This media release was originally published by Altis Labs on January 24, 2023.
Toronto, Ontario – Altis Labs, Inc. (“Altis”), the computational imaging platform for advancing precision medicine, announces today an initiative focused on developing, validating, and commercializing fully automated imaging biomarkers for solid tumors using deep learning.
Led by Altis, the initiative leverages a strong industry-academic coalition, comprising Bayer Canada, BC Cancer, Sunnybrook Research Institute, SapienSecure, Trillium Health Partners, University of Calgary, and University Health Network.
“We’re thrilled to lead this project with support from INOVAIT and our coalition members spanning industry and Canada’s leading health systems, who treat roughly half of Canadian cancer patients,” says Felix Baldauf-Lenschen, CEO of Altis.
Funding for this project is provided in part by INOVAIT through the Government of Canada’s Strategic Innovation Fund. Ce projet a été financé en partie par INOVAIT dans le cadre du Fonds stratégique pour l’innovation du gouvernement du Canada.
This initiative was one of 14 selected in the inaugural Focus Fund call for applications and will receive up to $2.0 million in INOVAIT contributions. Altis and its coalition members expect to contribute $4.0 million towards this initiative over three years, while further enriching clinical datasets across various tumor types.
“By continuing to grow and enrich the world’s largest cancer imaging dataset with associated clinical information like molecular diagnostics, treatment history, and outcomes, we’re enabling the development of powerful imaging biomarkers,” adds Duoaud Shah, Altis’ Vice President of Clinical Partnerships. “Our goal is for these biomarkers to help researchers and clinicians significantly reduce the time and cost of developing efficacious cancer treatments and ultimately inform care that results in better patient outcomes.”
The INOVAIT Focus Fund aims to support three-year commercialization-focused R&D projects at the intersection of advanced imaging, minimally-invasive therapies and artificial intelligence. These innovations will use advances in data sciences and artificial intelligence to enhance image guidance and corresponding therapies.
About Altis Labs
Altis Labs is the computational imaging company advancing precision medicine. We believe that medical imaging, making up 90% of all healthcare data, is the richest source of clinical insight but vastly underutilized. Trained on over 140 million real-world images with associated clinical information, our software platform Nota provides users access to deep learning models that predict clinically meaningful outcomes from existing imaging scans. Life sciences companies use Nota to accelerate all stages of clinical development by more accurately stratifying patients and quantifying treatment effect.
To learn more, visit www.altislabs.com or reach out via [email protected].
About INOVAIT
INOVAIT is a pan-Canadian network funded by the Government of Canada and hosted at the Sunnybrook Research Institute with the objective of building a truly integrated image-guided therapy ecosystem, fueling continuous innovation that revolutionizes healthcare globally. Through connecting, educating, and investing in the industry’s brightest minds and most promising ventures, INOVAIT will support and encourage collaborative development and the integration of artificial intelligence (AI) into medical technologies.
Financé par le gouvernement du Canada et situé à l’Institut de recherche Sunnybrook, INOVAIT est un réseau pancanadien dont l’objectif est de créer un écosystème de thérapie guidée par imagerie véritablement intégré qui favorise l’innovation continue et révolutionne les soins de santé à l’échelle mondiale. Grâce à l’établissement de liens, à la formation et à la réalisation d’investissements au profit des plus brillants cerveaux et des initiatives les plus prometteuses du secteur, INOVAIT soutiendra et stimulera le développement collaboratif ainsi que l’intégration de l’intelligence artificielle (IA) dans les technologies médicales.
