AI in Pharma Communications: Real-World Success Stories and Advanced Applications*
Terry Levi
Digital Transformation | Customer Engagement | Customer Experience | Commercial Excellence | Pharmaceutical | AI | AI Strategy
The pharmaceutical industry is beginning to realise the transformative power of artificial intelligence (AI) in enhancing customer engagement1. In the first article, we explored basic AI applications, such as using generative AI for content creation and data analysis. Here we explore more advanced, practical use cases that can enhance marketing and medical affairs activities, streamline operations, and unlock new levels of efficiency and engagement. From facilitating project retrospectives to AI-generated multimedia content, our goal is to inspire pharmaceutical professionals to experiment with these tools and integrate them into their workflows.
From Basics to Breakthroughs: How AI utilisation is evolving in Pharma
While early AI applications have centred on improving efficiency and automating repetitive tasks, there is great potential in its ability to tackle more complex problems. Advanced AI applications can deliver remarkable value for the pharmaceutical industry. Let’s dive into some examples of how AI is being leveraged in more advanced and impactful ways2.
?1. AI Video Avatars for realism and engagement
One of the most exciting developments in AI (though also one of the scariest for those concerned about “deep fakes”) is the ability to create lifelike video avatars. Tools like Synthesia can quickly generate video content, such as patient stories and simulated doctor-patient conversations3. These avatars bring a level of realism to educational content that static media simply cannot achieve. For example, patients can describe their experiences with a condition or treatment, creating a more engaging and relatable case study format.
An even more advanced use case is the creation of personal video avatars for (Digital) External Experts. An external expert can be filmed once, and with their permission, their avatar can be generated to deliver content in multiple languages. This capability is particularly useful when updates or modifications are needed, as changes can be made quickly without the need for re-filming. AI can also assist with script translation, while in-house native speakers review the results to ensure we maintain a "human in the loop" approach, combining the strengths of both AI and human expertise.
Why It Matters: This approach not only enhances audience engagement but also simplifies the process of updating content, making it faster and more cost-effective, especially in multilingual settings. It also ensures the delivery of consistent messaging across markets, with the ability to swap out avatars for more culturally appropriate personas.
?2. Generative AI for Project Retrospectives and Process Optimisation
Managing projects effectively and efficiently is crucial in pharma marketing and medical affairs, and AI can make a significant difference here. Generative AI can streamline the project retrospective process by helping teams reflect on their successes and areas for improvement4.?
Tools such as Microsoft’s CoPilot allows teams to record and analyse retrospective meetings, automatically summarising key points and extracting actions to drive improvement. This functionality ensures that no critical information is lost and that teams have a structured process of reflection to drive continuous improvement. ChatGPT can analyse transcripts of your meetings to generate visual aids such as word clouds to represent the discussion, and can even suggest improvements based on patterns in previous projects.
Why It Matters: By facilitating a process of continuous improvement, generative AI can lead to better project outcomes and more efficient use of time and resources. The ability to automate meeting documentation and provide data-driven insights ensures that retrospectives become a powerful tool for enhancing productivity and collaboration5.
?3. Text-to-Audio for Multilingual Narration
With the global reach of the pharmaceutical industry, communicating in multiple languages is essential. AI-driven text-to-audio tools, such as Transperfect’s GlobalLink, enable the rapid creation of narrated content in various languages. This is particularly useful for educational materials, whether aimed at healthcare professionals (HCPs) or patients.
For example, written product instructions can be quickly converted into a narration, and simultaneously translated into different languages, increasing accessibility and ensuring a wider reach for educational and medical information initiatives.
Why It Matters: The ability to create multilingual audio content swiftly and accurately makes this a valuable tool for global campaigns and ensures that critical information reaches non-English speaking audiences without delay.
?4. AI-Generated Images for Ideation and Design
In marketing, ideation is an essential process, and tools like Open AI’s DALL-E 3 offer a quick way to generate image concepts and mood boards. These AI-generated visuals can serve as high-level concepts that can kick start the creative process or serve as a template for designers to further refine. For example, in the early stages of a campaign, teams can use AI to produce multiple design ideas, saving time and helping to narrow down creative options.
Why It Matters: By accelerating the ideation phase, AI tools enable marketers to quickly translate written briefs to visual outputs, allowing creative teams to focus on refining ideas and executing high-quality designs.
Challenges and Practical Considerations
While AI offers immense potential, there are important legal and ethical considerations that pharmaceutical companies must navigate. The intellectual property ownership rights of AI generated content remain unclear and data privacy issues are especially important in an industry handling sensitive patient and clinical data. AI content is also prone to include “hallucinations” - unfactual, made-up statements as well as reflect human biases. For example, images generated using AI tools often reflect common gender and race stereotypes. Ensuring that AI-generated is accurate and adheres to legal and regulatory standards is essential.
Another important consideration is the way in which AI companies utilise user inputs. Users should avoid uploading any confidential information into the free generative AI engines as these may be used to train the models and could result in confidential information being exposed to other users6. Paid and enterprise accounts usually provide sandboxed environments where user input content is not uploaded into publicly available datasets but you should always check how your data will be used.
For these reasons, it is essential that pharma companies implement and train their employees on Standard Operating Procedures (SOPs) for AI use. Companies should also consider setting up AI Ethics Committees to review AI-generated content, ensuring transparency and ethical standards are met.
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Real-World Examples of AI in Action
Companies like Pfizer are leading the way in AI adoption. Pfizer’s Charlie platform integrates generative AI into the creation and review of marketing content. This includes using AI for content editing, regulatory reviews, and message segmentation, all of which improve the speed and accuracy of their marketing processes.
Similarly, Novo Nordisk has utilised AI for email marketing, achieving a 24% higher open rate through the optimisation of messaging with AI-powered brand language technology.
Why It Matters: These examples demonstrate that AI is already driving substantial improvements in efficiency and engagement for leading pharmaceutical companies. AI tools are not just theoretical—they are delivering tangible results today.
Conclusion: Start Your AI Journey Today
AI offers a wealth of opportunity to revolutionise pharmaceutical communications. From generating engaging video content to streamlining project management, the potential for AI to drive efficiency and creativity is vast.?
Now is the time to start exploring how these tools can transform your work. While the technology may seem overwhelming to some, you can start with small, manageable steps in a controlled way. For instance, try using AI-generated video avatars to present some content for an internal training programme you are developing or utilise text-to-audio tools to convert a briefing email to the field teams into an audio announcement.? As Sam Pygall, Regional IT lead at MSD says, “We can only really understand the impactful use cases through rapid implementation and experimentation”.
References:
Contributing Authors:
David Logue, Partner, Life Sciences, Baringa Partners
Chris Finch, Vice President, Earthware Limited
Richard Lucas, Innovation Director at Tangent90
James Turnball, Founder of Camino
Sam Pygall, Regional IT Lead @ MSD
*Generative AI was used as part of the process of creating this article, building on the strengths of human and AI collaboration.
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MD; Associate Consultant at Prime Access
3 周Thanks for sharing, Terry! Great to see some real-world examples with positive outcomes. I’m especially interested in more insights on how AI impacts engagement across different stakeholders and whether these effects carry over to various content formats.
Emerging Markets Integrated Agency Team Lead at Publicis Groupe
3 周Great article. As you highlight, once the IP questions are resolved, we can start to unlock the capabilities that already exist. Exciting times.
Digital Creative Agency Leader | Medical Communications | Omnichannel Strategy | Digital Solutions | Healthcare Innovation
3 周Thanks for sharing Terry Levi. It was fun working on this with you and the team! Having spent a fair bit of time experimenting with AI video tools like Synthesia I have to say I've been impressed by how mature they already are. AI speech has already evolved hugely from where it was and it's now really hard to distinguish AI generated voice from a real one! I think this presents a significant opportunity for the industry to product multi-language video content, using culturally appropriate avatars for content like educational case studies.