An AI-powered tool to support the identification and selection of fit-for-use Real-World Data (RWD)

– 1 min read

An AI-powered tool to support the identification and selection of fit-for-use Real-World Data (RWD)

In the high-stakes environment of HTA and regulatory submissions, selecting the right Real-World Data (RWD) is no longer just a technical challenge—it is a race against time. To address this, Quinten Health is proud to showcase a breakthrough AI-driven methodology designed to streamline evidence planning and support critical decision-making throughout the product lifecycle.

 

The Objective

Enable faster, more reliable identification, pre-assessment, and pre-selection of fit-for-purpose RWD to support critical decision-making throughout the product lifecycle.

 

The Challenge: Navigating the RWD Wilderness

Finding fit-for-purpose RWD is often hindered by fragmentation. Data is buried across disparate catalogs and vast scientific literature, with key metadata remaining unstructured or shielded from public view. Traditionally, matching a specific research question to a viable data source is a manual process that can create bottlenecks lasting weeks.

 

Our Approach

We have developed an AI-powered single point of access tool to transform how life-science organizations approach data identification. This solution is built on three foundational pillars:

  • Centralization: We have bridged fragmented data sources from global catalogs and libraries into a unified repository, currently hosting over 37,000 references.
  • Automated Extraction: Leveraging Large Language Models (LLMs) and Natural Language Processing (NLP), we structure metadata from publications following the PICOTS model. We have achieved ≥90% accuracy for critical fields including registry names, medical condition, geographical area, and outcome measures.
  • Smart Identification: Our hybrid search engine combines semantic and keyword-based algorithms to pinpoint fit-for-use registries instantly.

 

The Impact : A “one-stop shop” for RWD identification

The result is a significant reduction in the time-to-insight. By automating the pre-assessment and pre-selection of data, we enable faster, more reliable decision-making throughout the product lifecycle.

 



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The Quinten Health Edge

With over 15 years of AI-native expertise, Quinten Health does more than just “find” data. Beyond our technical assets, we translate complex real-world landscapes into regulatory-grade evidence. Our mission is to shorten the time-to-impact for life-science organizations by mastering the bridge between raw data and smarter insights.

 

Funding Acknowledgement

This tool is a deliverable of the More-Europa consortium, funded by the European Union (Horizon Europe). Grant agreement number: 101095479.