DistillerSR Launches the Industry's Most Advanced GenAI Capabilities for Extracting Scientific Literature Evidence

DistillerSR's Smart Evidence Extraction Now Fully Automates Text and Table Data at Scale

OTTAWA, ON / ACCESS Newswire / April 8, 2026 / DistillerSR, the market leader in AI-enabled literature review automation and evidence management, today announced new fully automated capabilities for its Smart Evidence Extraction (SEE) module. SEE uses purpose-built GenAI to automate end‑to‑end workflows for extracting evidence from scientific literature at scale, while maintaining full auditability and human governance over AI‑generated outputs.

As the volume of published research continues to grow exponentially, research teams in the pharmaceutical and medical device industries face increasing pressure to monitor evidence with speed and precision. SEE enables research professionals to accurately find, suggest, explain, extract, and link the supporting evidence within the reference in a human-in-the-loop and fully automated workflow.

"The latest version of SEE is designed to move research teams from reactive to proactive evidence strategy," said Peter O'Blenis, CEO of DistillerSR. "By automating the most time-consuming and error-prone aspects of data extraction, we are helping our customers deliver life-saving research to markets and patients more cost effectively, and with greater transparency and confidence."

New SEE functionality includes:

• Full Form Automation: SEE now completes and submits entire extraction forms automatically, replicating a human reviewer's workflow to significantly reduce manual labor.

• Enhanced Accuracy & Scope: The latest version of SEE demonstrated an 8.3 percentage point overall improvement on the standardized literature question-answering (LitQA) benchmark compared to its previous version, which is well above comparative benchmarks.

• Contextual Processing: Simplified prompting allows SEE to process all questions in a form simultaneously, allowing it to understand the full context of the extraction form and the relationships between variables for improved accuracy and consistency.

• Explainable AI: To facilitate regulatory compliance and trust, SEE provides plain-language explanations for every suggested answer, including full auditability of AI-extracted data.

• Real-Time Monitoring: An AI Dashboard enables teams to track and manage usage, while monitoring AI costs in real time.

• Adherence to AI Product Standards: Extracted data is fully hosted within DistillerSR's secure platform with zero customer data used for model training. The company has adopted the NIST AI Risk Management Framework to govern the design, deployment, testing, and validation of DistillerSR AI capabilities.

The latest iteration of SEE marks a significant milestone in DistillerSR's three-year Eureka-ITEA research consortium, the world's largest international research and development network representing 45 countries. The six-country research consortium is led by DistillerSR, and includes Philips Medical Systems, University of Leiden Medical Center, Bosonit,Dataseen BV, Össur, Adelphi Group, Biotronik, and DrugBank. Consortium members are working together to build AI-enabled workflows for research organizations that integrate Agentic AI, enrich underlying evidence with standard clinical and ontologies, and support the EU's healthcare data spaces initiatives.

DistillerSR is trusted by global research organizations, including more than 80% of the largest pharmaceutical and medical device companies, contract research organizations, governments, NGOs, and academic institutions.

About DistillerSR
For more information, visit www.distillersr.com.

DistillerSR Inc. Media Contact:
Vivian MacAdden
vivian.macadden@distillersr.com

SOURCE: DistillerSR Inc.

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