Medical Affairs professionals have been the scientific bridge between pharmaceutical companies and the broader healthcare ecosystem for decades, connecting clinical evidence to healthcare professionals, researchers, patients, and internal stakeholders. But the environment in which they work is changing rapidly. There is a proliferation of scientific publications, an increase in real-world data, a personalization of stakeholder expectations, and a pace of emerging new evidence that traditional processes have difficulty accommodating.

Artificial intelligence is an increasingly important part of this transformation. Artificial intelligence is able to do more than automate administrative work. It has the potential to change the way that Medical Affairs teams find information, generate insights, engage stakeholders, and make strategic decisions. Technologies like natural language processing, machine learning, generative AI, and AI agents are creating opportunities to move Medical Affairs from information management to more intelligent, insight-driven operations. The challenge is to make sure this transformation happens responsibly.

From AI Hype to Practical Medical Affairs Value

AI is often discussed as one technology, but the landscape is much broader. Machine learning finds patterns in big data, natural language processing understands human language, generative AI is able to make and summarize content, and new AI agents can coordinate multiple tasks in a workflow. The fundamental question for Medical Affairs is not, What can AI do?, but rather, Where will AI add meaningful value, without jeopardizing scientific integrity?

The pharma industry is already heading in this direction. The U.S. Food and Drug Administration has seen a rapid rise in submissions of drugs and biological products that contain artificial intelligence components. From 2016 to 2023, it had more than 500 submissions with AI components across nonclinical, clinical, post-marketing, and manufacturing activities. "This is a clear sign that AI is no longer in the theoretical realm. It is moving into the real-world development and regulatory environment.

The same pattern is seen in investment by industry. According to research by Deloitte, almost 60% of surveyed life-sciences executives intend to boost investment in generative AI throughout the value chain, signaling a move for organizations from experimentation to implementation. This is an opportunity for Medical Affairs to identify practical applications to solve real business and scientific challenges rather than jumping on the bandwagon because AI is trendy.

From Information Retrieval to Scientific Intelligence

One of the most promising applications of AI in Medical Affairs is to revolutionize the management of scientific information. Medical teams are faced with a complex, expansive ecosystem of information such as peer-reviewed publications, results from clinical trials, conference abstracts, treatment guidelines, regulatory updates, real-world evidence, and emerging science. Much of this work has traditionally involved searching, reading, categorizing, and manually synthesizing information. AI may assist in moving the process from intelligence retrieval to intelligence generation.

For example, an AI-enabled literature monitoring system can continuously search for relevant publications, categorize them by therapeutic area or scientific topic, summarize key findings, and highlight emerging patterns. Instead of bombarding a Medical Affairs professional with hundreds of articles, the system could help to pinpoint what developments are worth paying attention to. This is not to say that AI replaces the judgement of science. Instead, it can reduce repetitive processing of information, allowing experts to spend more time interpreting evidence.

This is an important point. The value of Medical Affairs isnt just in knowing what a publication says. This is about understanding what the evidence means, how robust it is, how it compares with existing knowledge, and what implications it may have for patients, healthcare professionals and the organization. PwC has identified AI-assisted scientific literature search and document summarization and medical strategy analysis among emerging capabilities in connected Medical Affairs models.

Generative AI and the New Medical Communications Landscape

Theres another great opportunity with Generative AI that opens the door for us to interact with complex information in natural language. Well-governed artificial intelligence systems could be used by Medical Affairs professionals to summarize scientific publications, compare documents, organize evidence, prepare initial drafts, or retrieve information from approved internal knowledge bases.

The potential gains in productivity can be large. Deloitte notes that medical writing could see a reduction of around 20% to 30% in medical writer effort in relevant activities, thanks to AI-driven automation, which could save large biopharmaceutical organizations a substantial amount. Medical Affairs is not a place for speed over accuracy.

Generative artificial intelligence systems can generate information that is believable but false, sometimes referred to as hallucinations. They also may misinterpret scientific context, inappropriately mix findings, or report an unpredictability with too much confidence. Thats why medical content generated by AI needs to be properly reviewed and verified by humans.