Qclarity, produced by Paragon Biosciences, looks to improve the quality and speed of breast cancer diagnoses.
About 30 million women are screened for breast cancer each year in the US, yet the process always requires a stringent series of tests and drawn out, highly stressful, waiting periods between follow-up biopsies. After this, 75% of them come back not having found any cancer at all. But this harrowing process could be about to change forever with the development of QuantX, the first ever computer-aided breast cancer diagnosis system to be cleared by the FDA [1].
Longevity.Technology: AI systems and human radiologists make highly effective tag-teams, this development demonstrates further expansion of the approvals by the US FDA of AI-supported technologies.
The TRL score for this Longevity.Technology domain is currently set at: ‘Technology completes secondary trials and provides further evidence for safety and efficacy.‘
The TRL score for the technology addressed in this article is: ‘Late proof of concept demonstrated in real-life conditions.’
Spun out from research by Dr Mareyllen L Giger at the University of Chicago, QuantX was incubated at the startup Quantative Insights before being acquired by Qlarity Imaging and Paragon Biosciences. And now, having obtained FDA approval for breast cancer, the two companies are looking to expand the system’s applications to address more indications.
Once the early implementation phase of QuantX is completed, which is currently being developed for clinical use with the help of radiologists at the MD Anderson Cancer Center at the Universities of Texas and Chicago, who are using the AI alongside their own medical expertise to form more accurate and speedy diagnoses.
The vision Paragon Biosciences have is of AI and doctors working in tandem to diagnose patients, rather than the former replacing the latter. “Radiology is the backbone of diagnosing many diseases today,” says Jeffrey Aronin, Paragon chairman and CEO. “We believe the future is radiologists with technology.”
According to Paragon, a clinical trial has showed that the program is able to reduce missed breast cancers by 39% and produce a 20% improvement to the overall accuracy of the diagnoses it produces. If this is matched with a similar increase in speed, the results could prove to be even more beneficial to millions of women.
“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,” says Aronin.
