EFTA02572473.pdf
dataset_11 pdf 209.7 KB • Feb 3, 2026 • 3 pages
From: Steven Sinofsky < I=>
Sent: Thursday, November 2, 2017 10:24 PM
To: Masha Drokova
Cc: Jeffrey E.
Subject: Re:
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 9:31 AM, jeffrey E. <jeevacation@gmail.com> wrote:
=br>
steve can you give=some guidance
On Wed Nov 1 2017 at 12:20 PM, Masha Drokova
target="_b rote:
EFTA_R1_01742096
EFTA02572473
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/095O93D3IJArEbnisdll4elVob0U/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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Unauthorized use, disclosure or copying of this
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including all attachments. copyright -all rights r=served
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