1. Home
  2. Case Study
  3. Automated eCRF Specification Generation System for Clinical Trials

Automated eCRF Specification Generation System for Clinical Trials

We developed a document intelligence system that automates the creation of Electronic Case Report Form (eCRF) specifications for clinical trials.
The platform extracts structured data, validation rules, and dependencies directly from complex study documents , significantly reducing the time, cost, and human effort involved in eCRF preparation for pharmaceutical and research organizations.

Summary :

We have built an AI-powered automation system that processes clinical trial documents to generate complete eCRF specifications in standardized, machine-readable formats. By combining OCR, NLP, and graph-based data modeling, the system extracts study procedures, edit checks, and validation logic from unstructured PDFs, Word files, and rule sheets. It ensures regulatory compliance, improves data consistency, and enables faster study setup for clinical research teams.

Problem

Problem

Objectives

  • Automate eCRF Creation

    Convert trial protocols and rule documents into structured eCRF specifications.

  • Ensure Regulatory Compliance

    Align outputs with CDASH and MedDRA standards.

  • Extract and Standardize Data

    Transform unstructured documents into clean, machine-readable formats.

  • Model Rule Relationships

    Use graph databases to link edit checks, data fields, and dependencies.

  • Improve Speed and Accuracy

    Reduce manual workload while ensuring consistent, validated outputs.

Challenges

  • Handling diverse document formats (PDF, Word, Excel, scanned images).
  • Extracting complex validation rules and interdependencies.
  • Managing medical terminology and hierarchical data standards.
  • Balancing automation with accuracy for compliance-critical outputs.
  • Visualizing rule relationships across hundreds of fields and entities.

Solution

We developed an AI-based eCRF automation system that transforms unstructured trial documentation into standardized, regulatory-compliant specifications.
Using Mistral OCR and Google Gemini models, the platform extracts data from multi-format documents, detects rule logic, and organizes it into structured JSON and Excel outputs.
A graph database (Neo4j) models dependencies between fields and rules, while Milvus vector search enables intelligent document retrieval and comparison.
The Streamlit interface allows users to upload documents, view extracted structures, visualize rule networks, and export final eCRF specs instantly.

Architecture

Document Upload & Processing
PDFs, DOCX, and rule files uploaded through Streamlit.
Text Extraction
OCR and text models extract study procedures, rules, and field data.
Data Structuring
LLMs standardize extracted content into CDASH-compliant formats.
Relationship Mapping
Graph database models dependencies and edit-check relationships.
Output Generation
eCRF specifications exported as Excel, JSON, and visual graph reports.

Results & Impact

Automated generation of eCRF specifications from unstructured clinical documents

Reduced manual processing time by 85%, improving trial setup efficiency

Modeled complex validation rule relationships for better data integrity

Improved compliance and consistency with CDASH and MedDRA standards

Enabled faster, error-free eCRF preparation for clinical research teams

Problem solved. Brainy Neurals accelerates AI
development for everyone

Let’s transform your business with custom AI solutions — from
ideation to deployment.

Here’s What Clients Say About Working With Us

Let’s transform your business with custom AI solutions — from ideation to deployment.

What Our Clients are Saying

We’ve partnered with global businesses to deliver AI solutions that unlock growth, efficiency, and innovation.

Cornelius | Founder, Shatterpoint
Cornelius | Founder, Shatterpoint
Brainy Neurals' AI algorithms have provided us with invaluable insights that have transformed our decision-making process. Their dedication to innovation and exceptional customer service make them the go-to partner for AI solutions.
Vineet | Gauss Moto Inc
Vineet | Gauss Moto Inc
Working with Brainy Neurals has been a game-changer for our organization. Their expertise in AI technology and their ability to tailor solutions to our specific needs have helped us stay ahead of the competition.
Vlad Tudor | Founder, Sapio AI
Vlad Tudor | Founder, Sapio AI
My experience with this RAG project was great. The team built a system that delivers accurate, context-aware responses. From summarizing documents to answering complex queries and improving knowledge retrieval, their efficient implementation ensured smooth and reliable performance.
Dr. Alper Altinok | CEO, Bugmapper
Dr. Alper Altinok | CEO, Bugmapper
Working with Brainy Neurals has been a remarkable experience for our greenhouse farms. Their AI-powered chatbot provides real-time insights that have completely transformed our insect monitoring process. Their expertise and innovative approach have truly made a difference!
Helen Yang | Founder, Andes Risk
Helen Yang | Founder, Andes Risk
Brainy Neurals has done an outstanding job in developing an AI-powered chatbot that streamlines investor profiling. By leveraging advanced data analysis and LLM integration, they’ve made it effortless to understand each client’s risk tolerance and investment behavior. Truly impressive work!
Ready to turn your AI
Ideas
into impact?
We’re here to help.
Let’s Connect to help you and your team
Please enable JavaScript in your browser to complete this form.