AI and medical writing: Unlocking value for life sciences

Placing a ‘no-regret bet’ on medical writing

The drug development life cycle is largely spent on regulatory authoring, submission, and review processes. While the regulatory process has advanced from physical paper submissions, it’s still very manual and document based. Our experience has shown that AI-driven automation in regulatory authoring, and medical writing in particular, can boost value quickly. Automation can reduce medical writer effort by 20% to 30%, yielding a potential annual cost savings of $30 million on average for a top 10 biopharma company (assuming a 50-candidate pipeline).

Since medical writing is data-driven in nature, many authoring tasks can be automated, allowing focus to shift from writing into more valuable activities such as scientific research, engagement with external research communities, and benefit/risk assessments. Beyond process efficiencies, GenAI-enabled automation also drives repeatability, reducing errors or inconsistencies, and can streamline the translating and localizing of content.

Take a holistic approach to transform medical writing

Medical writing covers a wide range of documents and authoring scenarios. For example, across study documents, an author may need to write narrative text, create plain language versions, localize content for regions, develop figures and tables, and ensure consistent references and citations. This complexity makes it challenging for any single technology to address the variety of scenarios.

While we’re optimistic about GenAI capabilities in medical writing, we expect the greatest value to come when GenAI is integrated with existing enterprise data ecosystems and platform solutions, including content management solutions and structured content authoring platforms. Choosing the “right tool for the job” has been the core underpinning of our approach in holistically solving for medical writing automation.

What to consider when using GenAI in the authoring process

While GenAI is set to transform the medical writing process, it comes with new considerations and precautions to ensure its responsible and ethical use. Below are things to weigh for enhancing medical communication without compromising accuracy, trust, or human expertise:

Data privacy and security

Design and implement controls for data privacy and security to ensure protection of sensitive information.

Ethical considerations

Plan, design, and monitor for bias and misinformation in generated content. Ensure that content is transparent and traceable.

Quality assurance

Embed human oversight into the submission development processes leveraging qualitative and quantitative techniques.

Regulatory compliance

Ensure solutions adhere to emerging regulatory requirements on the use of AI in generating submission content.

The future of AI in pharmaceutical regulatory affairs

As GenAI capabilities become a regular part of document-based business processes, GenAI will evolve from simple drafting of content to providing content intelligence. Integrating GenAI with structured content authoring solutions, for example, will allow the large language model to learn document structures and writing styles.

Regulatory review agents trained on regulations and past health authority inquiries will work with writers to ensure documents comply with relevant regulations and standards. Authoring assistant agents will also contain embedded knowledge of regional regulatory requirements, terminology, and translations allowing for simplified authoring of regional document variants.

Long-standing impact with AI for medical documentation

We believe that GenAI is here to stay, and the promise is real. Medical writing is a complex process, requiring specific domain expertise and multiple technologies, and GenAI cannot solve every piece of the authoring challenge alone. We have a clear vision of integrating GenAI with existing technologies and tools to streamline the authoring workflow, ensure regulatory compliance and global reach, and enhance collaboration and knowledge sharing.

Because a reduction in regulatory authoring and review timelines means lifesaving drugs can get to patients faster, it’s worthwhile to see how GenAI can fit into the overall authoring automation process. The technology should be viewed as a tool to be used with the appropriate controls to solve specific problems. With the right framing, GenAI can make a long-standing impact on the life sciences industry with benefits stretching across medical writers, life sciences organizations, and ultimately patients.

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