Harmonizing Global Clinical Trial <br /> Registries for Competitive <br /> Intelligence

Harmonizing Global Clinical Trial
Registries for Competitive
Intelligence

In Partnership with Bioloupe

In Partnership with Bioloupe

The Client: An oncology-focused health tech company automating clinical
evidence extraction.

In Partnership with Bioloupebioloupe.com
The Problem

The "Data-to-Insight" Bottleneck in Clinical Operations

To provide accurate, real-time competitive intelligence to their end-users, the client needed to track and analyze over 72,000 global clinical trials. However, their research team found that clinical datasets were vastly fragmented and maintained through fragile, semi-manual processes.

The "Data-to-Insight" Bottleneck in Clinical Operations
The Factory Solution

Industrializing Trial Data Workflows

To eliminate this bottleneck, Sogody deployed a standardized, AI-agentic data factory framework to continuously ingest, structure, and validate global trial data.

Step 1

Source-Aware Ingestion (The Loading Dock)

Automated pipelines continuously synchronize over 72,000 clinical trials across global registries.
  • Instead of blindly reprocessing the entire database, intelligent agents diff version histories to detect semantically significant changes in trial text, ensuring only meaningful updates (not just typos) trigger the processing pipeline.
  • Custom scrapers dynamically navigate anti-bot protections to routinely extract the thousands of specialized oncology trials from ChiCTR that other platforms miss.
Step 2

AI-Agent Structuring (The AI Refinery)

  • Deconstructing Study Plans: Embedded large language models read free-text trial protocols and decompose them into structured study arms (Experimental, Comparator, Control). The agents extract specific drug components, dosages, and administration routes, differentiating between experimental therapies and standard-of-care backgrounds.
  • Structuring Eligibility Criteria: Agents parse highly unstructured inclusion and exclusion paragraphs to extract specific patient populations. This converts free text into queryable fields detailing required biomarkers (e.g., “EGFR mutation”), disease stages, and prior therapy requirements.
Step 3

Automated Validation & Entity Resolution (The Quality Gate)

Pharmaceutical data cannot rely on simple keyword matching. We implemented a multi-stage entity resolution cascade that cross-checks extracted terms against industry-standard ontologies, like the NCI Thesaurus.
  • This ensures that a broad term like “Breast Cancer” and a specific subset like “HER2+ breast cancer” are intelligently linked, resolving thousands of raw text variations into a clean, canonical hierarchy of diseases and biomarkers.
The Output

Analytics-Ready Competitive Intelligence

The factory pipeline culminated in a harmonized Global Trial Database, delivering a pristine, single source of truth for the client's clinical and commercial leads.

Disparate trial records are transformed into a cohesive ecosystem where every trial is accurately linked to standardized drug molecules (INNs), molecular targets, and specific disease taxonomies.

Analytics-Ready Competitive Intelligence
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