Wednesday, June 21, 2023
Aiosyn, a company that specializes in medical software and focuses on AI-driven pathology solutions, has unveiled its inaugural AI algorithm as part of its Mitosis product line: Aiosyn Mitosis Research. This groundbreaking deep-learning algorithm is specifically developed to autonomously analyze whole slide images obtained from cancer biopsies and resections. Its primary objective is to aid research pathology laboratories in identifying cells undergoing division (known as mitoses) by detecting mitotic figures. Furthermore, Aiosyn is currently in the process of clinically validating the second algorithm in the Mitosis family, Aiosyn Mitosis Breast, which is intended for diagnostic purposes.
"We are excited to introduce Aiosyn Mitosis Research, our AI-powered solution for mitosis detection, which aims to enhance the efficiency and consistency of results in cancer research," states Patrick de Boer, CEO of Aiosyn.
Counting mitotic figures in histological slide preparations has long been a challenging and subjective task with limited reproducibility. By utilizing AI technology, our mitosis detection solution empowers laboratories to implement a more standardized and efficient protocol for biomarker discovery and drug development studies. This advancement improves the quality and standardization of results by effectively identifying mitotic figures in hematoxylin and eosin (H&E) slides before they are reviewed. Mitosis analysis is a critical biomarker for evaluating tumor growth.
Aiosyn Mitosis Research is a flexible and modular software solution that can be integrated into existing digital pathology software. It can be deployed via the cloud or on-premises installation, accommodating various laboratory setups. This release represents a significant milestone for Aiosyn, following the successful launch of AiosynQC, an automated quality control (QC) tool that streamlines the digital pathology workflow.
Aiosyn is currently in the validation phase for another product in the Mitosis product family, Aiosyn Mitosis Breast, designed for clinical diagnostics. These solutions, along with a portfolio of deep learning algorithms in development, aim to improve diagnostic precision and quality for different pathologies where there is a clear need.