson, added that management’s primary interest is in what technology can do for the business and how its success can be measured. The ability to truly show what AI can achieve can go a long way in winning C-suite support. While utilizing AI can be expensive, leadership is more likely to make a commitment when they have the assurance from marcomms that the results will amplify the business and a commitment to produce concrete results.

Too often, noted Tim O’Sullivan, CEO of Boundless AI, companies set a KPI without truly defining metrics to measure performance. “Those measurements are critical,” he said. Boundless has improved its dashboards to demonstrate that the cost to implement will generate additional dollars in revenue or script volume as well as efficiency gains within the actual operation. Francesco Lucarelli, chief commercial officer of Boundless Life Sciences Group, calls the approach “a bifurcated ROI.”

At Novo Nordisk, Corinne Yaouanq-Lyngberg, senior director, NextGen capability enablement, started small, then showcased her team’s achievements to get broader buy-in. “Leadership wanted us to start small and prove it was going to work. We had measurements for every milestone so we could prove we met the criteria of measurements we had agreed on. Then we could scale up. We were lucky enough to show financial return, not just savings.”

Remiszewski and AbbVie colleague Shakshi Kshatriya, associate director, regulatory U.S. advertising and promotion, digital and corporate communications, devised an education series to teach other functions how technology can help grow brands. “Marketing leadership was very excited from the top down because they’ve been hungry for anything to help save costs and get some behaviors and practices in motion,” said Kshatriya. Convincing the sales function, she noted, has been more of a challenge.

That has not been the case at Novo Nordisk, where Yaouanq-Lyngberg indicated that field sales teams are open to the benefits of AI. “They realize, especially since COVID, that they can’t always access physicians and they understand that customers consume content via digital channels,” she said. “We’re focused on giving them insights they couldn’t find on their own.”

Pulling key field salespeople into the process early on is one way to increase buy-in, noted Katz. O’Sullivan added that any intelligence marcomms can provide sales reps on how to improve their conversations or touchpoints with HCPs is also valuable data.

“If you’re able to show how AI or ML can tie together NPP based on preferences or even let reps put their appointments in the calendar, it all ties together to orchestrate the end experience,” said Amy Turnquist, principal at North Highland. “Breaking down those data silos and making data more easily accessible makes it less scary for the sales teams to consume this data quicker,” noted Yash Gad, CEO of Ringer Sciences.

Barriers remain

While company investment in AI/ML is clearly growing, there are still numerous hurdles in operationalizing this technology. Panelists detailed the opportunities — and challenges — of integrating AI/ML into marketing, sales, med affairs and clinical-trial marketing.

AI-generated content often gets pushback on both the creative and regulatory fronts. While O’Sullivan stressed that marcomms pros would not be using an AI engine to develop a core messaging campaign, he said using the technology to personalize messaging to several different audience segments is a huge acceleration in efficiency. “You can start optimizing your materials very quickly and have a robust omni channel marketing structure,” he said.

Having that conversation with creative isn’t something marcomms pros relish. “A lot of agencies and marketers are afraid of AI because they fear losing control of the creative,” said Remiszewski. “There’s a lot of misunderstandings around how it can be used even though most of us are already using it in some way.”

“Introducing AI into their lexicon or habit building has been challenging, because they think of the tools as limiting,” admitted Kshatriya.

Panelists conceded that the regulation and compliance aspects of AI generated content is also a stumbling block. “We don’t understand the legalities around this yet. We’re protective about the strategies we inculcate into our organization,” said Kshatriya.

While panelists saw opportunities in using AI to capture HCP and patient data, they are also concerned about commoditization and privacy issues associated with captured data. “We’re seeing more asks for siloed, completely in-house solutions,” said Gad. “It lets companies completely control all the data within their infrastructure. We’re probably going to see more of that rather than vendors where you can park your data. It’s more tailored and you can skirt a lot of those regulations because you’re not letting the data out of your system.”

A conservative industry mindset is also a barrier. “We have a great technology stack, but somewhat  traditional mindset,” said Yaouanq-Lyngberg. Rather than having a minimal data science team and a behemoth marketing department, Remiszewski believes pharma should rethink the investment in skill sets. “Having people looking at data specifically for each brand is what you really need. You can create content, but if you don’t understand what’s actually performing well, you can’t create the most value for your company,” he said.

Campaigns have become much more targeted and AI makes that segmentation easier to accomplish. “It’s about being more agile in that journey,” said David Pierpont, co-CEO, RocketSauce Media Labs. “We used to go out with the perfect campaign. Now it’s all those pieces of content and we have to figure out where they are in the journey and what may be missing from that messaging.”

“Tracking these things in real time pays off. It holds everyone accountable and starts to paint a picture of real-time information and a team that’s iterative,” continued Katz. “When you get into that mindset and make that initial investment, you start iterating on data reporting. When you put it all in place, you can explore more,” added Pierpont.

Marketers also talked about how they want to be using AI in the next three years. “There’s so much opportunity to improve on clinical trial design, from expediting design to trial setup and site training,” said Lucarelli.

One of Kshatriya’s goals is to better understand AbbVie’s stack. “We have so much available to us, but only 10% is being tapped. Our goal as a digital transformation team and regulatory team is to be a conduit between commercial aspects and bandwidth,” she said.

“We rebuilt the capability and competency model for the marketing team and field team to help upskill them for data driven decision making,” added Turnquist. “We’re trying to change the mindsets and behaviors and skill set first and hopefully raise the tide.”