DistillerSR Launches Regulatory-Grade Smart Screening for Titles and Abstracts

via ACCESS Newswire
ⓘ This article is third-party content and does not represent the views of this site. We make no guarantees regarding its accuracy or completeness.

Fully Automated, AI-Enabled Screening Delivers Unprecedented Productivity to Evidence Generation Teams.

OTTAWA, ON / ACCESS Newswire / September 10, 2026 / DistillerSR® Inc., the pioneer and market leader in AI-enabled literature review automation and evidence management, today announced the official launch of Smart Screening, a new capability that brings regulatory-grade GenAI to title and abstract screening within the DistillerSR platform. Smart Screening enables pharmaceutical, medical device, and research teams to accurately screen large volumes of abstracts automatically, with full auditability and human governance over AI-generated outputs, in either human-in-the-loop or fully automated workflows.

As published research volumes continue expanding exponentially, pharmaceutical and medical device research teams face mounting pressure to conduct first-pass abstract screening faster without sacrificing recall, accuracy or auditability. Smart Screening's purpose-built GenAI capability reads and evaluates abstracts and automates screening decisions at scale, within the same DistillerSR workflow configurations users already know and trust.

"Smart Screening brings the same trusted technology used in Smart Evidence Extraction (SEE) to title and abstract screening", said Peter O'Blenis, CEO of DistillerSR. "These capabilities are fundamentally reshaping evidence generation, dramatically accelerating research, regulatory and safety practices. The result is faster access for patients to life-changing medical products."

Regulatory-Grade AI Built for the Way Research Teams Work

Smart Screening is built on the same purpose-built GenAI backend as DistillerSR's Smart Evidence Extraction (SEE) module, ensuring consistent and accurate AI outputs across the complete literature review workflow. In a Philips baseline pilot study, Smart Screening reached 90.1% average accuracy prior to any prompt optimization*. New Smart Screening capabilities include:

  • Full Automation that batch-processes up to 100,000 abstracts per run with fully automated AI screening decisions and built-in audit trails.
  • Human-in-the-Loop Workflow that enables expert reviewers to maintain oversight of every AI decision for high-stakes regulatory submissions, with all AI and human activity fully tracked.
  • No Workflow Disruption, working within existing DistillerSR form configurations with no additional setup required.
  • No Model Preparation or Training. Smart Screening works right away, on all references, without any training as to inclusion/exclusion criteria.
  • Secondary AI Error Checking, leverages an additional, independent AI to validate the screening decisions made by the primary AI.
  • Regulatory-Grade Auditability that provides a fully traceable rationale for every inclusion and exclusion decision, supporting defensible regulatory submissions and notified body audits.
  • Secure by Design, ensuring customer data is never used for third-party model training, with copyright obligations fully respected.

About DistillerSR

DistillerSR is the pioneer and market leader in AI-enabled literature review automation and evidence management. Today, more than 80% of the world's largest pharmaceutical and medical device companies trust DistillerSR to securely produce transparent, audit-ready and regulatory-compliant literature reviews. The DistillerSR platform and modular ecosystem enable customers to securely automate the management and analysis of evidence-based research: faster, more accurately, more transparently, and at scale.

For more information, visit www.distillersr.com.

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

SOURCE: DistillerSR Inc.



View the original press release on ACCESS Newswire

Report this content

If you believe this article contains misleading, harmful, or spam content, please let us know.

Report this article