A multi-agent AI platform for clinical trial operations: specialized agents to accelerate feasibility assessment while ensuring data accuracy
- Bio LIMS INC
- May 29
- 3 min read
Yi Ni*
Bio LIMS INC, Boston, Massachusetts, United States
*Corresponding author: yi.ni@biolims.net
2026 ASCO Annual Meeting — American Society of Clinical Oncology
May 29 – June 2, 2026
McCormick Place, Chicago, IL
Poster
Abstract
Clinical trial feasibility assessment is one of the slowest, most resource-intensive steps in study start-up — particularly for sponsors evaluating multi-country deployments in emerging clinical research markets. Site questionnaires arrive as unstructured documents, capabilities are scattered across hundreds of sites, and matching the right protocol to the right site traditionally requires weeks of manual review. We present a multi-agent AI platform that orchestrates specialized agents across document ingestion (NLP and OCR), structured knowledge graph construction, site-protocol matching, and analytics generation — turning a workflow that traditionally consumes three weeks of expert effort into a three-day automated process. The platform was deployed in production with Clinical Research Malaysia (CRM), a Malaysian government-owned organization under the Ministry of Health that manages 400+ clinical trial sites and 200+ international multi-center trials annually, powering their FeasIQ Feasibility Management System across 90+ active sites. Headline outcomes include 89% site-matching accuracy, 65% improvement in site selection precision, 95% time savings on questionnaire processing, 80% reduction in manual workload, and a 40× efficiency gain in data processing. A human-in-the-loop architecture preserves expert oversight at every decision point, while a unified knowledge graph dissolves data silos across the trial site network and supports real-time visual analytics and predictive insights for sponsors.
Platform capabilities
Intelligent data architecture
NLP and OCR agents convert unstructured site questionnaires — PDFs, scanned forms, free text — into structured digital knowledge graphs for downstream reasoning.
AI-powered site selection
Specialized matching agents move site selection from "needle in a haystack" search to precision navigation, achieving 89% protocol-site matching accuracy.
Enterprise data platform
A unified data fabric integrates site capability, capacity, and historical performance across 90+ trial sites, breaking down the silos that block portfolio-level decisions.
Automated intelligence
Real-time visual analytics and predictive insights surface feasibility risk, capacity bottlenecks, and competitive site landscape for sponsors in a single dashboard.
Headline outcomes
Feasibility cycle
3 days
from 3 weeks manual
Site-matching accuracy
89%
protocol-to-site
Site selection precision
+65%
vs. manual baseline
Questionnaire processing
−95%
time required
Manual workload
−80%
human effort reduced
Data processing throughput
40×
efficiency gain
Deployment context
Production deployment
Partner
Clinical Research Malaysia (CRM)
System
FeasIQ — feasibility management system
Trial sites managed by CRM
400+ nationwide
International trials per year
200+ multi-center studies
Cumulative sponsored projects
2,500+ since 2012
Compliance certifications
ISO 9001:2015, ISO 37001:2016
CRM is a Malaysian government-owned organization under the Ministry of Health and serves as the principal gateway for global pharmaceutical sponsors entering Southeast Asia.
Why this matters for oncology
Oncology trials are increasingly multi-country, biomarker-driven, and competitive for limited site capacity — feasibility assessment lag is one of the leading causes of slow study start-up and missed enrollment timelines. Bringing feasibility from three weeks down to three days, while raising site-selection accuracy, materially shortens the path from protocol design to first patient in, particularly in emerging trial geographies where capability mapping has historically depended on manual outreach.
Keywords
Clinical trial operationsFeasibility assessmentMulti-agent AISite selectionKnowledge graphNLP & OCRStudy start-upSoutheast AsiaOncology trialsFeasIQ
How to cite
Ni Y, et al. A multi-agent AI platform for clinical trial operations: specialized agents to accelerate feasibility assessment while ensuring data accuracy. Poster presented at: 2026 ASCO Annual Meeting; May 29–June 2, 2026; McCormick Place, Chicago, IL. Available at: https://www.asco.org/abstracts-presentations/264224