DocEX
Clinical Research Data Structuring
The Challenge
Client maintained 10+ years of clinical trial data in scattered, unformatted Excel files with no standardization, inconsistent definitions, and poor regulatory readiness.
Manual processing took weeks and error rates were high (8–12%).
Solution: DocEX
AI-driven NER + ontology-based data extraction engine converting raw research into regulatory-ready structured formats.
Core Capabilities
Clinical NERAuto-extract dosages, demographics, efficacy %, study methods
Ontology MappingLink entities to RxNorm, SNOMED-CT, MedDRA
Study Outcome MatrixBuild structured outcome tables per trial
Ingredient-Condition MappingGenerate formulation recommendations based on clinical evidence
AI / ML Components
Named Entity RecognitionExtract clinical terms, dosages, and demographics
Ontology MatchingMap extracted data to standardized medical taxonomies
Study Outcome MatrixStructured clinical data compilation
Efficacy ScoringEvidence-based formulation recommendations
Deliverables
- Standardized Excel + JSON repositories with normalized schema
- Research-backed formulation recommendations with dosage ranges
- Traceability with confidence scores per extracted field
Business Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| Doc Cycle | 15–20 days | 2–3 days | 85% faster |
| Data Entry Errors | 8–12% | <0.5% | 99% reduction |
| Regulatory Prep | Weeks of rework | 3–5 days ready | Audit-ready |
| R&D Iteration | 2–3 weeks | 3–4 days | 80% faster |
Key Outcomes
Artificial Intelligence (AI) is revolutionizing industries worldwide, from healthcare to finance. Businesses are rushing to adopt AI to enhance operations, gain insights, and improve decision-making. However, many are discovering a critical issue: without strong governance, AI initiatives can quickly fall short of their potential.
AI governance is the secret ingredient that helps businesses unlock AI’s full power while ensuring security, compliance, and ethical use. In this blog, we’ll explore why governance is vital to your AI strategy and how it can help businesses avoid the pitfalls of AI implementation.
