Skip to main content
Healthcare & Life Sciences Global Pharmaceutical Company

Clinical Trials AI Platform: 85% Faster Screening

Challenge

Manual literature review, patient matching, and drug safety monitoring consuming thousands of hours across research teams.

Solution

End-to-end agentic AI platform covering 5 critical clinical trial workflows with FDA compliance built-in.

Results

85% reduction in screening time
8x faster patient matching
6x pharmacovigilance throughput
FDA 21 CFR Part 11 compliant

Challenge

A global pharmaceutical company faced significant operational bottlenecks across their clinical trials process. Research teams were spending thousands of hours on manual tasks:

  • Literature Review: Manually screening papers against PICO criteria
  • Patient Matching: Slow, error-prone matching of patients to trials
  • Drug Safety Monitoring: Labour-intensive pharmacovigilance processes
  • EHR Data Access: Limited ability to test with realistic patient data
  • Patient Recruitment: Manual outreach and coordination

The compliance requirements made automation particularly challenging—any solution needed to meet FDA 21 CFR Part 11, HIPAA, and GxP standards.

Solution

We built an end-to-end agentic AI platform covering 5 critical workflows:

1. Literature Review Agent

Automated screening of research papers using PICO (Population, Intervention, Comparison, Outcome) criteria. The agent reads abstracts, extracts relevant information, and flags papers for human review.

2. Synthetic EHR Data Generation

Created realistic synthetic patient records for testing and validation—enabling development without exposing real patient data.

3. Intelligent Patient-Trial Matching

AI-powered matching engine that analyses patient profiles against trial eligibility criteria, dramatically reducing time-to-enrolment.

4. Agentic Patient Recruitment Assistant

Automated outreach and scheduling coordination, handling routine communications while escalating complex cases to human coordinators.

5. Pharmacovigilance with Naranjo ADR Scale

Automated adverse drug reaction assessment using the Naranjo scale, processing safety reports at 6x previous throughput.

Architecture Highlights

  • LangGraph for complex multi-step agent orchestration
  • Braintrust for continuous evaluation and quality monitoring
  • NVIDIA NIMs for high-performance inference
  • Full audit trail for regulatory compliance

Results

The platform transformed clinical trial operations:

MetricBeforeAfterImprovement
Literature screening timeWeeksDays85% reduction
Patient matching speed8 days avg1 day avg8x faster
Pharmacovigilance reports50/week300/week6x throughput

Compliance Achievement

  • Passed FDA 21 CFR Part 11 compliance review
  • Full HIPAA compliance maintained
  • GxP documentation standards met
  • Complete audit trail for all AI decisions

Technical Details

Tech Stack

  • Orchestration: LangGraph for multi-agent workflows
  • Evaluation: Braintrust for continuous quality monitoring
  • LLMs: OpenAI GPT-4, NVIDIA NIMs for specialized tasks
  • Frontend: React/Next.js dashboard for trial coordinators
  • Infrastructure: HIPAA-compliant cloud deployment

Key Design Decisions

  1. Human-in-the-loop: Critical decisions always flagged for human review
  2. Explainability: Every AI recommendation includes reasoning chain
  3. Audit Trail: Complete logging for regulatory compliance
  4. Graceful Degradation: System falls back to manual workflows if AI confidence is low

Project Details

  • Duration: 6 months from kickoff to production
  • Team: 4 engineers (2 AI/ML, 1 full-stack, 1 DevOps)
  • Status: Live in production with ongoing support
  • Compliance: HIPAA, FDA 21 CFR Part 11, GxP

Interested in AI for clinical trials or life sciences? Contact us to discuss your use case.

Technologies Used

LangGraph Braintrust OpenAI NVIDIA NIMs React/Next.js

Timeline

6 months delivery

Similar Case Studies

Ready to achieve similar results?

Let's discuss how we can help your business succeed with AI.