Creating scientific whitepapers from clinical data is a complex and resource-intensive process. Teams must synthesize clinical trial data, real-world evidence (RWE), and scientific publications into structured, evidence-based narratives—while ensuring accuracy, traceability, and compliance with regulatory and medical-legal (MLR) standards.

The Life Sciences SME Content Engine transforms this process through agentic AI automation. Built on Narrativa’s proven framework for regulated content generation, the solution enables pharmaceutical teams to produce scientifically grounded whitepapers that are fully traceable to source evidence and ready for downstream commercialization use.

By guiding users through a structured workflow—from outline creation to draft generation and review—the platform ensures consistency, quality, and alignment across all outputs.

• Generates scientific whitepapers and case studies directly from clinical trial data, real-world data (RWD), and validated source materials
• Requires outline-first workflows to ensure structured, high-quality content aligned with strategic objectives
• Maintains full traceability between claims and supporting evidence for auditability and review
• Adapts content for different audiences, including healthcare professionals (HCPs) and payer stakeholders
• Supports MLR-ready review processes with versioning, comments, and export capabilities
• Enables reuse of approved content across downstream assets such as detail aids, brochures, and marketing materials

Scientific whitepapers play a critical role in pharmaceutical commercialization by translating complex clinical data into clear, evidence-based narratives that support stakeholder engagement, market access, and value communication.

However, traditional whitepaper development is often manual, time-consuming, and difficult to scale. Teams must gather data from multiple sources—including clinical study reports (CSRs), protocols, statistical analysis plans (SAPs), tables, listings, and figures (TLFs), and scientific publications—while ensuring consistency, accuracy, and compliance.

The Life Sciences SME Content Engine addresses these challenges by introducing a structured, agentic AI-driven workflow:

• Project setup: Define study context, audience (HCP, payer), geography, and output requirements

• Source ingestion: Organize clinical datasets, scientific evidence, and internal materials

• Template and style alignment: Apply structure, tone, terminology, and citation standards

• Outline generation and approval: Create a structured framework with key messages and evidence mapping

• Draft generation: Produce full whitepaper drafts grounded in validated sources

• Review and traceability: Link claims to evidence, flag gaps, and support collaborative review

• Export and reuse: Deliver MLR-ready outputs and store content for downstream use

This approach ensures that whitepapers are not only high-quality and compliant, but also scalable across therapeutic areas and commercialization initiatives.

By leveraging AI agents, knowledge graphs, and structured data workflows, Narrativa enables pharmaceutical teams to transform clinical evidence into impactful, reusable content—accelerating time-to-market while maintaining scientific integrity.