Medlior is an independent Canadian health outcomes research consultancy specializing in real-world evidence (RWE), health technology assessment (HTA), evidence synthesis, and advanced analytics. Since 2008, we have partnered with pharmaceutical and biotech companies, non-profit organizations, health systems, and government agencies to generate high-quality, decision-ready evidence that improves patient outcomes and informs clinical, regulatory, and reimbursement decisions.
Our multidisciplinary team integrates expertise in epidemiology, biostatistics, health economics, clinical research, data science, and strategic advisory services. This breadth of expertise enables us to deliver end-to-end evidence solutions, including study design, data strategy, access and linkage, advanced analytics, evidence synthesis, economic modeling, and scientific communication. Across all projects, we prioritize methodological rigor, transparent reporting, and the ethical and responsible use of health data.
Beyond our client work, Medlior leads several initiatives designed to strengthen Canada’s digital health and research infrastructure. Among these are Real World Radar, a subscription platform that curates a listing of global real-world datasets for life-science research teams, and the EvidaHealth Foundation, a not-for-profit dedicated to advancing patient-centered data infrastructure and fostering collaborative, real-world evidence generation across the healthcare sector. Through these initiatives, we aim to support more accessible, scalable, and interoperable data ecosystems that accelerate innovation while maintaining strong governance and patient trust.
As the landscape of digital health and artificial intelligence continues to evolve, Medlior remains committed to integrating emerging technologies into evidence generation. Our current priorities include expanding AI-enabled workflows, enhancing data quality and interoperability standards, and contributing to national and international discussions on the responsible use of real-world data in healthcare decision-making.