How It Works

From Clinical Question to Regulatory Output in Days, Not Months

Six integrated stages replace fragmented vendor engagements, manual data aggregation, and inconsistent frameworks.

Manual Process

14 weeks

Fragmented data sources, Excel-based analysis, manual document authoring, multiple rounds of QC, consultant dependencies.

ArcaScience

3 days

Integrated pipeline from data ingestion to regulatory submission with full traceability, continuous validation, and automated outputs.

Every Benefit-Risk Assessment Follows the Same Validated Process

From defining the clinical question through generating submission-ready regulatory documents — each stage feeds directly into the next with complete data lineage and audit trail.

1
Data Intelligence

Clinical Framing

Define the benefit-risk question: indication, comparator, patient population, time horizon. Map regulatory requirements to analysis plan. Establish value tree and effects table structure.

Key Outputs

  • Regulatory alignment checklist (FDA/EMA/PMDA)
  • Decision framework configuration (BRAT, MCDA, or custom)
  • Effects table template with pre-mapped endpoints
  • Comparator and subpopulation specifications
  • Analysis plan version-controlled for audit trail
2
Data Intelligence

Data Intelligence Engine

24 proprietary AI models extract, classify, and detect signals from AS Profiling Base 100b® — 100+ billion data points spanning clinical trials, spontaneous reporting databases, electronic health records, published literature, and regulatory submissions.

Data Sources

FAERS, EudraVigilance, VigiBase, ClinicalTrials.gov, PubMed, Embase, client CSR databases, RWE feeds

Data Volume

100B+ data points continuously updated, versioned snapshots for reproducibility

Harmonization

MedDRA coding, deduplication, standardization across heterogeneous sources

3
Decision Intelligence

AI Processing

NLP for unstructured text (case narratives, literature, regulatory documents). Entity recognition for drugs, adverse events, patient characteristics. Pharmacovigilance-specific classifiers supporting MedDRA coding and causality assessment.

AI Model Categories Applied

NLP Models (6)

Text extraction, entity recognition, classification, sentiment analysis, summarization, translation

Validation Models (6)

Consistency checks, bias detection, completeness scoring, confidence calibration

4
Decision Intelligence

Strategic Analysis

Quantitative benefit-risk frameworks including MCDA and weighted effects tables. Sensitivity analysis and scenario modeling. Subpopulation-level and comparator-level assessment.

BRAT Framework

Structured value trees and effects tables aligned with FDA/EMA guidance

MCDA

Quantitative weighting with SMAA and swing weighting methodologies

Scenario Modeling

Sensitivity analysis, comparator trade-offs, subpopulation stratification

5
Decision Intelligence

Decision Intelligence

Interactive visualizations: effects tables, forest plots, value trees. Scenario comparison and trade-off analysis. Complete audit trail for every analytical decision, compliant with 21 CFR Part 11.

Interactive Decision Tools

  • Effects tables with real-time comparator switching
  • Forest plots with confidence intervals and subpopulation filters
  • Value trees with adjustable criteria weighting
  • Scenario comparison dashboard with side-by-side analysis
  • Complete audit trail with timestamp, user, and rationale for every decision
6
Automated Outputs

Automated Outputs

Regulatory documents generated directly from analysis: PSUR/PBRER (ICH E2C(R2)), RMP (EMA GVP Module V), CTD Module 2.5 (ICH M4E), HEOR reports.

PSUR / PBRER

ICH E2C(R2) aligned with automated interval and cumulative data integration

Risk Management Plans

EMA GVP Module V format with safety spec, PV plan, risk minimization

CTD Module 2.5

ICH M4E structure, NDA/BLA/MAA ready with benefit-risk conclusions

HEOR Reports

Value dossiers for NICE, G-BA, HAS, CADTH, PBAC with comparative effectiveness

From 12-16 Weeks to 2-5 Days

Each stage builds on the previous with no handoffs, no data re-entry, and no waiting for external consultants.

Stage 1-2

Minutes to Hours

Clinical framing and data intelligence configuration

Stage 3-4

Hours to 1 Day

AI processing and strategic analysis execution

Stage 5-6

1-2 Days

Decision intelligence review and automated output generation

Total Time: ArcaScience

2-5 days

vs 12-16 weeks manual | 83% time reduction

Schedule a Technical Briefing

See the six-stage pipeline in action. Our scientists will walk through each stage using your therapeutic area and regulatory use case.

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