<table><tr><th>From:</th><th>Steven Sinofsky &lt; I=&gt; </th></tr><tr><td>Sent:</td><td>Thursday, November 2, 2017 10:24 PM</td></tr><tr><td>To:</td><td>Masha Drokova</td></tr><tr><td>Cc:</td><td>Jeffrey E.</td></tr><tr><td>Subject:</td><td>Re:</td></tr></table>

Greetings Masha,

=br>

I apologize for the delay. I was at some events in in U= where I did not have connectivity.

I have worked o= a related portfolio company so I will have to be a bit abstract on the spe=ifics of this opportunity. So please excuse these brief thoughts. Als=, the only information I had was what was provided in your mail which was l=mited relative to any detailed analysis.

* In gene=al the challenge with glucose measurement is the finger prick. Any device t=at relies on this will only be marginally better than any other device, whe=her or not there is software or a slightly more convenient measuring device= This is a statement about the inconvenience of a prick (and long term chal=enges) but also the medical challenges on relying on that point in time.

* My sense is that going down the path of an innovation, that still h=s a prick, but requires a level of FDA approval is a difficult one to appro=ch.

* This is a very crowded space. There are a lot of apps, a lo= of measuring devices, a lot of mixtures of app and measuring devices. It i= very difficult to avoid appearing as a commodity to consumers.

*=While I understand there is potential to see innovation using novel approac=es to analysis of data, it is not clear to me how much better the approach c=n be for an individual with data.

* The real opportunity I might s=e is around measuring glucose or some related telemetry to assist in compli=nce that is outside the scope of a finger prick and measuring glucose direc=ly. It seems like we should have some other data point upon which to apply m=chine learning.

I hope this helps...any friend of Jr. is a friend of mine.

On Nov 1, 2017, at 4:43 PM, Masha Droko=• &=t; wrote:

Thank yo= Jeffrey. Steve, great meeting you. Would appreciate your f=edback

On Nov 1, 2017, at 9:31AM, jeffrey E. <jeevacation@gmail.com> wrote: =br>

steve can you give=some guidance

<u>On Wed Nov</u> 1 2017 at 12:20 PM, Masha Drokova
target="_b rote:

I'm l=oking to invest at the company doing AI-based glucose monitoring system for=people with diabetes. We made tech evaluation, talked to a few expert= and more a question about the market and regulations. likely no, bec=use it's complex area, but still thinking of them.

<=pan style="background-color:rgba(255,255,255,0)">

May be someone in your ne=work who knows this area and can advise on this kind of tech?

<=div>

Center Health

Deck: https://drive.google.com/file/d/0B5O93D3IJArEbXBsdll4elVob0U/view

<=pan>Center Health is building a= Al-based glucose monitoring system for the 1 in 11 Americans who suff=r from diabetes, based on machine learning and their personalized Al, =ria. Users subscribe to their disposable test strips, a $14B/yr US market, w=ich are delivered monthly, as Aria learns about their diabetes and prompts b=havioral changes to lower blood sugar. The system is an order of m=gnitude cheaper than existing technologies, premised on leveraging data to h=lp users see what daily elements are affecting their blood sugar, and p=edicting dangerous highs and lows before they happen. </=iv>

Pros

— Existing glucometers from big companies=are very old-fashioned and outdated, those companies make their revenue fro= overpriced strips — Direct competitors, such as =/span>iHealth and Dario have negative customer reviews and minor —&=bsp;Uses FDA-approved circuits to get the approval in an automated manner</=ont>

=i>Cons

— Enormous pr=ssure both from the industry players and companies such as Apple and Google=that try to develop non-invasive glucose monitoring that will wipe out test=strip products <=ont face="Roboto-Regular">— Hardware startup without a product to=sell yet, finalizing the

development

— Young team =

please not=

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