In the life sciences industry, literature reviews are the foundation of evidence-based research and decision making. They play a critical role across the product lifecycle - from early discovery and clinical development to regulatory submissions, health technology assessments and ongoing medical strategy. By synthesizing and evaluating the published evidence, literature reviews inform decisions that drive scientific innovation, guide pharmaceutical and medical device development and ultimately improve patient outcomes.

The rigor that makes literature reviews essential also makes them slow, expensive and difficult to scale. Organizations must deal with the rapidly growing publication volume, heterogeneous data sources and necessary thorough expert oversight. Traditional literature review tools often support end‑to‑end workflow management and audit trails, but with limited automation. While general‑purpose generative AI or large language model (LLM)‑based tools may introduce automation, they may also lack the transparency, traceability and purpose‑built design required to reliably support each stage of a literature review and be scientifically rigorous.

IQVIA Literature AI Platform dramatically accelerated the literature review process, reducing timelines from months to days while improving the quality, consistency, and reproducibility of outputs. The Platform is powered by proprietary, domain-tuned Healthcare-grade AI^® agents that deliver expert-level performance beyond the capabilities of generic AI models.

Rather than replacing scientific judgment, the Platform automates the most labor-intensive aspects of the review process within a fully auditable, transparent and expert-led workflow. Each AI agent acts as an intelligent assistant at each stage of the review, from refining research questions and abstract screening, to full-text review, extracting evidence and drafting summaries. Human experts remain in control throughout, providing guidance, validation and feedback at every step.

This multi-agent, human-in-the-loop approach delivers greater methodological rigor, transparency and traceability than single-agent solutions. With the Literature AI Platform, organizations have reduced manual screening effort by 87% while maintaining 100% recall, reduced manual data extraction effort by 70%, and completed targeted literature reviews in a fraction of the time.

The IQVIA Literature AI Platform’s agentic architecture is made up of the following components:

• Orchestrator Agent: Serves as the central coordinator, interfacing with the user and coordinating the activity of other agents in the workflow.
• Researcher Agent: Refines the research question, helps define PICO (population, intervention, comparison, outcome) criteria, and develops robust Boolean search strategies to ensure comprehensive evidence retrieval.
• Searcher Agent: Executes a transparent and deterministic search strategy to surface relevant articles from a large, indexed and curated repository of scientific literature.
• Screener Agent: Evaluates retrieved articles against pre-defined PICO criteria, providing inclusion and exclusion recommendations along with confidence scores and clear evidence-based rationales.
• Extractor Agent: Extracts structured data and key findings from articles selected for inclusion, significantly reducing the manual effort required for evidence extraction.
• Insights Generator Agent: Generates a transparent, cited summary of evidence to provide an answer to the research question.

Increased Scientific Focus

Literature reviews will always require expert judgment. What the Literature AI Platform transforms is how researchers spend their time. Rather than focusing on labor-intensive, repetitive tasks, experts are empowered to concentrate on evidence interpretation, critical analysis and strategic insight, where human expertise delivers the greatest value

Through its specialized agentic architecture, the Platform provides AI assistants that support each stage of the literature review process while keeping experts firmly in control. This human-in-the-loop approach combines the speed and scalability of AI with the rigor, oversight, and scientific judgment required for high-quality evidence generation.

As the volume of scientific literature continues to grow and expectations for methodological rigor remain a critical priority, IQVIA Literature AI Platform enables faster, more scalable literature reviews without compromising transparency, traceability or quality.

For more information about the platform, read the fact sheet here.