Intelligent Systematic Literature Review

The Intelligent Systematic Literature Review accelerates the process of conducting systematic literature reviews (SLRs), which are essential for generating high-quality evidence used in Medical Affairs, Pharmacovigilance, Regulatory, and other fields. Traditional manual SLRs can take extensive time, delaying critical decision-making. This solution automates the entire SLR process, from initial screening to citation tagging, using advanced AI technology.

By automating these processes, the system improves the accuracy of screening decisions, surpassing FDA accuracy thresholds and outperforming human-only workflows. It allows teams to collaborate on literature reviews through a single interface, facilitating more aligned decision-making based on real evidence.

Key Benefits

• Accelerate Evidence Generation & Synthesis: Automatically deduplicate abstracts, prioritize relevant abstracts, and screen citations quickly using PICO criteria. Add notes and download tagged citations for deeper analysis.
• Exceed FDA Standards: Achieve higher accuracy in inclusion/exclusion decisions and auto-generate PRISMA flow diagrams. Mitigate review bias with access to a wide range of literature sources.
• Utilize Gold-standard Evidence: Access comprehensive, unbiased evidence for payer decisions and maintain alignment with a centralized analytics dashboard and custom review workflows.

The system's AI capabilities are specifically tuned for scientific content, enabling rapid evidence screening and bias mitigation. It features AI-powered abstract deduplication and screening, which highlights important abstracts and color-codes citations. The collaborative interface allows teams to review citations, add notes, and track progress, while customizable review workflows support single, dual, and multi-collaborator processes.

With this platform, outdated manual SLRs are replaced by a more efficient, AI-driven approach, allowing teams to keep pace with the latest evidence. The medically intelligent AI assistant aids in understanding complex medical topics, facilitating faster and higher-quality evidence synthesis. The platform also centralizes scientific literature, enabling real-time trend monitoring and extraction of key information.