Persistent QuickElevate BioMed for Life Sciences Research

Persistent QuickElevate – BioMed is an Amazon Quick-powered scientific intelligence solution designed to help Life Sciences organizations transform manual literature review processes into a governed, AI-assisted evidence review operating model.

The solution enables Research, Medical Affairs, Clinical Development, and Scientific Strategy teams to discover, synthesize, review, and operationalize scientific evidence faster while improving traceability, consistency, and decision readiness.

Scientific evidence is expanding faster than teams can manually search, review, validate, summarize, and convert into actionable decisions. QuickElevate – BioMed helps organizations move from fragmented evidence collection to a scalable scientific intelligence capability.

🌟 Key Benefits

🔬 Accelerate Literature Discovery • Reduce time spent manually searching scientific publications, conference abstracts, trial registries, internal repositories, and prior evidence reviews.

⚡ Improve Scientific Productivity • Enable researchers and Medical Affairs teams to focus on scientific interpretation, strategy, and decision support rather than information gathering.

📚 Generate Consistent Evidence Reviews • Create source-grounded evidence summaries, comparative reviews, and reusable scientific evidence packages.

🛡️ Improve Governance and Traceability • Capture citations, reviewer approvals, evidence lineage, review status, and decision rationale through governed workflows.

🔄 Convert Insights into Action • Route literature findings through scientific review, Medical Affairs workflows, and decision-making processes.

📊 Measure Business Impact • Track review cycle times, throughput, adoption, knowledge reuse, and decision latency through dashboards and scorecards.

💡 Why QuickElevate – BioMed?

🧠 AI-Powered Literature Discovery • Discover relevant scientific publications, conference abstracts, trial data, and biomarker evidence across approved sources.

📖 Scientific Evidence Synthesis • Generate structured, source-grounded summaries from multiple publications and evidence sources.

🔍 Comparative Literature Review • Compare research papers and identify similarities, differences, contradictions, evidence gaps, and supporting findings.

📚 Knowledge Management • Organize scientific evidence using curated knowledge repositories and reusable evidence assets.

⚙️ Scientific Workflow Automation • Enable review routing, reviewer assignment, approval workflows, evidence package generation, and action tracking.

📈 Executive Dashboards & Reporting • Track scientific review productivity, evidence quality, review throughput, adoption, and decision impact.

📦 Representative Use Cases

✅ Oncology Literature Discovery

✅ Medical Affairs Evidence Review

✅ Clinical Development Support

✅ Competitive Scientific Intelligence

✅ Regulatory & Scientific Review Support

🎯 Ideal For

Research & Evidence Generation

• Research Scientists
• Literature Review Specialists
• Translational Research Teams
• Evidence Generation Leads

Medical Affairs

• Medical Affairs Leaders
• Medical Directors
• Scientific Communications Teams

Clinical Development

• Clinical Development Leads
• Study Team Leaders
• Clinical Program Managers

Regulatory & Governance

• Regulatory Affairs Teams
• Quality & Compliance Teams
• Scientific Governance Teams

🚀 Expected Business Outcomes

• Literature review cycle time improvement
• Evidence discovery speed improvement
• Evidence synthesis effort reduction
• Scientific review throughput improvement
• Source-grounded evidence quality enhancement
• Insight-to-action conversion acceleration
• Knowledge asset reuse increase
• Scientific decision readiness improvement
• Scientific team productivity improvement
• Competitive intelligence responsiveness improvement

🤝 Why Persistent + Amazon Quick

Persistent combines deep Life Sciences expertise with Amazon Quick's AI-native research, retrieval, synthesis, workflow automation, and business intelligence capabilities to establish a governed Scientific Intelligence operating model.

Key differentiators include:

• Purpose-built scientific evidence workflows
• Audit-ready governance and traceability
• Life Sciences domain expertise
• Workflow automation and review governance
• Performance measurement and continuous improvement capabilities