Novartis made headlines in 2019 when it armed its sales force with an AI-driven service to tell sales reps which doctors they should visit and what topics they should bring up once they got through the door.
When the pandemic hit in 2020 and reps couldn’t see doctors face-to-face, many more pharma marketers turned to AI to help their brands get noticed by the right doctors at the ideal moment.
Industry watchers see no signs of that stopping in 2022. But they also see pharma marketers branching out into new areas. Experts expect more pharma companies will experiment with using AI and machine learning to do everything from nurturing patient relationships to weeding out content that could raise eyebrows with regulators. Companies may even look to machines to write some of their promotional copy.
Research by Salesforce shows 84% of marketers across all industries were using some form of AI by the end of 2020, a percentage likely to grow in the coming year, Ari Schaefer, co-president of pharma communications agency Klick Health, said in an email interview.
Of course, privacy concerns and the sensitive nature of marketing products to real people with real diseases makes it a lot tricker than, say, Nike using AI to sell a pair of sneakers on Amazon. Still, pharma comms experts expect more drugmakers—and not just deep-pocketed Big Pharma—to follow other consumer industries and wade deeper into AI to boost their brands in the coming year, as the technology matures and gets cheaper.
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Schaefer said Klick has been helping many clients “test and learn” new uses for AI while working with others to roll out full-blown programs.
Chatbots are one AI application he expects more pharma marketers will adopt in 2022. While automated helpers on branded websites are nothing new—Novo Nordisk debuted its digital concierge chatbot Sophia back in 2018—they’re becoming more mainstream, and Schafer expects they’ll continue to improve in 2022.
Not only will they appear more human, but they’ll have better coordination with other services like telemedicine appointment scheduling and tools to help patients find pharmacies or specialists, he said.
Beyond chatbots, Schaefer and others point to three AI uses that should be on pharma marketers’ radar in the coming year: content creation, audience targeting and compliance automation.
While the thought of a copy-writing robot may rankle creative types, Schaefer said companies have begun using AI to generate some of their more routine promotional material like personalized email subject lines.
“Applying this type of technology to pharma marketing won’t replace the need for talented copywriters but can extend brand budgets,” he said, and get marketers “ever-closer to the holy grail of a truly one-to-one marketing program scaled to an entire HCP or patient database.” The pandemic pushed pharma marketers closer to that one-to-one goal with HCPs, noted Andrea Palmer, president of Publicis Health Media.
But, Palmer added, fewer marketers are harnessing AI’s potential to engage with patients. “I think that’s where you’re going to see a lot more growth.”
It’s not enough for pharma companies to know who a patient or doctor is based on what they’ve done or “what some mechanical engine full of data” says they might do in the future, Palmer noted. “They need to really use that to make intelligent decisions about content strategy and content engagement.”
That creates an opportunity to not only find new patients but also to build relationships with existing ones, Palmer explained. For example, a patient in the middle of cancer treatment might welcome information about a drugmaker’s patient support program or tips for managing side effects from an IV infusion—even though that kind of messaging may not appeal to the masses in a broad marketing campaign.
But it’s a “delicate dance,” acknowledges Mike Rousselle, vice president of data product for digital health company OptimizeRX, which specializes in HCP marketing at the point of care.
“We’re dealing with people’s health, and the stakes are so much higher than shopping on Amazon,” he said. However, he said with good controls to protect privacy and respect the doctor-patient relationship, patients can benefit from the kind of AI-driven personalized marketing that’s common in other industries.
His company, for example, has been working with rare disease drugmakers to identify patients who may be eligible for specialty meds, using AI to find predictive patterns in reams of de-identified insurance claims data.
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One client is using the technology to find a “very small subset” of patients who have already failed the first- and second-line therapies for a specific rare disease, he said. The company then uses that information to message their HCPs.
“The way I think about it is we’re scaling the amount of possible surface area for these life-saving therapies to help,” said Rousselle. “We’re identifying patients who, without the AI, maybe never would have been identified.”
The recent push toward more customized digital marketing has also meant explosive growth in the volume of promotional content, pointing to another promising use for AI—reviewing that content to make sure it’s consistent with the drug’s label and complies with regulatory guidance.
“Folks are looking at how to do that without adding tremendous amounts of additional headcount,” said Nick Cernese, life sciences sector leader for EY Global Consulting.
EY has rolled out a technology it calls Smart Reviewer to automate some of the Medical, Legal and Regulatory (MLR) review process. By having errors flagged earlier in the process, companies can get marketing content out quicker without risking mistakes that can get them in hot water with the FDA, Cernese explained.
Some drug manufacturers may be wary—and rightfully so—about handing over regulatory compliance to a computer. But Cernese says AI aims to enhance, not replace, humans. He likens it to driving a Tesla.
“Tesla will allow you to [automate] certain aspects of the process of driving a car, but it doesn’t mean you can’t be in the car,” he said. “This isn’t to take people completely out of the loop but to automate the more mundane and routine activity to increase capacity.”
Klick’s Schaefer sees a future where pharma companies meld the work of traditional MLR teams with machine learning systems that improve over time—helping them quickly “scale up to thousands or even hundreds of thousands of potential variations of a campaign asset.”
“Simple business rules can limit risk, but using Natural Language Processing (a form of AI that allows machines to comprehend human language) to understand whether a marketing message is compliant to the label and to regulatory guidelines is very possible,” he said.
So what’s the top piece of advice experts have for pharma marketers looking to delve deeper into AI in 2022? Most agree: Figure out a clear use case before you jump in.
“A lot of times we try to get to the solution before we even recognize the problem we’re trying to solve,” PHM’s Palmer said.
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