Generative AI is no longer just an option in pharma. It’s essential, and it continues to evolve at a staggering speed. But where can it assist us in medical affairs? What are the opportunities, challenges and potential pitfalls – and how can we at Word Monster help you navigate this new digital era responsibly?
AI is revolutionising the way companies work at an astounding rate, and pharma is no exception. According to recent forecasts, the global market for AI in drug discovery is expected to grow from around $1.5bn currently to approximately $13bn by 2032.1
Medical affairs also has the potential for a unique partnership with AI, including generative AI (GenAI), especially as organisations strive to enhance efficiency, accuracy, and stakeholder relations. Many medical affairs leaders (surveyed by the Medical Affairs Professional Society) are indeed expecting digital and AI to have a high impact on areas of their work, especially in customer insights, medical communication and evidence generation.2
However, AI integration does not come without its challenges. Let’s take a closer look at some of the top benefits – and cautions – associated with AI in medical affairs.
Where can AI provide value in medical affairs?
As advanced capabilities in data analytics and scientific content creation grow, it’s expected that the strongest impacts of AI in medical affairs will be in customer insights, evidence generation, and medical communication.2
Customer insights. Utilising social listening as well as medical-science liaison (MSL) interaction data and customer queries, AI can instantly analyse vast amounts of information to uncover invaluable insights, a task that previously required hours of human curation. With thousands of discussions and endless online content summarised into clear summaries and reports, this could allow a wider and deeper understanding of healthcare professionals’ (HCPs) behaviours, preferences, and unmet needs. Read more about the power of social listening here.
Literature review and analysis. Similarly, AI is able to quickly and efficiently scan through research papers and other scientific data to pull out valuable summaries and patterns for analysis. This can help companies stay abreast of the latest research and industry trends, which can be a challenge given the vast amounts of literature available. It can also help teams draw conclusions and ideas that might have otherwise gone amiss. Think subscribing to Google News updates, but far more in depth.
Regulatory and compliance. Navigating the complex landscape of regulatory requirements is a critical function of medical affairs. As part of AI, Natural Language Processing (NLP) algorithms can help to review documents, reports, and submissions to flag inconsistencies and ensure compliance with the ever-evolving rules.
Content generation. Medical affairs teams spend a large amount of time developing content, from the short to the very long. AI can help by generating first drafts of more routine information, like standard responses to medical enquiries or simple scientific documents, freeing up teams’ time to focus on areas requiring more complex clinical interpretation and nuanced personalised writing. It can also help to tailor existing content to specific audiences and build upon powerful omnichannel strategies. Here at Word Monster, our team is already utilising AI to start each task before refining – making the best use of our time and expertise.
What concerns are there around using AI in medical affairs?
Confidentiality. Handling sensitive patient and HCP data necessitates stringent confidentiality measures, with 79% of health leaders considering legal challenges around data usage as a significant barrier to AI.2 Like with all systems, traditional and digital, AI must comply with data protection regulations like GDPR, and ensuring secure data storage, processing, and transmission is paramount to maintaining trust and legal compliance.
It’s clear that AI is incredible in what it can help us achieve. But before we start automating everything, there are some important considerations that must be taken into account. While all sectors and organisations need to be careful in their use of AI, it’s particularly true for pharma, with strict regulations and patient safety at stake.
Referencing. AI-generated content may lack proper referencing, or it may cite outdated sources, compromising the credibility of reports and scientific communications. Implementing robust validation processes and cross-referencing AI outputs with current literature, ideally by experts in the field, is essential to uphold accuracy.
Bias. As we know, fair balance in medical affairs and communications is paramount. Unfortunately, AI can unintentionally introduce bias into materials or communications, or it may exaggerate existing disparities. Careful and intentional review of AI-generated content is necessary to mitigate bias.
Potential for factual errors. AI can make mistakes too! These are known as “hallucinations” – plausible-sounding but incorrect information presented as facts. Hallucinations can be due to one of a multitude of reasons: over-reliance on training data, use of non-reputable or even factually wrong content, incorrect assumptions or understanding, or even just pure error. Such mistakes, even small ones, can have serious implications in medical contexts. Therefore, human oversight is crucial to review and verify AI outputs before dissemination.
Lightning-fast evolution. AI is growing at a staggering speed – can you even recognise it as it was a year ago? This fast-paced development can outstrip the ability of organisations to adapt in time, especially as health leaders cite a current lack of internal capabilities and capacity as significant boundaries to adopting AI.2 Continuous training, infrastructure updates, and policy revisions are required to keep pace with advancements and ensure effective integration.
The importance of thoughtful implementation
To harness the potential of AI, we can’t just jump straight in and let it do all the work, especially in pharma, where patients lives’ may be affected through errors or oversight.
For the best use of AI in medical affairs, concerns, like those discussed above, must be mitigated through quality control measures and thoughtful implementation strategies.
And, to really succeed with this new and evolving technology, healthcare companies must integrate it properly across complex workflows, and provide ongoing training and education to promote adoption and impact across different teams.
Why we still need human experts
AI holds transformative potential for medical affairs, offering tools to enhance efficiency, compliance, and stakeholder engagement. However, as mentioned, its integration must be approached with caution.
It will still be essential for medical affairs professionals to properly monitor and correct the outputs of their AI partners to ensure accuracy and compliance. Quality control measures must be securely in place – and even tightened. Teams also need to regularly assess AI performance and find ways to incorporate feedback, so that AI outputs meet goals and objectives while maintaining top accuracy.
Furthermore, interrogating the science and ensuring every single word is clear, compliant and will resonate with the end user is something that must be validated by a human. Original thought is essential to connect data to the humans receiving it and applying it to their specific clinical context.
Care is still, ultimately, human.
Where do we come in?
Despite AI’s capabilities, human expertise remains irreplaceable in medical affairs, namely through strategic oversight, clinical judgement and scrutiny, and ethical caution and accountability.
Here at Word Monster, we have the best of both worlds, with a specialist AI team creating efficiencies that allow our scientific experts to focus on making your data sing. We know how to utilise AI insights and use them to develop strong strategies – and can train your own teams to do the same, too. AI doesn’t have to be intimidating; just let us know how we can get you started.
References
- Statista. AI in the pharmaceutical industry – statistics and facts. Available from: https://www.statista.com/topics/11820/ai-in-pharmaceutical-industry/#statisticChapter
- MAPS. 2024 MAPS Ambassador Alliance. Digital, Advanced Analytics & Artificial Intelligence (AI) in Medical Affairs. Available from: https://medicalaffairs.org/wp-content/uploads/2024/10/MAPS-Digital-Advanced-Analytics-Artificial-Intelligence-Report-2024.pdf