Artificial Intelligence (AI) is revolutionising various industries, and pharmaceutical marketing is no exception. Generative AI, in particular, offers unprecedented opportunities for marketers to enhance their strategies and drive better outcomes. This article provides a foundational understanding of AI and its practical applications for pharmaceutical marketers, focusing on immediate steps you can take to incorporate AI into your workflows confidently.
What is AI?
AI refers to the simulation of human intelligence in machines programmed to think and learn like humans. Key components of AI include machine learning, natural language processing, and computer vision. These technologies enable machines to process data, recognise patterns, and make decisions1.
AI has for a long time been making significant strides in the pharmaceutical industry, particularly in areas such as drug discovery, clinical trials, and personalised medicine. For instance, AI models like AlphaFold predict protein structures with remarkable accuracy, potentially enhancing safety profiles and creating novel molecules2. Despite these advancements, many other areas of pharma, including marketing, have lagged behind in AI adoption.
In this article, when reference is made to AI, it is generally referring to Generative AI (e.g. ChatGPT, Claude, Gemini, etc). It is assumed that the reader is working for a company which has developed a policy on using GenAI and the reader has a subscription where confidential proprietary information is not being used as training material for the Large Language Model (LLM). It’s important to not upload confidential information/data to public AI tools, so it is strongly recommended only to use a company-approved or enterprise-level tool.
GenAI for Pharmaceutical Marketers
Generative AI offers a myriad of opportunities to enhance efficiency, optimise content, and personalise customer experiences. Understanding and leveraging AI may lead to improved campaign effectiveness and better meet external stakeholder expectations, and ultimately, a competitive edge in the market3.
Generally, there are two broad categories where GenAI might be able to enhance workflows – Customer Experience and Operational Efficiency, and many use cases may fall under these broad headings. Some examples of these are outlined below:
What’s available to start learning about GenAI?
- Understand your company’s technology roadmap: Gain a clear understanding of the AI tools and technologies available within your organisation.
- Educational resources: Use free online resources such as YouTube videos and LinkedIn articles to stay informed about AI use cases.
- Paid courses: There are many courses available which can teach you all you need to know about how to use generative AI.
- Community engagement: Establish forums or communities of practice within your organisation to share insights and experiences with AI.
- Define business problems: Identify specific marketing challenges that AI could help solve.
- Hands-on experience: Engage with AI tools directly. Experiment with writing prompts and exploring the possibilities of prompt engineering.
Immediate Steps for Marketers
Believe it or not, the first step to getting started is to actually login to your company’s GenAI tool and have a play with it with basic prompts like “make a poem for a birthday card using some key facts (name, age, hobbies or a funny fact) about the person who’s birthday it is”. It’s amazing how many people do not take even that simple step forward. In a well known pharmaceutical company which rolled out GenAI across their organisation, even technology professionals are learning about the possibilities presented by the technology. Sam Pygall (IT Regional Lead, Core Europe and Canada, MSD” says “The value can only be understood through gaining practical experiences. My advice is to log on, jump in, have a go, experiment – we can only really understand the really impactful use cases through rapid implementation and experimentation. Only then will the tangible business value be determined,”
Practical Examples
Ideation: GenAI can be a valuable tool for generating ideas for a facilitated workshop. By providing the tool with key details about the workshop’s goals, audience, and subject matter, it can suggest a range of interactive activities, discussion topics, and potential themes that align with your objectives4.
Summarisation: Uploading a document to GenAI can streamline the process of summarising lengthy texts. By simply uploading your document, you enable GenAI to quickly analyse and condense the content, extracting key points and presenting a clear, concise summary5. Do watch out for GenAI tending to be optimistic, hallucinating and excluding important edge cases.
Personalisation: GenAI can be used to create personalised content by analysing individual preferences, writing style, and specific needs to generate tailored text. To enhance this process, you can use the Knowledge Hub within a bespoke GPT to upload specific documents, guidelines, or reference materials3.
Next Steps
In conclusion, marketers in the pharmaceutical industry appear to be lagging behind their counterparts in drug development when it comes to adopting AI. While other disciplines are leveraging AI to drive innovation, marketing remains cautious, missing out on the transformative potential it offers1. The only way to bridge this gap is to take the first step: log in and experiment with some simple use cases as outlined in this article. By doing so, marketers can begin to explore AI’s capabilities and start unlocking its value, positioning themselves ahead of the curve in an increasingly competitive landscape.
“Always invite AI to the table. It may be helpful, frustrating, or useless — but understanding how it works will help you appreciate how it may help or threaten you.” – Ethan Mollick, author of Co-intelligence
References:
- AlphaFold and Drug Discovery Jumper, J., Evans, R., Pritzel, A., et al. (2021). “Highly accurate protein structure prediction with AlphaFold.” Nature, 596(7873), 583-589. doi:10.1038/s41586-020-2649-2.
- AI in Pharmaceutical Marketing Choudhury, A., & Saha, S. (2020). “The role of artificial intelligence in pharmaceutical marketing.” Journal of Pharmaceutical Marketing & Management, 34(2), 115-128. doi:10.1080/10496491.2020.1712345.
- Generative AI Overview OpenAI. (2023). “What is Generative AI?” Retrieved from OpenAI.
- Practical Applications of AI in Pharma Hwang, T.J., et al. (2020). “Artificial Intelligence in HealthCare: Anticipating Challenges to Ethics, Privacy, and Bias.” Health Affairs, 39(7), 1144-1151. doi:10.1377/hlthaff.2020.00138.
- Ethan Mollick on AI Mollick, E. (2023). “Co-intelligence: How AI will change the way we work.” Retrieved from Ethan Mollick’s Blog.
- Online Learning Resources for AI Coursera. (n.d.). “AI for Everyone.” Retrieved from Coursera.
Author: Terry Levi
Contributors:
David Logue, Partner, Life Sciences, Baringa Partners
Chris Finch, Vice President, Earthware Limited
Richard Lucas, Innovation Director at Tangent90
James Turnbull, Founder of Camino
Sam Pygall, Regional IT Lead at MSD