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DistillerSR
AI-Enabled Literature Review Automation Software

What is DistillerSR?

DistillerSR is a software platform specializing in the automation and management of literature reviews, incorporating Artificial Intelligence to enhance efficiency and accuracy. It is designed for research organizations across various sectors, including academic institutions, medical device manufacturers, pharmaceutical companies, and public sector entities. The platform streamlines the entire literature review lifecycle, aiming to significantly reduce the time required for review processes while ensuring the results are defensible and compliant with regulatory standards.

The system emphasizes transparency and traceability by tracking all actions within the review process, making it suitable for audits and regulatory submissions. DistillerSR offers highly configurable workflows, allowing adaptation to specific research protocols and team structures. It is built to handle large volumes of data, supporting projects with hundreds of thousands of references, and maintains high standards for security and compliance, being SOC-2 certified and GDPR-compliant.

Features

  • AI-Enabled Workflow: Seamlessly integrates AI into all aspects of the literature review process.
  • Automated Review Management: Streamlines the entire literature review lifecycle.
  • Configurable Workflows: Supports customizable protocols, workflows, and team configurations.
  • Audit-Ready Tracking: Records 100% of searches, references, changes, and data for transparency.
  • Scalability: Capable of supporting projects with over 675,000 references.
  • Enterprise-Grade Security: SOC-2 certified and GDPR-compliant platform.

Use Cases

  • Conducting systematic literature reviews for academic research.
  • Managing literature evidence for medical device regulatory submissions (e.g., CERs).
  • Streamlining pharmacovigilance literature reviews.
  • Supporting evidence-based health policy decisions in the public sector.
  • Accelerating research for Health Economics and Outcomes Research (HEOR).
  • Improving efficiency in evidence synthesis for Health Technology Assessment (HTA).
  • Facilitating collaborative research projects within large teams.

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