EFTA02572517

From: jeffrey E. <[email protected]> Sent: Thursday, November 2, 2017 10:26 PM To: Steven Sinofsky Subject: Re: thx On Thu, Nov 2, 2017 at 6:24 PM, Steven Sinofsky wrote: Greetings Masha, I apolo=ize for the delay. I was at some events in in UK where I did not hav= connectivity. I have worked on a related portfol=o company so I will have to be a bit abstract on the specifics of this opp=rtunity. So please excuse these brief thoughts. Also, the only infor=ation I had was what was provided in your mail which was limited relative =o any detailed analysis. * In general the challen=e with glucose measurement is the finger prick. Any device that relies on =his will only be marginally better than any other device, whether or not t=ere is software or a slightly more convenient measuring device. This is a =tatement about the inconvenience of a prick (and long term challenges) but=also the medical challenges on relying on that point in time. * =y sense is that going down the path of an innovation, that still has a pri=k, but requires a level of FDA approval is a difficult one to approach. " This is a very crowded space. There are a lot of apps, a lot of m=asuring devices, a lot of mixtures of app and measuring devices. It is ver= difficult to avoid appearing as a commodity to consumers. * Whi=e I understand there is potential to see innovation using novel approaches=to analysis of data, it is not clear to me how much better the approach ca= be for an individual with data. * The real opportunity I might =ee is around measuring glucose or some related telemetry to assist in comp=iance that is outside the scope of a finger prick and measuring glucose di=ectly. It seems like we should have some other data point upon which to ap=ly machine learning. I hope this helps...any frie=d of JE is a friend of mine. On Nov 1, 2017, at 4:43 PM, Mas=a Drokova wrote: https://drive.google.com/file/d/065O93D3IJArEbXBsdll4eIV=b0U/view Our memo: https://docs.google.com/document/d/1M7ZV7VEI8CTnb4EtYWFH2sq5dc=m0PM6g1AlcwrIOtM <https://docs.google.c=m/document/d/1M7ZWVEI8CTnb4EtVWFH2sq5dcCm0PM6g1AlcwrIOtM> EFTA_R1_01742151 EFTA02572517 Center Health is bu=lding an Al-based glucose monitoring system for the 1 in 11 Americans=who suffer from diabetes, based on machine learning and their personalized=Al, Aria. Users subscribe to their disposable test strips, a $148/yr =S market, which are delivered monthly, as Aria learns about their diabetes=and prompts behavioral changes to lower blood sugar. The system =s an order of magnitude cheaper than existing technologies, premised on le=eraging data to help users see what daily elements are affecting thei= blood sugar, and predicting dangerous highs and lows before they happen..C2. Pros — Existing gluco=eters from big companies are very old-fashioned and outdated, those compan=es make their revenue from overpriced strips — Direc= competitors, such as i Health and Dario have negative customer=reviews and minor — Uses FDA-approved circuits to get the ap=roval in an automated manner Cons — Enormous pressure both from the industry players an= companies such as Apple and Google that try to develop non-invasive gluco=e monitoring that will wipe out test strip products Q=94 Hardware startup without a product to sell yet, finalizing the developm=nt — Young team c/=iv> conversation-id 25269 date-last-viewed 0 date-received 1509661553 flags 8590195713 gmail-label-ids 7 6 remote-id 764693 2 EFTA_R1_01742152 EFTA02572518