CuriMeta transforms de-identified real-world health data from health systems and academic medical centers into actionable insights for life science researchers, enabling them to conduct non-interventional studies and novel clinical trial designs. By providing access to comprehensive patient cohort data, CuriMeta addresses the challenge of limited data availability that hinders scientific and therapeutic advancements.
Funding
$6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Life science researchers face challenges in accessing comprehensive, real-world health data needed for non-interventional studies and innovative clinical trial designs. Limited data availability hinders scientific and therapeutic advancements, slowing the pace of medical breakthroughs.
Solution
CuriMeta transforms de-identified real-world health data from health systems and academic medical centers into actionable insights for life science researchers. By curating, enhancing, and anonymizing multimodal data, including genetic variants, radiology, and pathology, CuriMeta provides researchers with comprehensive patient cohort data. This enables researchers to conduct retrospective and prospective studies, design novel clinical trials, and develop external control arms. CuriMeta's approach accelerates the pace of biopharmaceutical and life science research by providing better insights and more complete data to fuel studies.
Target Audience
CuriMeta's primary customers are life science researchers, bio-pharma companies, medical device companies, clinical research organizations (CROs), and clinical AI and digital health companies.
Features
- Access to multimodal real-world data, including genetic variants, radiology, and pathology data.
- Support for non-interventional retrospective and prospective studies.
- Expertise in study planning, feasibility, and design.
- Capabilities for novel clinical trial designs and external control arms.
- Provision of training datasets to support AI development.
- Application of privacy-preserving technologies to ensure patient data is de-identified according to regulatory standards.