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As the FDA transforms its internal processes, driven by experiences like Jinzhong (Jin) Liu's "game-changer" use of generative AI to perform tasks in minutes that previously took days, leading to Commissioner Martin A. Makary mandating agency-wide AI adoption to slash "non-productive busywork". This transformation raises a natural question: To what extent can the pharmaceutical industry leverage AI-driven efficiencies to streamline its extensive clinical documentation processes?

For AI vendors like AlphaLife Sciences, who partner with major pharma companies, there is already significant precedent for substantial gains. The AuroraPrime Generative AI platform and its suite of GenAI solutions, including the AuroraPrime RMA (Regulatory and Medical Authoring) Add-In and Prime Medical Narratives, are purpose-built extensions designed to significantly enhance the creation of clinical documentation such as clinical study reports (CSRs), study protocols, lay summaries, and medical narratives.

The AuroraPrime RMA Add-In, a Word plugin ready for immediate use that seamlessly integrates into existing workflows, helps pharmaceutical companies reduce cycle times, lower costs, and enhance the overall efficiency of their clinical trials by automating time-consuming tasks such as incorporating Tables, Figures, and Listings (TFLs) and generating TFL summaries. Similarly, Prime Medical Narratives allows users to efficiently generate comprehensive, free-text reports of individual participant experiences by leveraging the power of generative AI.

These tools achieve efficiency gains through several key functionalities:

• Automated Initial Draft Generation: Template Admins can create AI-enabled document templates that include structure, content reuse methods, styles, writing instructions, and content examples. This enables medical writers to leverage generative AI to auto-generate initial document drafts, significantly accelerating the writing process.

• Large-scale TFL Automation: The RMA Add-In facilitates the efficient incorporation of TFLs into CSRs and the auto-generation of TFL summaries based on the data presented in tables, figures, and listings. This significantly optimizes the TFL management workflow. Users can incorporate TFLs individually or in batches, either directly from source files (RTF format is supported with specific guidelines) or using in-text placeholders. The system can incorporate TFLs in batches from source files, Excel config files, or DPS files.

• Automated Narrative Generation: Prime Medical Narratives allows users to import clinical trial datasets from various sources, including Prime Collect EDC, third-party EDCs (ODM, Excel), and script-generated datasets (SAS, SDTM, ADAM). After mapping data points and configuring AI generation rules and examples, the system can auto-generate patient narratives. Narratives are typically required for subjects with Serious Adverse Events (SAEs) and those who discontinue due to Adverse Events, with criteria configurable within the system. The tool allows batch downloading of generated narratives. The gains can appear dramatic for highly structured, repetitive tasks like patient narratives, which can be generated based on imported data and configured rules.

• Generative AI Companion: Writers can interact with an AI Chat for assistance with tasks, view the progress of AI tasks, manage personal prompts, and provide feedback to improve AI-generated content.

Of course, raw speed gains don't matter if they come at the cost of accuracy. AlphaLife Sciences has built a robust AI-driven quality control framework to ensure the highest-quality content generation, continuously enhancing output accuracy and consistency. This framework helps ensure compliance with regulatory standards. Achieving precision involves a mix of humans and machines. The RMA Add-In provides features for validating TFL summaries against the corresponding TFL data to ensure accuracy and consistency. While AI assists in generating content, medical writers and scientists ultimately remain responsible for the output. Providing feedback on AI-generated content is encouraged and used to refine AI behavior and enhance content accuracy and relevance.

While creating standardized workflows that keep humans firmly in the loop is important, best practices need to extend across the board. Effective AI tools require managing data processes well and managing writing processes well. Dossiers must be built from machine-processable data. The AuroraPrime platform supports various data sources and file types, and the RMA Add-In allows configuring source data paths for synchronization. Standardizing the human element and the raw data is as vital as refining the machine learning models themselves. Standardizing the input going into the AI is also helpful, and prompts can be managed for consistency and accuracy.

The gains plateau quickly unless teams plug AI straight into the systems they already trust. The AuroraPrime platform is designed for seamless integration with upstream and downstream systems (e.g., RIM), enabling users to automate document authoring by assembling structured content with minimal manual intervention. The RMA Add-In operates directly within Microsoft Word 365, a familiar environment for users. It integrates fully with regulatory ecosystems. AlphaLife Sciences follows an agile development lifecycle with a monthly release cadence, allowing quick adaptation to evolving requirements.

Now that the FDA is also chasing GenAI-driven efficiency gains, perhaps the next phase of work for the wider industry will shift from head-spinning productivity gains to a deeper focus on disciplined data hygiene, prompt governance, and accountability. Those maturity gains could lead to continued progress over time. There is a need for "pushing really hard to have very solid processes — data consistency — and machine processable data for all studies, moving forward, consistently across all studies". If those pieces fall into place, the industry's busiest writers could soon spend more of their time interpreting data rather than just formatting it.

AlphaLife Sciences has proven success with global pharma and a strong track record in global RFP processes, consistently ranking as a top choice due to the effectiveness and reliability of our AI-powered solutions. We collaborate with top AI technology companies such as Microsoft, Google, and Nvidia, ensuring we remain at the forefront of AI innovation. Our deep expertise in AI, combined with seamless integration capabilities, allows us to deliver cutting-edge, enterprise-ready solutions that outperform other application platforms in the industry.