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One thing that I'd point out is that this comes entirely from the press rather than the startup - we see ourselves in a totally different sub-industry from Theranos (Athelas is a single type of blood test, at-home device, specifically for oncology patients, and a totally different technology). Really the only common word is "blood", but unfortunately I think that often gets drowned out in the media

The $20/mo is for the device and the test strips per month, as such the device is rented. Each subscription comes with 10 test strips a month usable between different users!

CTCs are a very early application in our tech and one that we're excited to continue working on. We have some strong sample share relationships with Stanford and sensitivity/stage/specificity testing is in its early stages right now. Will publish on the data page when more information

We're working under the 510k Class 1 and Class 2 framework

Thank you!

Great questions

-The first line of defense against interstitial fluid is wiping away the first drop (commonly used protocol in most drop test). The inevitable remaining interstitial fluid chunk is then classified out by our image processing models, which have been trained to recognize differences in images based on debris/cell concentration.

-We currently report the WBC, WBC Differential, Platelets, and RBC indices. The flags we're missing are secondary RBC metrics like MCH and RDW estimates but we have plans to roll these out soon as well.

-Yes, we've run both bench and clinical testing on patients with north of 100k white blood cells - the image processing can segment out cell chunks in these crowded samples better than traditional flow cytometry. Not in the currently published studies, but some good data coming out about this soon.

-We've run basic initial tests on platelet clumping (artificially induced in certain diluted samples), and present in clinical samples. Since our model looks at the boundaries of these platelet cells, we have a lot less trouble with this than flow cytometry/beckman and even human pathologists. Still, we're working to find more samples with clumping to define the limits of detection on this front.

-We've done interference studies with Hemolysis, EDTA, not with lipemia and icetrus. These are on our list of clinical samples to source as well.

-We've begun working with some of these EMR providers, the good thing is many of them have sandboxes to get setup in relatively quickly. The larger ones do have long, long-term engagement timelines.

-We work with dozens of pathologists to help review results, train the system further, and in general go over good morphology practice. Has definitely been a core part of our strategy.

Does anyone know why a side-view of the actual touchdown (like they usually release after) hasn't been posted by SpaceX yet?