 IDx eye diagnostics

the IDx-DR AI system was evaluated using surrogate markers of diabetic retinopathy – akin to a doctor measuring cholesterol levels as a surrogate marker for the future risk of cardiovascular disease – rather than compare it directly with a physician-made clinical decision. ‘That’s pretty unique for AI – though standard in drug trials – because physicians are almost never validated against outcomes.’ Abramoff believes truly autonomous AI

could address three of the major issues with healthcare today; quality, cost, and access. ‘Autonomous AI can increase productivity and quality, drive down prices, and improve access because you can now have a diagnosis or therapy in environments where healthcare is unevenly distributed.’ Every other AI system approved by FDA to date has been an assistive AI technology, he pointed out, but while assistive AI can aid in image evaluation or assess other patient data, there is still the need for a healthcare professional or specialist to make that final clinical decision. ‘At the end of the day this doesn’t address issues of cost and access, or, indeed, quality.’ IDx then had to work with bodies including the American Medical Association, the American Academy of Ophthalmology, and many other organisations in the healthcare system to set up a payment process. There had never been a situation where a CPT code, which is required for billing, had been issued | @scwmagazine

for a process without a human element, Abramoff noted. The consideration was, then how do you value the time and expertise of machines and software? ‘Fortunately, within eight weeks we had at least achieved a temporary bridging CPT code so that providers could bill and pay for use of the IDx-DR system, but it took months of discussions before we were granted a CPT code in May 2019. It was as big a hurdle to overcome as FDA blessing.’ American Diabetes Association

acceptance of the IDx-DR platform diagnosis as part of standard of care for people with diabetes is also a ‘huge’ milestone Abramoff noted. ‘It often takes 8 to 10 years for new technology to become part of a standard of care. Importantly, the system has been well received both by patients and the medical community, despite initial concerns that the use of autonomous AI diagnosing could put clinicians out of jobs. ‘Which is why, 10 years ago, I was given the nickname ‘the Retinator,’ Abramoff acknowledged. Today, the firm is witnessing mass adoption of the IDx-DR platform, and is rolling out the platform. ‘We are in an exciting phase of getting the system out there as rapidly as we can, so that it can be broadly implemented.’ In parallel, IDx-DR is working to develop additional autonomous AI systems that will bring specialty healthcare to the point of retail and primary care, Abramoff explained. ‘We want to empower primary care

physicians to do more for their patients using AI, where they have limited expertise, and to feel safe doing these things. That’s why we focus on products that really lift diagnosing and therapeutic expertise from specialists, like me, to primary and point-of-care settings. Critically, this is not ‘glamour AI,’ which is technologically exciting and ‘cool’, but does not improve patient outcome, and which doesn’t have any follow through. We believe autonomous AI systems must be embedded in the healthcare system so they are part of the continuum of patient care.’

In parallel with rolling out the IDx-DR

system, the company is also developing algorithms for detecting age-related macular degeneration (AMD) through retinal scans, and diagnosing glaucoma through the use of optical coherence tomography. The IDx-AMD, and IDx-G systems are projected for clinical trials during 2020 or 2021, Abramoff indicated. The firm is in addition working on AI algorithm prototypes for diagnosing ear infection and skin cancer risk. Away from its own product development,

IDx is using its experiences to help non-competing companies negotiate development and regulatory hurdles of other autonomous AI platforms, through what Abramoff calls an autonomous AI coalition. ‘There’s a lot of challenges that these companies will have to overcome, which we can help them with.’

Spring 2020 Scientific Computing World 23

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