Fine Tuned Private Model for Clinical Visit Summary Processing
Executive Summary
The Clinical Trial Assistant is an AI-powered documentation solution designed to automate and standardize clinical visit summaries. Built on a fine-tuned Small Language Model (SLM), it converts raw, unstructured clinical notes into protocol-compliant, structured 8-section visit summaries in under a minute. By significantly reducing documentation time, improving consistency, and minimizing compliance risk, the solution enables Clinical Research Coordinators (CRCs) to focus more on patient care while ensuring high-quality, regulatory-ready trial documentation.
Challenges
Time-Intensive Manual Entry
CRCs spend 8–15 minutes per visit manually writing summaries, reducing time available for patient interaction and core research activities.
Inconsistent Data Quality
Variations in terminology, structure, and completeness across coordinators and sites lead to downstream reconciliation and data-cleaning efforts.
Compliance & Protocol Risk
Incomplete or inconsistent documentation increases the risk of protocol deviations, audit findings, and regulatory non-compliance.
Solution Overview
The Clinical Trial Assistant introduces Smarter Clinical Summaries, powered by a fine-tuned Small Language Model: Automatically transforms unstructured visit notes into standardized, protocol-aligned 8-section summaries Supports multiple therapeutic areas including Urology, Oncology, Cardiovascular, CNS, and Metabolic/GLP-1 Adapts to diverse study designs, visit types, and protocol requirements Deployable securely on-premise or in the cloud, including local inference on NVIDIA DGX Spark, ensuring full data privacy and regulatory compliance
How it Works
Functional Workflow
Pre-Processing & Data Extraction
- Identifies participant ID, phase, therapeutic area, visit type
- Extracts symptoms, safety notes, compliance data
- Captures labs, procedures, deviations, and next-visit details
Fine-Tuned Visit Summaries
- Generates consistent, protocol-aligned summaries
- Outputs structured JSON ready for EDC, CTMS, and RTSM systems
Template & Consistency Enforcement
- Ensures all 8 sections are always present
- Prevents hallucinated or inferred content
- Enforces standardized terminology and formatting
Privacy-Safe, On-Device Deployment
- Fully on-prem inference using DGX Spark (128GB unified memory)
- Zero data egress with support for HIPAA and 21 CFR Part 11
- Optional cloud deployment on GCP or Azure
Business Impact
- 70% of visit summaries required no CRC edits
- Remaining summaries needed only minor formatting or terminology adjustments
- Consistent documentation across sites, coordinators, and studies
- Seamless integration into mock EDC and RTSM workflows
Key Benefits
key Outcomes with Fine Tune Private Model For Clinical Visit Summary
Documentation Time
Under 1 minute per visit - 90% Reduction
Accuracy Rate
70% of summaries are 100% accurate - High Consistency
Data Readiness
Structured JSON for direct integration - Clean Integration
Technical Foundation
Model
Google Gemma 3 (fine-tuned Small Language Model)
Training Data
1,000+ curated clinical visit–summary pairs
Runtime
NVIDIA DGX Spark (on-prem) or GCP / Azure
Framework
Custom pre-processor and normalization pipeline
Guardrails
SOP-aware validation layer enforcing accuracy, structure, and compliance
From Manual Documentation to AI-Driven Clinical Precision
The Clinical Trial Assistant demonstrates how specialized, fine-tuned AI models can deliver real value in regulated clinical environments. By reducing documentation time by nearly 90%, improving first-draft accuracy, and ensuring standardized, compliant outputs, the solution addresses one of the most persistent operational bottlenecks in clinical research. Its secure, on-premise deployment model and strong guardrails make it a practical, scalable foundation for modernizing clinical trial operations without compromising privacy, precision, or regulatory trust.
