Precision in Pharma Marketing: How AI & ML Helps Overcome Data Latency & Drive Physician Engagement

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Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are undeniably transforming various industries, and the pharmaceutical sector is no exception.  These advancements present unprecedented opportunities to optimize the use of real-world data (RWD) and physician-level data (PLD) for more targeted and effective marketing strategies. As someone deeply invested in the potential of AI, I firmly believe that safely & compliantly integrating these technologies into pharmaceutical marketing is a gamechanger for supporting health outcomes.

The Stale State of Traditional Physician Data

Data goes stale quickly. Physicians retire, die, change names because of marriage or divorce, join other practices, get sanctioned — in other words — change is constant and inevitable. When pharma marketers define an NPI physician target list, using RWD, the data is outdated from the moment it is compiled.

RWD can be anywhere from four to twelve weeks old by the time it is actionable. This latency combined with an NPI list that may not change for six months or more, will minimize the effectiveness of marketing campaigns, as the accuracy of the data rapidly diminishes over time. As a result, marketers miss opportunities to engage physicians with pertinent and timely information. That’s where the predictive power of AI and ML can measurably change how pharma marketers can execute their campaigns more effectively.

The Future is Now. AI and ML are transforming physician engagement. These technologies offer unparalleled opportunities for more targeted, effective, and efficient marketing strategies.


AI and ML Use Prediction to Combat Latency

AI and ML offer a compelling solution to the data stagnancy challenge, by predicting upcoming care events based on the clinical milestones of a patient population. This sets the stage for more effective messaging to your ideal prescribers. These technologies can be designed to identify patterns and trends within the clinical landscape which are meaningful to a specific brand’s objective that would be impossible for humans to discern at scale, or predict manually using pre-staged user journeys. This predictive element enables us humans to mock out the impossible scenario of having RWD in real-time, making it an invaluable asset for pharma marketing.

Predictive targeting is one of the most promising applications of AI in this context. By leveraging an AI-based solution, marketers can anticipate patient eligibility for specific treatments and time and tailor their messaging accordingly. This removes the need to rely on media platform “triggers,” such as native EMR data, or look-alike audiences to deliver relevant content.   

OptimizeRx developed an AI platform for this very reason. We use longitudinal medical claims and prescriber data to prioritize physicians for outreach based on relevant patient care events or care windows. We’re seeing our clients significantly improve the ability to deliver more personalized messages to healthcare providers at more opportune times and when it is most relevant to their patients' needs.

Dynamic Targeting and Continuous Learning  

A compelling advantage of AI and ML is their ability to facilitate dynamic targeting. Unlike traditional methods that rely on unchanging, or static, NPI lists, AI-powered systems are continuously learning and adapting, improving data quality over time.

Additionally, AI can integrate data from diverse sources, such as electronic health records, physician feedback, and social media interactions, which can provide an even more comprehensive view of physician behavior and patient needs. This approach can enable marketers to develop more effective campaigns that reflect a deeper understanding of the target audience.

The Future of Pharmaceutical Marketing: A Transformation Powered by AI and ML  

The integration of AI and ML into pharma marketing to predict contextual content delivery represents a significant shift in how physician data is utilized. These technologies offer unparalleled opportunities for more targeted, effective, and efficient marketing strategies. Pharma marketers who embrace AI and ML will be better positioned to navigate the complex healthcare landscape and drive meaningful engagement with their target audiences. 

As we continue to witness the digital transformation of the pharmaceutical industry, staying informed about the latest technological advancements is essential. As we unlock and connect more intelligence about our clinical audiences, we’ll get smarter and smarter about how and when to engage. AI and ML have driven us many steps forward as an industry and pharma marketers can now unlock new levels of precision and personalization, ultimately leading to more successful outcomes.