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Use CasePSUR & PBRER Generation

AI-Accelerated Periodic Safety ReportingAI Agents for PSUR & PBRER Generation

AI agents aggregate cumulative ICSR data, safety signals, clinical study outcomes and benefit-risk evidence to draft ICH E2C-compliant PBRER and PSUR sections — ready for medical writer review in days, not months.

About PSUR & PBRER Generation

PSUR & PBRER Generation solutions powered by autonomous AI agents enable enterprises to overcome the periodic report bottleneck. Our PSUR automation AI platform provides comprehensive automation for automated periodic report drafting. Trusted by Fortune 500 companies and leading enterprises worldwide for mission-critical psur & pbrer generation operations. Deploy AI-powered agents that work 24/7 to transform your psur & pbrer generation workflows with enterprise-grade security, compliance, and scalability.

Key capabilities include automated data extraction and cross-section reconciliation from argus, arisg or vault safety, narrative drafting for all pbrer sections with citation to source data, cumulative summary tabulations, cioms tables and subject-level line listings, version-controlled output in submission-ready word/pdf format for writer review. Organizations achieve 75% Reduction in Report Preparation Time, Higher First-Draft Quality, and Scale Across Portfolio through our intelligent automation platform.

Purpose-built autonomous agents, tailored to your stack.

Problem and Solution Overview

The friction today

The Periodic Report Bottleneck

PSUR and PBRER preparation ties up safety and regulatory teams for months per product. Aggregating data from dozens of sources is error-prone and version-controlled chaos.

Common challenges in psur & pbrer generation include high operational costs, slow processing times, manual errors, and scalability limitations. Traditional approaches to psur & pbrer generation struggle with manual aggregation of cumulative icsr data, signal summaries and study results across databases, leading to inefficiencies and missed opportunities. Organizations face increasing pressure to modernize psur & pbrer generationoperations while maintaining compliance and reducing costs.

  • Manual aggregation of cumulative ICSR data, signal summaries and study results across databases
  • Inconsistent section drafting quality across products, writers and geographies
  • Last-minute regulatory submission pressure from compressed timelines
  • High cost of senior medical writers dedicated to structured report sections
With Alomana agents

Automated Periodic Report Drafting

Alomana agents pull structured data from your safety database, literature archive and regulatory system to auto-draft all ICH E2C sections — from cumulative exposure tables to benefit-risk narratives.

Alomana's psur & pbrer generation AI agents provide end-to-end automation with enterprise-grade reliability. Our platform leverages advanced machine learning, natural language processing, and intelligent process automation to deliver 75% Reduction in Report Preparation Time. The solution integrates seamlessly with existing systems including ERPs, CRMs, and legacy applications. Real-time monitoring, audit trails, and compliance reporting ensure governance and transparency. Scalable architecture supports growing workloads without performance degradation.

  • Automated data extraction and cross-section reconciliation from Argus, ARISg or Vault Safety
  • Narrative drafting for all PBRER sections with citation to source data
  • Cumulative summary tabulations, CIOMS tables and subject-level line listings
  • Version-controlled output in submission-ready Word/PDF format for writer review

See it in motion

See the agents working on your behalf

Watch how autonomous agents orchestrate data extraction, reasoning and reporting on complex, real-world workloads.

Turn your proprietary data into value

Autonomously analyzes databases, discovers anomalies, and extracts insights from your data

Jade is an autonomous AI data analysis agent that discovers anomalies, generates predictive insights, and automates database analysis across your enterprise systems. Key features include fraud detection, automated reporting, real-time data monitoring, and advanced analytics for business intelligence.
$1M Fraud Prevented

in the last 12 months for one of the largest global servicers across $5B+ in transactions processed.

Data Upload

Upload and process your data files

Drop your files here, or browse

Supports Excel (.xlsx, .xls) and CSV files

Outcomes

What teams achieve with this use case

Organizations implementing psur & pbrer generation AI agents achieve significant improvements across key metrics. Benefits include reduced operational costs, faster processing times, improved accuracy, enhanced compliance, and better scalability. Real-world deployments demonstrate measurable ROI within weeks of implementation. Teams report higher productivity, reduced manual work, and ability to focus on strategic initiatives. The platform supports continuous improvement through machine learning and adaptive algorithms. Enterprise customers benefit from dedicated support, custom integrations, and tailored deployment options including on-premises and cloud-based solutions.

01

75% Reduction in Report Preparation Time

Compress PSUR preparation cycles from 3–4 months to under 3 weeks per product, meeting submission windows without team burnout.

02

Higher First-Draft Quality

Consistent section structure, compliant citations and reconciled tables reduce QC cycles and regulatory queries.

03

Scale Across Portfolio

Run multiple PSUR/PBRER workstreams simultaneously — critical for companies with 10+ products on staggered submission cycles.

Questions, answered

Frequently asked questions

Which PSUR/PBRER sections can agents auto-draft?

Agents can draft all standard sections including cumulative exposure, ICSR line listings and summary tables, signal assessment summaries, study data synopses, benefit-risk evaluation and the executive summary — with full source citations throughout.

How do agents handle benefit-risk narrative drafting?

Agents synthesize cumulative safety data, efficacy evidence and comparator context into structured benefit-risk narratives aligned with the IMI BRACES framework and ICH E2C guidance, flagging evidence gaps for medical writer attention.

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