AI: A Value Advantage? Maximizing Your Brand Outreach

Avinob Roy, Vice President and General Manager, Information Management and Analytics, IQVIA

With the increasing interest in generative artificial intelligence (AI), pharmaceutical and life sciences companies are transforming their outreach strategies across multiple channels to maximize impact. The main goal is to generate data and AI-driven insights that inform educational materials and advanced support programs for healthcare providers (HCPs) and patients. These innovative approaches aim to create more resonant and effective communications compared to traditional methods, which often fail to address unmet HCP needs and, consequently, increase the burden on healthcare systems. The primary aim is to empower HCPs with personalized patient engagement strategies to enhance and expedite improved patient outcomes.

Generative AI, which is a specific subset of AI, employs algorithms to predict and generate new content, such as text, images, or videos, based on patterns learned from large datasets. It can produce realistic and coherent content, making it an invaluable tool for brand teams to create highly engaging materials for both internal and external stakeholders within the healthcare ecosystem.

GIVING HCPs AND PATIENTS WHAT THEY NEED

Generative AI can help brand teams to generate content based on HCP’s content and channel preferences making it hyper-personalized. Such informative content helps HCPs to diagnose patients better and prescribe therapies more appropriately.

However, to unlock the full potential of generative AI, a myriad of data gaps needs to be addressed, and data connections need to be made with proper privacy, security, and governance in place. The goal is to deliver the right personalized content at the right time and drive competitive advantage.

Examples of how generative AI can deliver timely value:

• Identifying HCPs that have soon-to-be diagnosed patients and educating them with content that describes diagnosis protocol, options for patients, as well as product-relevant information.
• Sending HCPs information on new or comparative safety data based on HCP scientific activity around researching product adverse effects and observing a drop in diagnosis or prescription rates.
• Delivering summarized key insights of a publication on new efficacy data from a key opinion leader that is in the HCP peer network due to recent brand-switch activity.
• Presenting information on rebate programs based on local patient demographic data that can hinder affordability of treatment.
• Educate HCPs on patient support programs where there is detection of drop in patient adherence.

Generative AI can also be used to surface HCP insights on-demand, so that teams can be better informed on their engagement and campaign planning and can prioritize activities accordingly to improve clinical and financial outcomes.

These improvements offer a strategic competitive advantage for brands—a critically important objective when competing in a crowded therapeutic space.

BUILDING A CONTENT STRATEGY TO CONTINUOUSLY STRENGTHEN CUSTOMER RELATIONSHIPS

The more value HCPs derive from an engagement, the more likely they are to engage again. It’s not just the content that matters, but also how it’s delivered to ensure that it is informative, digestible, and actionable for HCPs. Generative AI empowers brand teams to create diverse content formats to optimize engagement, including informative emails, text messages, articles, tutorial-style decks, blogs, and more—all enhanced with engaging visuals and empathetic audio/video files. Since generative AI is informed by the latest data, brand teams can continuously evolve their materials to meet the changing needs of HCPs and patients.

However, it’s crucial to consider the needs of HCPs and patients within the context of each phase of the product’s lifecycle. This is particularly beneficial, as the understanding and demand for new disease- and product-specific information will continue to evolve over time. From launch through the adoption cycle, data-driven materials can help HCPs grasp the full value proposition and clinical advantages of the therapy compared to competing brands in the same therapeutic space.

In addition, life sciences companies are increasingly challenged to meet HCPs needs on-demand. One promising solution being explored is the use of AI-enabled chatbots and virtual “medical information assistants” that are equipped with voice or video capabilities. These tools offer real-time, data-driven decision support at the point of care, significantly reducing the time HCPs spend searching for information across various sites and publications.

By consolidating validated, trusted information from sources such as approved regulatory data, published literature,
and clinical guidelines, these assistants streamline access to essential resources.

Moreover, these AI-driven tools can help stakeholders to navigate access and affordability challenges related to prescribed therapies, providing financial and mental health resources, nutritional support, and more. This not only enhances patient care and clinical outcomes but also fosters positive brand sentiment and encourages greater engagement, potentially expanding HCP reach over time.

Generative AI can also be used to train algorithms to produce content that is country- and language-specific. This allows culturally appropriate materials and viable dialogue scripts to be developed for HCPs and patients wherever they are in the world. It can also verify that the generated materials are compliant with prevailing legal, regulatory, and company requirements. This advantage provides enormous efficiency and cost savings during global commercialization efforts.

For brand teams, the objective is to create robust support systems around HCPs and patients, improving adherence,
clinical outcomes, and quality of life for patients managing multiple comorbidities.

Generative AI accelerates the development of these program elements, enhancing the overall effectiveness of biopharma commercialization strategies.

MAKING SENSE OF TODAY’S DATA AVALANCHE

The amount of data associated with an approved therapy is immense and continues to grow over time. As more companies create omnichannel commercialization strategies, the volume and complexity of data becomes exponentially more challenging. Fortunately, generative AI thrives on vast data sets to inform and personalize various deliverables.

1. Generate actionable and hyper-personalized insights to inform engagement and strategy.
2. Automate, augment and enhance activities and workflows to interact with data and insights in intuitive ways to increase productivity and efficiency.
3. Monitor various data sets and provide real-time alerts that can help adjust the tactics over time in response to changing customer needs and preferences.

DON’T OVERLOOK THE NEED FOR CHANGE-MANAGEMENT STRATEGIES AND TRAINING

Whether your brand is just exploring or actively experimenting with generative AI, the effort to embrace and incorporate these new technology capabilities can create challenges in terms of understanding of how it works and what value it brings, acceptance of its role, and more.

To support the effective integration of generative AI into daily practice, biopharma manufacturers should use proven change-management strategies. This commitment, along with support and training from senior management, will enable the organization to anticipate and address important questions, alleviate concerns, and help ensure broader acceptance and a smooth adoption process.

Specifically, companies should:

• Define the roles and responsibilities to coordinate efforts and avoid confusion.
• Start small to demonstrate and validate the value of the approach.
• Define use cases that are aligned to specific and immediate needs of the organization.
• Consider partnering with a third-party partner that can help to integrate generative AI, support change-management strategies, help internal stakeholders manage the learning curve, provide guidance on a measurement framework, and reduce overall risk.

FUTURE MOMENTUM

Forward-thinking biopharma brand teams are embracing generative AI and exploring its capabilities to support HCPs and patients in more targeted and meaningful ways. As innovation, investment, and parallel adoption efforts continue to grow, so will the capabilities of the underlying algorithms.

Over time, the collective industry-wide experience will allow remaining weak links to be identified and rectified while allowing best practices to emerge.

Avinob Roy is Vice President and General Manager, Information Management and Analytics, IQVIA