Automation of Clinical Study Reports (CSRs)

Narrativa’s Answer to Regulatory Affairs Automation

Narrativa harnesses Generative AI to transform clinical trial data into comprehensive CSRs. AI’s capabilities extend beyond text generation to include information extraction, question answering, etc. This technological advancement is set to revolutionize clinical trial design and reporting.

Automation of Clinical Report Writing

Automating CSRs enables pharmaceutical companies to streamline workflows, minimize costs, and ensure guideline adherence. By reducing human errors and review cycles, AI-driven CSR automation enhances efficiency. Key applications include automating Tables, Listings, and Figures (TLFs) and patient safety narratives, significantly reducing the workload for medical writing teams.

How Does Our Platform Work?

Narrativa’s platform automates CSR writing by extracting data directly from Tables, Listings, and Figures (TLFs) and ADaM (Analysis Data Model) structured datasets, converting them into structured prose. Instead of manually analyzing complex tables, our AI-powered system processes TLFs from various formats (PDF, Word, etc.), imports the data into Narrativa’s Knowledge Graph, and generates clear, concise narrative text—saving time and improving accuracy.

Our data-to-text AI models allow both system-generated and custom user prompts for flexible content generation.

Traceability and Validation

Since the platform generates an initial draft, the medical writer must review and validate the text for accuracy. To facilitate this, the system allows users to click on any data point, instantly locating the corresponding value in the original table or dataset.

This feature streamlines the quality assurance (QA) process, enabling quick verification and edits while keeping full control in the hands of the medical writer.

By clicking on any data point, the system will locate the corresponding data point in the appropriate table

Narrativa Knowledge Graph® integrates various data management methodologies, including:

• Interlinked Databases: Providing structured entity descriptions.
• Semantic Knowledge Bases: Enabling data interpretation and inference.

By combining deep learning with knowledge graphs, Narrativa can process vast datasets, extract key insights, and generate contextualized reports.

Advanced Statistical and Analytical Integration

Narrativa’s CSR Automation solution incorporates:

• Statistical testing for hypothesis validation
• Confidence interval calculations
• Risk assessments (relative risk, risk ratios)
• Frequentist and data augmentation techniques

More Features: Variability and Rich Language

Narativa’s CSR Automation Solution is specifically engineered to create quality content in a simple and effortless way. We require a corpus to train our system and adapt it to the appropriate or desired style so that; the final result will have variability and rich language if needed.

We use different deep learning algorithms to extract all the valuable information and ingest large amounts of medical trial data to generate the text. To achieve this in a more accurate way, we extract topics, synonyms, and similar sentences. The goal is to mimic the writing style used in the corpus.

In addition, companies maintain full control of the output. If the final result does not meet the expectations, text adjustments can be quickly made as the process is reiterated.

It is part of Narrativa’s mission to use technology for good, and transforming medical trial data into documentation is certainly a way that artificial intelligence can be democratized for the benefit of humanity.