Holding Pharma Tech to the Highest Possible Standards

This article is part of solli’s September series exploring The Effective Use of AI in Pharma Media.

Think about the last time you or a loved one was seriously sick. 

Maybe it started with an ache or a pain that you couldn’t quite explain. You searched the internet for answers. Perhaps you used AI tools such as Claude or ChatGPT to delve deeper. A friend or family member encouraged you to see a doctor. Your doctor ordered a test and referred you to a specialist, and eventually treatment was prescribed. In the midst of all that was the insurance process, including coverage checks and authorizations. 

That was one patient’s journey. Another patient with the same symptoms might experience an entirely different sequence of research, tests, physicians, treatments and access hurdles. 

It’s that complexity and variability— often involving multiple healthcare providers, caregivers, and other influencers— that makes healthcare marketing so distinct from, say, consumer packaged goods or autos. 

It’s also what makes data so important. Pharmaceutical marketers have historically used a relatively narrow set of signals to understand this highly complex journey, most notably medical and pharmacy claims data. But that’s only one part of the patient journey, albeit an important one. 

Claims data may tell a marketer that a diagnosis occurred. It may not shed any light on the symptoms and tests that preceded the diagnosis. It doesn’t highlight the clinical questions a physician was trying to answer. It doesn’t necessarily reveal the biomarkers that ultimately determine which therapy is likely to be successful. And it doesn’t tell the full story of what happens after a prescription is written—including whether the patient’s insurance covers the treatment, whether a prior authorization is required or whether the patient ultimately gains access to prescribed treatment. These distinctions matter. 

A New Age of Pharma Brings New Challenges 

AI is helping pharma companies develop increasingly precise treatments. Treatment precision means we can both address conditions that have long lacked research investment as well as prescribe combinations of therapies that can be more and more customized to specific patient groups.  

And that’s fantastic news for all of us. Our ability to manage and treat conditions successfully is only going to improve in the years ahead because of this innovation. 

But marketing drugs that treat smaller patient populations makes the marketer’s job even more challenging. In order for precision medicine to be successful, marketers must be able to raise awareness of treatments among audiences that are harder to find and reach. If they can’t reach the patients and healthcare providers who can most benefit from medical research breakthroughs, the treatment may not be successful in market. Even today, this happens with more than 60% of new treatments entering the market.  

At the same time, pharma marketing is governed by a very strict and ever-evolving compliance framework that protects individual privacy. And rightly so: healthcare data is extraordinarily sensitive and personal, and patients should not have to sacrifice privacy in order for the healthcare system to become more intelligent or personalized. 

So, the goal for pharma marketers is to understand and use data that is relevant, reliable, timely and appropriately governed—and to connect those signals in ways that produce meaningful insight—without compromising individual privacy. That’s all done in service of giving therapies and treatments the best chance of success in market, so those who need them and prescribe them are aware of them. 

Leveling Up Precision with Compliance 

The process of deriving useful, population-level insights from appropriately governed and de-identified data while maintaining strong controls around how information is used requires rigor at every stage. It means strong controls around the provenance of the data, how it is stripped of any personal information, what inferences are made and how privacy is protected at every step. 

As AI transforms the pharma marketing and commercialization workflow, in the same way that it is transforming the research and development workflow, we need to ensure we are not simply slapping AI interfaces onto datasets without the appropriate safeguards. An AI system can only be as useful as the data, logic and safeguards behind it. And for healthcare, these emerging commercial platforms need to be held to an even higher standard. 

The industry approach to this has been built around connecting high-quality data to the marketing value chain, historically by integrating a relatively narrow set of trusted currencies centered on claims. The architecture that precision medicine requires goes further, bringing first- and third-party media, biomarker and access signals alongside claims and making them usable for planning, targeting, activation and optimization inside a privacy-safe, HIPAA-compliant framework. 

Governance has to be engineered into that architecture at every step. In practice, that means data is de-identified before it reaches the platform and certified by independent experts as statistically low-risk under HIPAA and applicable state requirements. It means audiences are scored on safe consumer attributes rather than on diagnosis, so no health attribute is ever assigned to an individual and no inferred health data is created in the course of building a campaign. That is the standard we’ve worked toward in building DeepIntent’s trusted technology architecture, DeepIntent Helix data cloud, and it’s the standard pharma marketers should hold any technology partner to. 

As pharma marketers embrace the full power of AI and data-driven decision-making, more technology partners are coming forward with agentic solutions to help them. These innovations will be essential in driving precision marketing, but marketers need to ensure these innovations meet the unique requirements of the pharma industry, particularly around the rigorous protection of consumer data. 

The objective should not be to know everything about a specific patient. It should be to understand the healthcare ecosystem accurately enough to get more life-changing treatments into market successfully, while responsibly enough to protect privacy. 

We need to make sure we are holding the industry to these very high standards—not just meeting current compliance standards, but always striving to exceed them. It’s only in this way that we’ll continue to build provider and consumer trust in a way that will help bring more essential treatments to market successfully.  

This guest commentary piece was written by Natalie Mancuso, SVP, Data Partnerships, DeepIntent