Structured Content Management Meets AI: Enhancing Health Authority Interactions

Today’s Playing Field 

Regulatory submissions and health authority interactions seem to only get more and more complex.

Regulatory bodies like the FDA, the EMA, and others globally often need timely, accurate, and adaptable responses to questions and requests for information following sponsor submissions. Because of the ad hoc nature of these interactions, challenges traditionally may include information that is cobbled together from various sources having inconsistent formatting, manual errors from reviewers or editors, or other seemingly minor mistakes which, on the regulatory scale, are anything but minor. Problems like these can lead to rejected submissions, time-consuming iterations on the same documents for minor tweaks, and sullied relationships with regulatory approvers. Artificial intelligence (AI) has made its way into this scene, but its success is built upon a robust counterpart which for years has streamlined routine authoring activities – structured content management. 

What is Structured Content Management? 

Structured content management refers to organizing content into standardized sections, templates, tables, or some other format. This type of compartmentalization of data into predetermined fields offers significant benefits to regulatory submission processes, especially where improvements in consistency, compliance, and efficiency cannot be overstated. 

Transforming the Game 

AI can take on structured content management in automating content creation, updates, mapping activities, and other tasks which have historically burdened reviewers. Natural language processing (NLP) and machine learning (ML) can ensure that content is dynamically aligned with evolving guidelines, taking structured content management a step beyond its traditional role. Additionally, AI is able to identify patterns, trends, and gaps in previously submitted documents if these are incorporated into its training and retraining, allowing for more robust, comprehensive, and compliant outputs in future iterations. All of these strengths of properly trained AI systems enable quicker and more accurate responses to specific inquiries from health authorities (HAs) than structured content management alone. 

Winning Points 

Benefits to regulatory submission processes through the meshing of structured content management and AI range from micro to macro and go beyond the document itself. Take a look at a few we list here. 

1. Faster and more accurate responses. By retrieving relevant content, drafting responses in record time, and applying updates based on prior iterations, AI tools can help expedite responses to HAs. 

2. Improved consistency across submissions. The training and retraining of AI tools helps ensure terminology, formatting, and other specifics are consistent across multiple submissions. 

3. Enhanced flexibility and adaptability. Organizations can quickly adapt to changing guidelines or new HA requirements without reworking an entire document, promoting efficient submissions even when tailoring is needed for multiple HAs. 

4. Scalability and efficiency. AI tools allow teams to increase the volume and complexity of their submissions with reduced manual effort. 

5. Improved relationships with HAs. Efficient and well-crafted responses can improve or maintain good relationships with HAs and ensure faster approvals. 

6. Across the value chain. Ultimately, faster submissions with the help of AI will help get therapies to patients sooner, impacting many others across the value chain. 

   
   

Charting the Next Play 

As the intersection of structured content management and AI continues to shape future interactions with regulatory bodies and HAs, it will be important for stakeholders to remain active in the conversation around responsible adoption and implementation of these tools. While benefits can be clearly seen in the automation of certain tasks, quality must remain a key goal. AI provides a way forward by building upon structured content management to expedite and streamline accuracy, consistency, and formatting checks across responses and submissions while letting submission teams handle the collaboration necessary to bring these projects to successful completion.  

AI solutions like AgileWriter.ai™ are paving the way forward for these processes and may serve as a helpful steppingstone in optimizing the regulatory response process. For more information on how AI is entering the conversation with HAs, check out our related blog on engaging with the FDA on AI in clinical trials.