Aiosyn Secures Funding to Advance AI Cancer Diagnostics
Dutch medical software company Aiosyn has successfully raised €2.4 million in funding from investors including TNO Ventures, Oost NL, LUMO Labs, and Health Innovations. This investment supports Aiosyn’s mission to accelerate the development and adoption of artificial intelligence solutions in cancer diagnostics, with a focus on improving the accuracy and efficiency of tumor detection and classification.
Strategic Partnerships Drive Innovation
A significant milestone for Aiosyn is its strategic partnership with TNO, the Netherlands Institute of Applied Scientific Research. This collaboration enables access to TNO’s extensive AI expertise and research capabilities, facilitating rigorous clinical validation of Aiosyn’s AI-powered software. According to Aiosyn’s leadership, combining industry innovation with TNO’s scientific resources expedites Aiosyn’s readiness for market expansion and enhances the reliability of its diagnostic tools.
Transforming Pathology with AI
Aiosyn’s precision pathology software harnesses AI to automate and augment the analysis of histopathological images. The technology delivers measurable benefits, including up to 50% reduction in time required for mitosis detection, improved productivity for pathologists, and increased consistency across diagnostic assessments. Their software, Aiosyn Mitosis Breast, which holds the CE mark, is a notable example, providing validated performance in breast cancer diagnostics. This certification underlines the clinical reliability and regulatory compliance of their AI system.
The Future of AI in Clinical Practice
Looking ahead, Aiosyn envisions AI-integrated diagnostics as a foundational component in cancer care pathways. The convergence of AI with pathology aims to improve patient outcomes by delivering faster and more precise diagnostic insights, ultimately supporting personalized treatment plans. Through collaborations like that with TNO and ongoing developments, Aiosyn contributes to reshaping clinical decision-making and streamlining medical workflows in oncology.
