Using generative AI to rescript pharmaceutical marketing

In the pharmaceutical industry, generative AI is playing a crucial role in redefining the organization’s marketing potential. From accelerating insights to improving first and last-mile content creation and ensuring adherence to medical-legal review, generative AI is making pharma marketers more efficient

Overcoming hesitation and utilizing generative AI in Pharma

Generative artificial intelligence (gen AI) use cases have transformed the way numerous businesses develop content and campaigns. However, its implementation in pharma has been constrained due to previous digital transformation challenges. Even today, many pharma leaders and marketers remain hesitant to adopt generative AI, fearing a significant gap between what is promised and what is actually delivered.

Encouragingly, many pharmaceutical companies are gradually learning from early AI adopters how to effectively integrate generative AI into their workflow. Additionally, strategic collaborations with marketing consulting firms and a deeper understanding of generative AI’s potential to enhance the quality, speed, and productivity of their operations have helped pharma marketers gain increased confidence. The technology offers promising opportunities for streamlining complex regulatory processes and personalizing patient communications at scale. However, identifying the best use-case scenario of generative AI for individual applications still requires careful oversight and strategic implementation planning.

Efficient insight generation with AI

Insights hold the potential for more value generation. However, the progress so far has been experimental. Siloed market research data, quarterly business reviews, surveys, sales force reports from medical representatives engaging with healthcare professionals (HCPs), dashboards and presentations leave marketers wanting for more. These manual processes are often slow, expensive and prone to human bias. With vast amounts of structured and unstructured data at their disposal, pharma companies need professionals to extract actionable insights.

While some organizations are holding steadfast to old methods of insight generation, several others are investing in insight agents and interfaces, which can help them mine insights much faster.

Generative AI models have real-time data processing capabilities, allowing them to process vast amounts of data from multiple sources, such as call center transcriptions, dashboards and qualitative research transcripts to uncover trends and real-time insights.

For instance, gen AI can help analyze brand perception and understand HCP and patient sentiment to identify real-time shifts at the click of a button. Pharma organizations can also integrate their research transcripts and secondary data into these generative AI models and empower their marketing teams to ask the right questions and get real-time answers

Streamlining first-mile content creation.

First-mile content in pharma marketing refers to the process of generating concepts and crafting high-quality, compliant and engaging promotional content that may include brochures, awareness and educational materials and much more.

Traditionally, generating first-mile content has been time and cost consuming, requiring collaborations between medical writers, creative agencies, weeks of reviews, revision, concept and ideation.

AI can revolutionize the landscape by automating and accelerating content creation. Marketers can train models to write creative copy and scientifically accurate marketing materials, cutting down the time and cost significantly.

Beyond brief, through careful prompting, image-generation platforms like Midjourney, DALL·E, and Firefly can also be used to turn concepts into images and sketches, freeing up teams to create first-mile content faster and focus on strategic storytelling.

While agency collaborations remain essential for first-mile content production, refining copy and imagery with AI can help lower costs, which can be reinvested in improving patient outcomes.

Optimizing last-mile content personalization

As pharma organizations are preparing to launch full-scale adoptions, last-mile creative concept ideation becomes increasingly important.

Last mile content refers to the final and most impactful content copy that will reach the end customer. This is also where messaging and creative assets are fine-tuned and personalized to deliver the right message to the right audience.

For example, different global teams may want to capture different variables that are ethically appropriate to their audience group. However, in several cases, the setting or model may not feel culturally appropriate.

Content and creative use cases continue to be a top priority across generative AI in pharma marketing. Several organizations are launching pilots and experimenting with messaging and creatives to be as segment-specific as they can be. Furthermore, AI models can translate and culturally adapt content for different geographies while taking into account the best practices of copyright law and regulatory requirements.

Transforming medical-legal-regulatory review

Medical-legal-regulatory (MLR) review is considered one of the most challenging processes in pharma marketing. However, it’s crucial to ensure marketing and promotional content is accurate, legally sound, maintains ethical standards and scientific accuracy and adheres to regulatory standards before public release. Marketers agree that prioritizing this process is essential to improving efficiency and protecting the integrity and reputation of the organization.

Traditionally, this process has been time-consuming, requiring between a month or two for each promotional asset, and multiple rounds of review by medical, legal and regulatory teams. Not to mention, each instance of personalization and new iteration increased the MLR workload.

Generative AI is revolutionizing MLR by automating first-draft feedback. AI algorithms can analyze potential compliance issues, highlight messaging, identify off-label and risky content and auto-score updates to help identify content that may need a more thorough review.

The future of pharma marketing with generative AI

With improved generative AI models, marketers can also learn from prior regulatory and medical comments and draft messaging and content that aligns with compliance. Thus speeding up approvals and creating a seamless, data-driven compliance process that helps organizations gain a competitive edge.

The buzz around generative AI for pharma marketing is intensifying, especially among marketers who are eager to explore new opportunities. Leaders agree that generative AI is not just a technological upgrade but has the power to improve the pharma marketing processes.

The key lies in prioritizing business-driven use cases, personalization through clear value propositions, redefining partnerships and upskilling and reskilling marketers on generative AI use cases.

The solution for rewriting the script in pharma marketing no longer lies in embracing AI but in how soon. Collaboration with industry leaders and top management consulting firms focusing on healthcare and life sciences continues to refine AI-driven solutions for pharma marketing.