The Challenge
Why Benefit-Risk Assessment Remains Fragmented
Fragmented Data Sources
Safety data spread across clinical trials, spontaneous reporting databases, literature, and real-world evidence with no single view.
Manual, Inconsistent Methods
Teams rely on spreadsheets, ad hoc literature reviews, and qualitative narratives that don't scale with regulatory complexity.
Slow Report Cycles
PSUR/PBRER production takes 12-16 weeks. Signal detection is reactive, not continuous. CRO engagements are project-based and expensive.
The Platform
Six Stages. One Analytical Environment.
Data Intelligence Engine
24 AI models extract, classify, and detect signals from 100B+ data points spanning clinical trials, spontaneous reporting, literature, and real-world evidence.
Explore Data Engine →Decision Intelligence
BRAT framework, MCDA, weighted effects tables, sensitivity analysis, and scenario modeling. Interactive visualizations for regulatory communication.
Explore Decision Engine →Automated Outputs
PSUR/PBRER, RMP, CTD Module 2.5, HEOR reports generated directly from the analytical pipeline. Submission-ready, audit-trailed.
Explore Outputs →Why ArcaScience
How ArcaScience Differs
Domain-Specific AI
24 models purpose-built for pharmacovigilance, not adapted from general-purpose NLP.
60% Faster
Evaluation timelines reduced by 60% compared to traditional BRA approaches across 50+ engagements.
70% Cost Reduction
Platform subscription replaces project-based CRO engagements of equivalent scope.
100% Regulatory Acceptance
Every submission using ArcaScience-generated outputs accepted by FDA, EMA, and PMDA.
Case Study — Sanofi
Dermatology BRA Acceleration
Challenge: Sanofi's pharmacovigilance team needed to accelerate PSUR generation for a key dermatology biologic while maintaining regulatory rigor. Manual processes required 12+ weeks per cycle.
Results: 60% reduction in PSUR cycle time, 47 countries harmonized, 100% regulatory acceptance rate.
Read Full Case Study →Dr. Sophie Laurent
VP Pharmacovigilance, Sanofi
Use Cases
Across the Drug Lifecycle
Early Development (Phase I-II)
Safety signal identification, DDI screening, comparator selection, early benefit-risk framing before Phase 3 investment.
Late Development (Phase III / Submission)
CTD 2.5 benefit-risk sections, advisory committee preparation, quantified benefit-risk aligned with FDA and EMA.
Post-Marketing
PSUR/PBRER generation, signal management, RMP updates, continuous benefit-risk monitoring across spontaneous reporting and RWE.
Market Access & HEOR
Value dossiers, comparative effectiveness, payer evidence packages for NICE, G-BA, HAS, CADTH, PBAC.
Trusted by Leading Pharmaceutical Companies
Featured Resources
Download Our Latest Research
AI-Driven Benefit-Risk Analysis: The Quantitative Methodology
Comprehensive overview of the platform's scientific foundation, covering 24 AI models, the BRAT framework, and regulatory alignment with FDA and EMA guidance.
Download WhitepaperArcaScience Platform Overview
A concise summary of ArcaScience's unified analytical environment — Data Intelligence, Decision Intelligence, and Automated Outputs in one page.
Download One-PagerExplore All Resources
Browse our full library of whitepapers, case studies, webinars, and regulatory guides on benefit-risk methodology.
View All Whitepapers → View Case Studies →See ArcaScience Applied to Your Therapeutic Area
Request a demonstration customized to your regulatory challenge, development phase, and therapeutic area.