Sight Diagnostics, an Israeli medical devices startup in Jerusalem that’s using computer vision and machine learning technology to speed up blood testing, is launching a point-of-care blood diagnostics system.
It claims the compact, desktop machine — called OLO — which analyzes single-use cartridges manually loaded with drops of the patient’s blood, can deliver lab-grade complete blood count (CBC) tests from only a finger prick of blood.
The idea being for clinicians to use the device to perform the most prevalent medical blood diagnostics test directly in their office, rather than a patient having venous blood drawn and sent away to a lab for analysis — a process that can take a few days.
They’re also intending to offer a high tech alternative to carrying out manual microscopy on a blood smear — another technique that can be used to conduct an point-of-care CBC test, but which requires specialist personnel taking the time, care and attention to get it right.
The team hasn’t previously disclosed total funding but are now confirming they’ve raised $25 million in equity financing (Series A and B) from VC firms, including Eric Schmidt’s Innovation Endeavors — which they say they’re expecting to take them through their US clinical trials. They are also in the process of raising a Series C.
Sight Diagnostics is touting OLO as the high tech alternative that healthcare providers have been waiting for — with AI-powered analysis performing a blood count right then and there, after a healthcare worker has pipetted a few drops of the patient’s blood into place.
Sight Diagnostics points out that CBC tests are used to diagnose a broad range of common medical conditions, as well as for the vast majority of baseline tests ordered during routine ‘well visits’, arguing that speeding up this type of routine blood test could support faster diagnostics of medical problems. Or, indeed, speedier reassurance that a person is okay.
The OLO system uses a patented process for ‘digitizing’ patient blood into a set of specifically colored microscope images. It then applies proprietary machine vision algorithms to the images to identify and count different blood-cell types — with the company claiming its technology simplifies blood testing so that even non-professionals can perform the tests.
According to the company, new sample-preparation methods allow them to present a small amount of blood to OLO’s microscope in a way that is tolerant to inaccuracies in the preparation process — placing what they describe as “minimal burden” on the user — as well as being robust in the face of inaccuracies in any manufacturing processes, saying this means the cost of their testing kits can remain low.
“This novel way of digitizing blood is equally important to our approach as the artificial intelligence driving the analysis,” they add.
Of course any novel blood testing technology claiming a disruptive advantage must be able to prove it is as accurate and robust as traditional lab testing methods.
Very clearly, lives are at stake.
And, well, on the disruptive startup side, the shadow cast by Theranos’ implosion is a very long one.
But — to be clear — Theranos had claimed it could deliver a full battery of laboratory tests from a few drops of blood — not just a CBC count, which is at least the initial aim for OLO. And for CBC tests having only a small blood sample to work is actually not so unusual.
“CBC tests operate even today with low sample volumes,” it says. “For example, several central-lab instruments have been cleared for capillary samples (200-300uL of blood, of which less than 10uL is actually counted), and the older manual method for CBC analysis — the traditional blood smears on microscope slides — uses less than 10uL of blood in total. This is to say that in our domain the use of low sample-volumes stands on solid scientific ground.”
Sight Diagnostics has been working on the OLO system for more than eight years at this stage.
The co-founder duo — Yossi Pollak and Daniel Levner — combine machine vision and AI expertise on the one hand (Pollak worked on algorithms for automotive machine-vision giant Mobileye), with a medical background, via Levner’s postdoctoral fellowship at Harvard Medical School (and later a CTO role at a biotech company, called Emulate).
Their key claim is that OLO produces “lab-quality” CBCs.
Recently, DCL Laboratory Product Limited announced a collaboration with Sight Diagnostics Limited (SightDX) Israel, to introduce the Parasight Malaria Detection Platform in Nigeria and Ghana.
Through this agreement DCL will market the Parasight Platform in the Nigerian diagnostics market, adding to DCL’s extensive infectious disease diagnostics portfolio in the country.
Speaking at a workshop on the introduction of the revolutionary malaria diagnostic machine in Abuja, Chairman, DCL Group, Mr. Charles Anyanwu, said the collaboration is aligned with firm’s purpose of advancing the world of health by bringing technology solutions for malaria diagnosis to West Africa.
Source – Tech Crunch https://techcrunch.com/2018/07/12/sight-diagnostics-launches-an-ai-based-diagnostics-device-for-faster-blood-tests/
