CSR Automation with AI Agents

Quickly automate clinical study reports (CSRs)

Specialized AI Agents that transform clinical trial data into accurate, compliant, and submission-ready Clinical Study Reports.

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SPOTLIGHT

Discover how Narrativa is helping Pharma companies to accelerate Regulatory Submissions

Clinical Study Reports automation

Clinical Atlas automates the process of CSR generation. By deploying specialized AI Agents for dataset creation, TLF generation, table-to-text conversion, and QA validation, the platform transforms TLFs into submission-ready CSR content. Each AI Agent handles a specific stage of the CSR workflow, working together to produce accurate, compliant reports with full traceability from every data point back to its source.

Clinical Study Reports and related documents are essential for regulatory approval, but they are slow and complex to produce. Manual processes require significant coordination across teams, especially for components like Tables, Listings, Figures, and patient narratives, which often leads to delays, inconsistencies, and higher costs.

AI-powered automation simplifies this process by turning clinical data into structured, compliant documents in a fraction of the time. By automating key tasks such as CSR drafting, narratives, and data outputs, teams can reduce timelines, improve accuracy, and focus on higher-value work. Solutions like Narrativa’s platform help life sciences organizations move faster and deliver treatments to patients sooner.

Key Benefits of CSR AI Automation

Compliant

The Compliance Specialist AI Agent ensures regulatory adherence and alignment with ICH E3 guidelines and sponsor-specific templates from the first draft.

Accelerate Regulatory Approvals

Automated, compliant CSRs speed up the submission and approval process, shortening time to market.

Full Traceability

Click on any data point in the generated narrative to instantly trace it back to its source in the original table or dataset, enabling fast, precise

Fewer Review Cycles

AI Agent-generated narratives maintain consistency and accuracy across sections, reducing the need for multiple rounds of editorial and medical review.

Efficiency

Significantly lower costs and overhead associated with CSR creation by delegating repetitive data extraction, formatting, and writing tasks to purpose-built AI Agents.

Faster CSR Drafting

AI Agents generate structured CSR narratives in hours, reducing weeks of manual effort typical in traditional report writing.

CSR AI Agents

TLFs

TLF Generation

Generates Tables, Listings, and Figures (TLF) for clinical trials, streamlining the reporting process. This capability enhances the efficiency of data presentation, allowing researchers to focus on insights and outcomes rather than the technicalities of report generation.

CSR

Table to Text

Converts complex TLFs into clear, narrative prose text, facilitating easier interpretation of data. This transformation aids researchers and stakeholders in understanding findings without needing to decipher intricate tables, thereby supporting more informed decision-making.

Documents

Document Planner

Organizes and plans the creation of regulatory documents, ensuring timely and accurate submissions. By streamlining the documentation process, it reduces the risk of delays and errors, facilitating smooth compliance with regulatory requirements.

Quality Control

QC Validator

Ensures the quality and consistency of documents through automated quality control checks. This tool significantly reduces the likelihood of errors and inconsistencies, maintaining the integrity and reliability of all documentation.

Compliance

Compliance Specialist

Monitors and ensures adherence to regulatory compliance across processes and documentation. By actively overseeing compliance, it helps to prevent potential regulatory issues, ensuring all practices meet current legal and industry standards.

Clinical Atlas streamlines Clinical Study Report (CSR) development with its core AI Agents, which are designed to enhance quality and compliance throughout the process. These intelligent agents provide continuous oversight, coordinating the creation of CSRs while performing rigorous quality control checks to identify and rectify errors at an early stage.

Learn more: CSR agentic AI automation

The pharmaceutical industry is undergoing a data revolution, with AI playing a pivotal role in transforming raw data into actionable insights. Traditionally, empirical analysis has been the foundation for identifying patterns, testing hypotheses, and evaluating treatment efficacy. Now, AI is set to amplify this process, enabling faster knowledge dissemination and regulatory compliance.

Clinical Atlas enables pharmaceutical companies to automate the creation of Clinical Study Reports (CSRs), streamlining workflows, reducing costs, and ensuring regulatory compliance. By minimizing human error and cutting down on review cycles, this AI-powered tool enhances overall efficiency. Clinical Atlas supports key use cases such as the integration of Tables, Listings, and Figures (TLFs) and patient safety narratives, significantly reducing the manual workload for medical writing teams.

Clinical Atlas automates the writing of Clinical Study Reports by extracting data directly from Tables, Listings, and Figures (TLFs) and ADaM datasets, converting them into clear, structured narrative text. Instead of manually reviewing complex tables, the AI processes TLFs from multiple formats, maps the data into the Narrativa Knowledge Graph, and generates accurate, submission-ready prose—saving time and reducing errors.

Clinical Atlas supports both system-generated and user-defined prompts, allowing for flexible, high-quality content tailored to specific reporting needs.

Since Clinical Atlas generates the initial draft, medical writers are responsible for reviewing and validating the content for accuracy.

To support this, the platform allows users to click on any data point in the narrative and instantly trace it back to its source in the original table or dataset. This feature simplifies the quality assurance process, enabling fast, precise verification and edits while keeping full editorial control with the medical writer.

The 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.

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

Narrativa’s CSR automation solution is designed to generate high-quality content with ease. By training on a provided corpus, the system adapts to each organization’s preferred writing style, producing narratives with rich language and variability when needed.

Using deep learning, the platform extracts key topics, synonyms, and sentence structures from large volumes of clinical trial data to mimic the desired tone and format. Users retain full control over the output, with the ability to refine text as needed through an iterative process.

This approach reflects Narrativa’s mission to apply AI responsibly—turning complex clinical data into clear, compliant documentation that serves both science and society.

Regulatory compliance is a critical component of clinical trials, yet the manual creation of CSRs remains a resource-intensive task. Automating these reports allows pharmaceutical companies to:

Optimize operational efficiency

Reduce costs and manual workload

Reallocate resources to higher-value research and development activities

By embracing AI-driven CSR automation, the pharmaceutical industry can expedite drug development, improve regulatory submissions, and ultimately enhance patient outcomes.