This new-era approach to gain a cutting-edge in drug marketing is fast gathering winds on its sail – the world over and is being accepted as a transformational one, in tandem. It is primarily a two-pronged approach that involves merging or convergence of RWE (real-world evidence) and AI (artificial intelligence) into a unified approach for tasks like healthcare research, drug discovery, and patient care optimization.

However, in the context of this article, the process would involve a perfect synthesis between RWE (Real-World Evidence) and AI (Artificial Intelligence) for achieving a cutting edge in patient-driven marketing. A well-crafted shift to this strategic direction, I reckon, holds immense potential to revolutionize the way pharmaceutical companies connect with patients and build trust in today’s complex market environment.

Provides benefits both to patients and drug companies in equal measure:

Following reasons may give a sense of how this transformational strategic initiative provides benefits both to patients, as well as the drug companies in equal measure, which, consequently, makes this fusion or synthetization is so crucial:

1. Unveiling Deeper Patient Understanding:

• AI-powered insights: AI excels at analyzing vast amounts of RWE data, uncovering hidden patterns and relationships that might escape human analysis. This translates to a deeper understanding of patient journeys, preferences, and unmet needs.

2. Crafting Personalized Engagement:

• Tailored communication: By leveraging RWE and AI, pharma companies can move beyond generic marketing messages. They can tailor their communication to specific patient segments, addressing their unique concerns and delivering relevant information about treatment options.
• Empowering patients: Access to clear, personalized information empowers patients to actively participate in their healthcare decisions. RWE and AI can provide insights into potential benefits and risks, allowing patients to make informed choices alongside their healthcare provider.

3. Optimizing Marketing Strategies:

• Enhanced targeting: Traditional marketing often involves a scattershot approach. RWE and AI enable precise targeting, reaching the right patients with the right message at the right time. This improves marketing ROI and ensures patients receive relevant information about potential treatments.
• Data-driven decisions: By analyzing RWE data, AI can identify trends and predict patient behavior, allowing pharma companies to optimize their marketing strategies and campaigns for maximum impact.

4. Demonstrating Real-World Value:

• Moving beyond clinical trial data: Clinical trial data, while essential, doesn’t always translate perfectly to real-world settings. RWE provides a more holistic picture of drug effectiveness and safety in everyday clinical practice, building trust with patients and healthcare professionals.
• Supporting regulatory approvals: RWE, backed by AI analysis, can provide robust evidence to support regulatory applications for new indications or expanded use of existing drugs.

These are a few reasons why this novel approach is gaining traction across the world.

Some recent global and Indian examples related to the synthesis of RWE & AI in patient-driven drug marketing:

Let me now give just 5 examples each for both global and Indian companies, as available in the public domain, of how pharmaceutical companies are deriving benefits from this process.

Examples from global companies:

1. AstraZeneca: Analyzed RWE data from EHRs to identify subgroups of patients who respond best to their lung cancer drug Tagrisso. This enabled them to target marketing efforts towards these specific groups, leading to increased adoption and sales.

2. Roche: Employed AI to analyze social media data to understand patient sentiment towards their hemophilia drug Hemlibra. This helped them tailor their marketing messages to address patient concerns and anxieties, improving patients’ experience.

3. Pfizer: Leveraged RWE from registries to demonstrate the long-term effectiveness and safety of their pneumococcal vaccine Prevnar13 in older adults. This data supported regulatory approval for a new indication, expanding market reach.

4. Novartis: Utilized AI to analyze large datasets from clinical trials and RWD to predict patient response to their heart failure drug Entresto. This personalized treatment approach improved patient outcomes and reduced hospital readmissions.

5. AbbVie: Used RWE to identify factors influencing physician prescribing behavior for their immunology drug Humira. This data helped to tailor their marketing efforts towards relevant healthcare professionals, enhancing brand awareness and adoption.

These are just a few examples, and the field is constantly evolving. As RWE and AI technologies become more sophisticated, we can expect even more innovative Patient – Centric marketing approaches from global drug companies.

A few examples from domestic Indian companies:

While the use of RWE and AI in patient-driven drug marketing is still at an earlier stage in India compared to global giants. This is mainly due to the relatively nascent stage of adoption in India. As the field evolves, we can expect more examples of innovative applications for greater impact in the future. That said, there are some interesting examples emerging, such as:

1. Sun Pharma: Launched a mobile app called “SunRx” that leverages AI to analyze past medication history and suggest personalized recommendations for over-the-counter (OTC) products. This app uses patient data anonymously and adheres to privacy regulations.

2. Cipla: Partnered with a US-based AI company to develop a platform that analyzes RWE data from patient registries to identify new treatment opportunities for complex diseases like chronic kidney disease. This data will be used to inform future drug development and marketing strategies.

3. Dr. Reddy’s Laboratories: Implemented a pilot program using AI to analyze social media data to understand patient sentiment towards their diabetes medication. This helped them identify key concerns and tailor their communication strategies accordingly.

4. Glenmark Pharmaceuticals: Leveraged RWE data from electronic health records (EHRs) to demonstrate the real-world effectiveness of their respiratory drug Brocacef. This data was used to support regulatory approval for a new indication, expanding market reach.

5. Lupin Limited: Partnered with a healthcare analytics company to analyze claims data and identify patient segments with unmet needs. This data will be used to develop and market targeted solutions for these specific patient groups.

It’s important to acknowledge here that the Indian drug industry faces several challenges in adopting RWE and AI for patient-driven marketing in the country. These include access to high-quality and standardized RWE, scarce availability of skilled professionals for building and implementing industry-oriented AI-based solutions. Besides, the regulatory framework for using RWE data in marketing is still evolving, while robust ethical frameworks and transparent data handling practices are essential for this process to be sustainable.

Conclusion:

Synthesizing RWE and AI in pharmaceutical marketing is not just an option now, but a critical step towards a more Patient-Centric and data-driven approach that benefits both patients and pharmaceutical companies. By addressing the challenges and ensuring ethical practices, this powerful combination can pave the way for a future where patients are empowered partners in their health journeys, and pharmaceutical companies can deliver targeted, effective marketing that truly benefits patients.

By: Tapan J. Ray

Disclaimer: The views/opinions expressed in this article are entirely my own, written in my individual and personal capacity. I do not represent any other person or organization for this opinion.