Qlarity Imaging will focus on the further development of QuantX, which is claimed to be the first FDA-approved computer-aided breast cancer diagnosis system in radiology.

QuantX incorporates images from multiple modalities to help adiologists assess and characterise breast abnormalities.

Qlarity Imaging, which is Paragon’s seventh portfolio company, will also work to expand the diagnostic applications of its AI technology to additional image modalities and medical conditions to improve patient care and reduce lowering costs for hospitals and payers.

QuantX is the medical imaging AI system with innate displays, advanced analytics, and machine learning. It was initially developed at the University of Chicago based on research of Dr Maryellen Giger and incubated at Quantitative Insights, a startup launched with the support of the University of Chicago’s Polsky Center for Entrepreneurship and Innovation.

According to the company, a clinical study showed the effectiveness of QuantX at helping radiologists interpret cancerous and non-cancerous breast lesions, and lead to a 39% reduction in missed breast cancers without a reduction in specificity and 20% overall diagnostic improvement.

Paragon said its capabilities and investment in Qlarity Imaging provide it with the working capital required to further develop and implement its computer-aided diagnosis system and assess expanded uses of AI-enabled diagnostic tools.

Paragon, along with its financial partners, has invested and committed more than $500m over the last 18 months to support its portfolio companies in the development of novel therapies and diagnostic tools.

Paragon Biosciences chairman and CEO Jeff Aronin said: “By driving innovation across life sciences, Paragon fulfills its mission of improving outcomes for patients with severe medical conditions. So, we’re pleased to help further develop the first FDA-cleared, artificial intelligence-enabled diagnostic software for breast cancer MRIs.

“We are entering an exciting time where advances in supercomputing and machine learning make it possible for artificial intelligence to deliver on its promise for drug discovery, drug development, and diagnostics.”