An interview on the Diabetes Research Hub with Juan Espinoza, Chief Research Informatics Officer at Lurie Children's Hospital and Associate Director of the Center for Biomedical Informatics and Data Science at Northwestern University, and Shahid Shah, CEO of Netspective Communications.
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David Klonoff (00:15):
Hello, this is Diabetes Technology Report.
I'm David Klonoff.
I'm an endocrinologist atSutter Health and UCSF.
I'm here today with my co-host,David Kerr, who has two very
special guests.
I'm going to introduce Davidand he will begin the interview.
David Kerr (00:33):
Thanks, david, and hello to everyone again.
David Kerr, speaking once morefrom Santa Barbara, california,
and we have two superstars ofdiabetes research and technology
on the podcast today.
We're very, very excited.
We're going to hear about a newinnovation that's planned
through the Diabetes TechnologySociety.
(00:53):
So welcome Shahid, welcome Juan.
It's lovely to see you todayand to hear from you and just to
really set the scene.
I'd like both of you just todescribe what's your day job,
really set the scene.
I'd like both of you just todescribe what's your day job.
But, more importantly, how didyou end up being interested in
diabetes in general and diabetestechnology specifically?
Shahid Shah (01:17):
Shahid, do you want to go first?
Sure, yeah, I'm a softwareengineer by training and I've
these days mostly doingentrepreneurship, in which I've
built and sold a few electronichealth record companies digital
technology but a lot of my workhas been in very specific types
of medical devices, you know,like insulin pumps or
respiration systems, and what wedeal with a lot is both in my
own family as well as a lot ofthe patients that we've helped
(01:40):
take care of with respect to ourmedical devices is always
related in some way to diabetesand other chronic conditions.
And so just a few years ago, drPlonoff and I met at an FDA
event, of all places, and hestarted talking a lot about what
the Diabetes Technology Societywas doing, and I was always
interested in diabetes just froma healthcare perspective, but
(02:02):
the fact that there was anactual society which just
focused on technology arounddiabetes was really what got me.
He had me at hello when he saidtechnology and diabetes in the
same sentence, and that's how wegot together.
David Kerr (02:17):
He's very persuasive indeed.
Juan, is your story similar orhow did you?
Is it different?
Juan Espinoza (02:23):
There are definitely some similarities.
So, uh, my day so I'm a generalpediatrician by training an
informaticist, my day job is I'mthe chief research informatics
officer.
Uh, and in robert h larrychildren's hospital, chicago, um
.
And I got interested indiabetes, uh, from the
perspective of it being acondition that was very much
(02:49):
probably at the forefront of theincorporation of technology and
data for disease management,especially if you think about 10
years ago.
Like no other disease useddevices and data to manage it.
Diabetes is this highlyquantified disease and has been
for a long time, and so for meit came along in this
(03:09):
professional side of like oh,this is an interesting problem,
I like data and technology.
Here's a disease with a bunchof data and technology.
Let me focus on it.
I was involved early on inefforts around CGME, hr
integration and sort of thinkingthrough innovative ways to
develop uh, uh, develop caremodels for diabetes, um, working
closely with the endocrinologyuh division at children's
(03:32):
hospital Los Angeles, where itwas at the time, and we
published a paper, uh about ourwork and building the first um
CGM EHR integration.
And one day I get an email froma guy named David Klonoff said
like oh, I saw your paper,that's really interesting.
We should talk and then youknow, four or five years later,
of fruitful collaboration.
(03:52):
We're here now working on thisproject.
David Kerr (03:54):
Excellent.
So this project, I mean, I takeit.
You mean the diabetestechnology meeting just the
other week in Burlingame.
There was a huge amount ofexcitement about something that
was new and being launched, andyou guys are starting this.
So, to avoid any delay, what isthis project all about?
What's this new project?
(04:15):
Shahid, do you want to startoff?
Shahid Shah (04:17):
Yeah, I'll just tell you from a quick tech
perspective, but really thefocus is on clinicians, so we'll
let Juan pick it up from there.
But really the focus is onclinicians, so we'll let Juan
pick it up from there.
The Diabetes Research Hub is acore technical platform where
guys like me, as softwareengineers, are participating
with real clinicians.
Like all of you on this call toreally focus our efforts on
(04:38):
technology designed specificallyfor researchers who are driving
towards cures and treatments.
A lot of other technology thatyou see out there like, for
example, when we create digitalhealth systems for, like
electronic health recordsolutions or patient portals
many of those are focused on thepatients themselves or the
doctors or the hospitals and thehealth systems.
But there's really not much outthere, especially in diabetes,
(05:01):
which says I'm buildingsomething for and by the
researchers themselves, whosejob it is to have real
evidence-driven research,evidence-driven experimentation,
evidence-driven data collectionand so that evidence-driven
part of it which just drives alot of what clinical trials need
to be done, whether they'rerandomized or not, or they're
(05:23):
dealing with real-world evidenceit's really hard for
researchers to find done.
Whether they're randomized ornot, or they're dealing with
real world evidence, it's reallyhard for researchers to find a
place where they can call theirown and do real work, and so
that's what interested me isthat most of my prior career has
been focused on healthcaredelivery professionals or
patients and their caregiversand families, as opposed to
researchers.
But when I ran into, you knowDr Klonhoff and Dr Espinoza and
(05:46):
these guys, they're like doingserious, serious data work
specifically on the clinicalside, and that's what excited me
.
So, juan, your view of this iseven more important than mine.
I think they complement eachother.
Juan Espinoza (05:59):
So you know, I'll answer that question, david, by
telling a little bit of a story, which is in 1999, the FDA
approved the first evercontinuous glucose monitor in
the United States no-transcript.
(06:38):
So it probably took until aboutthe mid-2010s to really achieve
both saturation, both from theperspective of the professional
societies, the way thatclinicians felt about these
technologies, and reallyincorporating CGMs even into our
clinical practice guidelines,which is normal for a new
technology.
(06:58):
Um and then, but thatpopularity, as as CGMs became
more and more used.
Not only were they being usedin research about CGMs for
clinical care and improving theclinical care of patients, but
it started being used for othertypes of research.
Uh is thinking of the CGM as notjust a tool in the clinical
(07:20):
management of persons withdiabetes, but CGM as a glucose
sensor, as a new type of datasource that is available to
inform any kind of scientificquery in diabetes and outside of
diabetes.
And so, as the devices becamemore available in clinical use,
(07:44):
they also started becoming usedmore in research, and not just
in research about validatingthem, analyze, store and share
this essentially new type ofdata.
(08:10):
Right, like we know how to dealwith survey data, we know how
to deal with data from othertypes of medical devices, we
know how to deal with EHRexports, but this is essentially
a new type of data that has newtypes of requirements.
And so we feel reallypassionately and over roughly a
(08:30):
decade or so of research in thecommunity, that there are gaps
in our knowledge right of howbest to manipulate this data,
and there have been, absolutely.
There have been publicationswhere people have proposed new
types of metrics, new types ofmethods for statistical analysis
, but that information isn'tnecessarily well disseminated or
(08:53):
understood across the entireresearch community, and I think
it's a real barrier, right, it'sa barrier for early stage
investigators, it's a barrierfor, maybe, clinical researchers
who are less technical, and soit keeps people away.
It keeps people away from usingCGMs, it keeps people away from
using this data, and we thinkthat this is really powerful,
(09:14):
that this has the potential tochange other diseases and other
research modalities, just likeit did in the care of patients
with diabetes, and so theproblem that we're most
interested in solving is how dowe demystify the technical piece
of this, how do we make iteasier for researchers to use
CGM data?
(09:34):
How do we aggregate thecollective knowledge of a
community of researchers overthe last 20 years into
evidence-based recommendationsaround how we analyze the data,
how we clean the data, how doyou deal with missingness?
What type of imputation shouldyou use?
Which metrics are the bestmetrics to use for different
(09:55):
kinds of applications?
And I think by building boththe tools the technology, which
Shahid was talking about, aswell as the community of
researchers who can come aroundthose tools and how to best use
them to support research isreally critical.
I think fundamentally is whatthe Diabetes Research Hub is all
about.
The technology is critical, butit doesn't do anything without
(10:19):
the community and the sharedknowledge that then makes it
move forward.
Shahid Shah (10:28):
Yeah, and one of the things we're doing right now
, in a very similar way as if wewould do if we're doing an
entrepreneurial startup, iswe're trying to build a very
basic amount of technology justto start, because we can, and
the technology is alreadyubiquitous and available today.
But the thing that Juan and DrKlonoff and others at DTS are
teaching us is how do weactually establish a set of
surveys where we go out and askresearchers what do they need,
(10:49):
rather than just creatingsomething and telling them what
they should want?
Right, and so you know, there isthis idea that, especially, you
know, arrogant entrepreneurslike myself we're like we're
going to build it and they willcome.
And while that might be useful,when you already know
everything in the market, in thecase of research, the whole
point is no one knows what theanswers are, and that's why
(11:11):
research is necessary, and sothat's a huge area and that's a
huge call to action foreverybody.
Listening to this podcast is ifyou are even tangentially
related to the research field indiabetes, please reach out to
us, because we actually havereal formal surveys, actual
interviews, or we're actuallysitting down with the
researchers asking them what areyou doing today with CGMs and
(11:33):
how are CGMs working well foryou or not working well for you?
And so, juan, talk about thatimportant really part, about you
know getting to the meat ofwhat researchers are working on
first, before building all thetechnology.
Juan Espinoza (11:46):
Yeah, no, that's absolutely right, Shahid.
I think, as you said, we don'thave the hubris yet to decide
that we know best, and so we'rereally starting from a ground up
approach where you know we'renot editorializing, you know
(12:07):
we're trying to find everypossible metric, every possible
analytic, every possibleimputation method, every
possible application, aggregateit, collect the information and
build tools that help addressthose use cases and so.
But to do that, you know we areactively trying to engage
members of the researchcommunity through surveys,
(12:28):
through interviews, throughfocus groups, and so there's
opportunities to.
So we do have a website alreadyset up for the Diabetes
Research Hub.
I'm sure we can include thelink in your show notes and on
the website and so individualscan sign up to participate, to
share their feedback and to tellus more.
(12:48):
And, honestly, if folks want toreach out to us in a more
unstructured way, just quiteliterally send an email like hey
, I'd love to talk to you aboutthis and tell you about how
we're doing things we want toknow, because there's a range of
researchers, there are peoplewho are incredibly sophisticated
and they're like oh yes, we'reusing these complex technical
(13:11):
tools to extract the data.
It all goes into thisvirtualized machine where we've
built a bunch of code thatstructures are normalized and
applies different metrics, andthat's fantastic.
That's really importantresearch.
Fantastic, that's reallyimportant research.
And there's also the folks whoare much closer to the patients,
much closer to the clinicalpart, who have really critical
clinical questions that theythink data from the CGM is going
to help them answer.
(13:31):
But they don't have thosetechnical resources.
They don't have a PhD datascientist on their research team
, they don't have an engineer tomanage all of this data for
them, and so you need to be ableto solve both of those problems
.
David Kerr (13:44):
Let's follow the dream here.
So if this is successful forpeople with diabetes, for health
, equity, for access.
Juan Espinoza (14:00):
Do you think it's going to be game changing?
Yeah, that's a really goodquestion.
I'll tell you, my aspirationalanswer to that is yes, the way
that it'll be game changing?
Right, because we're working atthe level of supporting
research.
So I think it'll be gamechanging in a couple of ways
(14:20):
more researchers of differentbackgrounds and different level
of maturity of, of, sorry, oftechnical maturity, meaning that
they do or do not have datascience expertise or data
handling expertise.
Um, this will be something thatwill be useful for folks who
are, whether they're from comingto diabetes research from a
physician background, from apsychologist background, from a
social work background, rightExp expanding the pool of people
(14:43):
who can do meaningful researchusing CGM data.
So that's one.
There's increasing access andreducing the barriers to entry
for the research community.
The second is that, and a lotof the focus on CGMs
historically and the researchhas been on, what are those key
clinical metrics, the componentsof the AGP, the things that the
(15:07):
manufacturers put in theirportals, the things that we
build clinical guidelines on.
All that is really reallyimportant and it moves slowly
for good reasons, right the needfor the robust level of data,
the need for appropriateregulatory approvals, for things
for consensus development.
That said, in the researchworld there's the opportunity to
(15:29):
move a lot faster to help eachother answer different kinds of
questions and new questions thatmaybe are more relevant to
specific subsets of patients andpopulations, or in specific
aspects of conditions that mayotherwise not rise to the same
prioritization structure as someof these.
Bigger like this is how wemanage all people with diabetes,
(15:52):
but we can think about morespecifically within a research
context, of how to generate theinformation that might help us
change the way that we makeclinical decisions about the
disease.
David Klonoff (16:05):
Juan and Shahid.
To what extent do you thinkthat the Diabetes Research Hub
is intended to help anindividual researcher understand
their own data better, and towhat extent do you think it's
important or desirable for themto upload their own data and
share data with otherresearchers?
Shahid Shah (16:26):
Yeah.
So the way to think about thatis that we have already built
out enough code so that youcould do both right, if you
don't know how you want thatdata to be used, but you have
some data to share like if Juanis better at it than you know
you are you can upload your dataand Juan can do the analysis.
But at the same time, as soon asyou upload the data, many of
(16:49):
the things that Juan has alreadytalked about we already do as
part of the metrics management.
So as soon as you upload datatoday, we'll do a whole bunch of
standard calculations, standardalgorithms and things like that
, but then open it and make itready for everyone else to use.
So the good news is, as oftoday, it's already in good
shape to do both of what you'resaying.
But the more we get like rightnow we're in a network problem,
(17:12):
which is, you know, we've gotabout 10 or 15 studies that
we've got the data in and we'retrying to load this in.
We'd like to be at hundreds ofstudies, so that those who are
good at collecting data can getdata, but those that are good at
researching can actuallyresearch, and so we get the best
of both worlds.
Juan Espinoza (17:27):
Yeah, and I think what I would add to that is you
know, from a philosophyperspective, our goal is to
advance the field, and I thinkwe advance the field first and
foremost by meeting researcherswhere they are and helping to
solve practical problems thatthey face today.
They are in helping to solvepractical problems that they
face today, and so a lot of ourfocus has been on creating the
software tools that researcherscan use locally on their own
(17:48):
machine, on their own data,without necessarily sharing it
back to us, because, you know,there might be different
institutional reasons why theycan or cannot, and that's okay,
we are here.
There are lots of good reasonswhy there are rules around that.
Some of them are federal, someof them are institutional, and
we're not asking we shouldcomply with those rules, just
like every other researchrepository complies with those
(18:09):
rules.
So what we're saying is let ushelp you solve your problems.
By the way, if you solve yourproblems using the tools that we
provided you, you can then justvery easily upload your data to
the repository that we'rebuilding.
You can then just very easilyupload your data to the
repository that we're buildingand that potentially solves two
different problems for theresearcher.
Right, it solves.
You needed better tools toanalyze your data.
(18:30):
Two, maybe this is anNIH-funded research study where
you're required to deposit yourdata into a public repository.
We are a public repositorywhere you can deposit your data,
so we're trying to solve twodifferent problems and now that
you've deposited your data bythe're trying to solve two
different problems and now thatyou've deposited your data, by
the way.
Now it's accessible to an entireresearch community.
Who can do this secondary useof data, real world approach to?
(18:51):
What new questions might I beable to ask if I had hundreds of
tracings from hundreds ofpatients about how CGMs can be
useful?
David Klonoff (19:00):
One.
Where can people find out moreinformation about the Diabetes
Research Hub?
Juan Espinoza (19:06):
Yeah, so our website is up and running.
It's with the DiabetesTechnology Web, so folks can go
to drh for Diabetes Research Hub, drhdiabetestechnologyorg, and
there they can learn about howto both view some of the data
that we're already hosting, aswell as how to submit their own
data and how to contact us toget a copy of the local software
(19:29):
that they can use on their owndata.
Thank, you.
David Klonoff (19:33):
Well, this is a really good project and I know
that there's more to it than yousaid in this time frame, and we
plan to interview you againlater to find out some of the
additional capabilities of theDiabetes Research Hub.
So for now, on behalf of Davidand myself, I would like to
(19:56):
thank both of you, shahid Shahand Juan Espinosa, for speaking
with us about the DiabetesResearch Hub.
So until our next podcast.
I'm going to say goodbye andthis podcast is available on
Spotify, the Apple Store and theDiabetes Technology Society
website.
So until our next podcast,thank you and goodbye.
(20:17):
Thank you very much.
Thank you for having us.
Shahid Shah (20:20):
Thanks.
Hello, this is Diabetes Technology Report.
I'm David Klonoff.
I'm an endocrinologist atSutter Health and UCSF.
I'm here today with my co-host,David Kerr, who has two very
special guests.
I'm going to introduce Davidand he will begin the interview.
David Kerr (00:33):
Thanks, david, and hello to everyone again.
David Kerr, speaking once morefrom Santa Barbara, california,
and we have two superstars ofdiabetes research and technology
on the podcast today.
We're very, very excited.
We're going to hear about a newinnovation that's planned
through the Diabetes TechnologySociety.
(00:53):
So welcome Shahid, welcome Juan.
It's lovely to see you todayand to hear from you and just to
really set the scene.
I'd like both of you just todescribe what's your day job,
really set the scene.
I'd like both of you just todescribe what's your day job.
But, more importantly, how didyou end up being interested in
diabetes in general and diabetestechnology specifically?
Shahid Shah (01:17):
Shahid, do you want to go first?
Sure, yeah, I'm a softwareengineer by training and I've
these days mostly doingentrepreneurship, in which I've
built and sold a few electronichealth record companies digital
technology but a lot of my workhas been in very specific types
of medical devices, you know,like insulin pumps or
respiration systems, and what wedeal with a lot is both in my
own family as well as a lot ofthe patients that we've helped
(01:40):
take care of with respect to ourmedical devices is always
related in some way to diabetesand other chronic conditions.
And so just a few years ago, drPlonoff and I met at an FDA
event, of all places, and hestarted talking a lot about what
the Diabetes Technology Societywas doing, and I was always
interested in diabetes just froma healthcare perspective, but
(02:02):
the fact that there was anactual society which just
focused on technology arounddiabetes was really what got me.
He had me at hello when he saidtechnology and diabetes in the
same sentence, and that's how wegot together.
David Kerr (02:17):
He's very persuasive indeed.
Juan, is your story similar orhow did you?
Is it different?
Juan Espinoza (02:23):
There are definitely some similarities.
So, uh, my day so I'm a generalpediatrician by training an
informaticist, my day job is I'mthe chief research informatics
officer.
Uh, and in robert h larrychildren's hospital, chicago, um
.
And I got interested indiabetes, uh, from the
perspective of it being acondition that was very much
(02:49):
probably at the forefront of theincorporation of technology and
data for disease management,especially if you think about 10
years ago.
Like no other disease useddevices and data to manage it.
Diabetes is this highlyquantified disease and has been
for a long time, and so for meit came along in this
(03:09):
professional side of like oh,this is an interesting problem,
I like data and technology.
Here's a disease with a bunchof data and technology.
Let me focus on it.
I was involved early on inefforts around CGME, hr
integration and sort of thinkingthrough innovative ways to
develop uh, uh, develop caremodels for diabetes, um, working
closely with the endocrinologyuh division at children's
(03:32):
hospital Los Angeles, where itwas at the time, and we
published a paper, uh about ourwork and building the first um
CGM EHR integration.
And one day I get an email froma guy named David Klonoff said
like oh, I saw your paper,that's really interesting.
We should talk and then youknow, four or five years later,
of fruitful collaboration.
(03:52):
We're here now working on thisproject.
David Kerr (03:54):
Excellent.
So this project, I mean, I takeit.
You mean the diabetestechnology meeting just the
other week in Burlingame.
There was a huge amount ofexcitement about something that
was new and being launched, andyou guys are starting this.
So, to avoid any delay, what isthis project all about?
What's this new project?
(04:15):
Shahid, do you want to startoff?
Shahid Shah (04:17):
Yeah, I'll just tell you from a quick tech
perspective, but really thefocus is on clinicians, so we'll
let Juan pick it up from there.
But really the focus is onclinicians, so we'll let Juan
pick it up from there.
The Diabetes Research Hub is acore technical platform where
guys like me, as softwareengineers, are participating
with real clinicians.
Like all of you on this call toreally focus our efforts on
(04:38):
technology designed specificallyfor researchers who are driving
towards cures and treatments.
A lot of other technology thatyou see out there like, for
example, when we create digitalhealth systems for, like
electronic health recordsolutions or patient portals
many of those are focused on thepatients themselves or the
doctors or the hospitals and thehealth systems.
But there's really not much outthere, especially in diabetes,
(05:01):
which says I'm buildingsomething for and by the
researchers themselves, whosejob it is to have real
evidence-driven research,evidence-driven experimentation,
evidence-driven data collectionand so that evidence-driven
part of it which just drives alot of what clinical trials need
to be done, whether they'rerandomized or not, or they're
(05:23):
dealing with real-world evidenceit's really hard for
researchers to find done.
Whether they're randomized ornot, or they're dealing with
real world evidence, it's reallyhard for researchers to find a
place where they can call theirown and do real work, and so
that's what interested me isthat most of my prior career has
been focused on healthcaredelivery professionals or
patients and their caregiversand families, as opposed to
researchers.
But when I ran into, you knowDr Klonhoff and Dr Espinoza and
(05:46):
these guys, they're like doingserious, serious data work
specifically on the clinicalside, and that's what excited me
.
So, juan, your view of this iseven more important than mine.
I think they complement eachother.
Juan Espinoza (05:59):
So you know, I'll answer that question, david, by
telling a little bit of a story, which is in 1999, the FDA
approved the first evercontinuous glucose monitor in
the United States no-transcript.
(06:38):
So it probably took until aboutthe mid-2010s to really achieve
both saturation, both from theperspective of the professional
societies, the way thatclinicians felt about these
technologies, and reallyincorporating CGMs even into our
clinical practice guidelines,which is normal for a new
technology.
(06:58):
Um and then, but thatpopularity, as as CGMs became
more and more used.
Not only were they being usedin research about CGMs for
clinical care and improving theclinical care of patients, but
it started being used for othertypes of research.
Uh is thinking of the CGM as notjust a tool in the clinical
(07:20):
management of persons withdiabetes, but CGM as a glucose
sensor, as a new type of datasource that is available to
inform any kind of scientificquery in diabetes and outside of
diabetes.
And so, as the devices becamemore available in clinical use,
(07:44):
they also started becoming usedmore in research, and not just
in research about validatingthem, analyze, store and share
this essentially new type ofdata.
(08:10):
Right, like we know how to dealwith survey data, we know how
to deal with data from othertypes of medical devices, we
know how to deal with EHRexports, but this is essentially
a new type of data that has newtypes of requirements.
And so we feel reallypassionately and over roughly a
(08:30):
decade or so of research in thecommunity, that there are gaps
in our knowledge right of howbest to manipulate this data,
and there have been, absolutely.
There have been publicationswhere people have proposed new
types of metrics, new types ofmethods for statistical analysis
, but that information isn'tnecessarily well disseminated or
(08:53):
understood across the entireresearch community, and I think
it's a real barrier, right, it'sa barrier for early stage
investigators, it's a barrierfor, maybe, clinical researchers
who are less technical, and soit keeps people away.
It keeps people away from usingCGMs, it keeps people away from
using this data, and we thinkthat this is really powerful,
(09:14):
that this has the potential tochange other diseases and other
research modalities, just likeit did in the care of patients
with diabetes, and so theproblem that we're most
interested in solving is how dowe demystify the technical piece
of this, how do we make iteasier for researchers to use
CGM data?
(09:34):
How do we aggregate thecollective knowledge of a
community of researchers overthe last 20 years into
evidence-based recommendationsaround how we analyze the data,
how we clean the data, how doyou deal with missingness?
What type of imputation shouldyou use?
Which metrics are the bestmetrics to use for different
(09:55):
kinds of applications?
And I think by building boththe tools the technology, which
Shahid was talking about, aswell as the community of
researchers who can come aroundthose tools and how to best use
them to support research isreally critical.
I think fundamentally is whatthe Diabetes Research Hub is all
about.
The technology is critical, butit doesn't do anything without
(10:19):
the community and the sharedknowledge that then makes it
move forward.
Shahid Shah (10:28):
Yeah, and one of the things we're doing right now
, in a very similar way as if wewould do if we're doing an
entrepreneurial startup, iswe're trying to build a very
basic amount of technology justto start, because we can, and
the technology is alreadyubiquitous and available today.
But the thing that Juan and DrKlonoff and others at DTS are
teaching us is how do weactually establish a set of
surveys where we go out and askresearchers what do they need,
(10:49):
rather than just creatingsomething and telling them what
they should want?
Right, and so you know, there isthis idea that, especially, you
know, arrogant entrepreneurslike myself we're like we're
going to build it and they willcome.
And while that might be useful,when you already know
everything in the market, in thecase of research, the whole
point is no one knows what theanswers are, and that's why
(11:11):
research is necessary, and sothat's a huge area and that's a
huge call to action foreverybody.
Listening to this podcast is ifyou are even tangentially
related to the research field indiabetes, please reach out to
us, because we actually havereal formal surveys, actual
interviews, or we're actuallysitting down with the
researchers asking them what areyou doing today with CGMs and
(11:33):
how are CGMs working well foryou or not working well for you?
And so, juan, talk about thatimportant really part, about you
know getting to the meat ofwhat researchers are working on
first, before building all thetechnology.
Juan Espinoza (11:46):
Yeah, no, that's absolutely right, Shahid.
I think, as you said, we don'thave the hubris yet to decide
that we know best, and so we'rereally starting from a ground up
approach where you know we'renot editorializing, you know
(12:07):
we're trying to find everypossible metric, every possible
analytic, every possibleimputation method, every
possible application, aggregateit, collect the information and
build tools that help addressthose use cases and so.
But to do that, you know we areactively trying to engage
members of the researchcommunity through surveys,
(12:28):
through interviews, throughfocus groups, and so there's
opportunities to.
So we do have a website alreadyset up for the Diabetes
Research Hub.
I'm sure we can include thelink in your show notes and on
the website and so individualscan sign up to participate, to
share their feedback and to tellus more.
(12:48):
And, honestly, if folks want toreach out to us in a more
unstructured way, just quiteliterally send an email like hey
, I'd love to talk to you aboutthis and tell you about how
we're doing things we want toknow, because there's a range of
researchers, there are peoplewho are incredibly sophisticated
and they're like oh yes, we'reusing these complex technical
(13:11):
tools to extract the data.
It all goes into thisvirtualized machine where we've
built a bunch of code thatstructures are normalized and
applies different metrics, andthat's fantastic.
That's really importantresearch.
Fantastic, that's reallyimportant research.
And there's also the folks whoare much closer to the patients,
much closer to the clinicalpart, who have really critical
clinical questions that theythink data from the CGM is going
to help them answer.
(13:31):
But they don't have thosetechnical resources.
They don't have a PhD datascientist on their research team
, they don't have an engineer tomanage all of this data for
them, and so you need to be ableto solve both of those problems
.
David Kerr (13:44):
Let's follow the dream here.
So if this is successful forpeople with diabetes, for health
, equity, for access.
Juan Espinoza (14:00):
Do you think it's going to be game changing?
Yeah, that's a really goodquestion.
I'll tell you, my aspirationalanswer to that is yes, the way
that it'll be game changing?
Right, because we're working atthe level of supporting
research.
So I think it'll be gamechanging in a couple of ways
(14:20):
more researchers of differentbackgrounds and different level
of maturity of, of, sorry, oftechnical maturity, meaning that
they do or do not have datascience expertise or data
handling expertise.
Um, this will be something thatwill be useful for folks who
are, whether they're from comingto diabetes research from a
physician background, from apsychologist background, from a
social work background, rightExp expanding the pool of people
(14:43):
who can do meaningful researchusing CGM data.
So that's one.
There's increasing access andreducing the barriers to entry
for the research community.
The second is that, and a lotof the focus on CGMs
historically and the researchhas been on, what are those key
clinical metrics, the componentsof the AGP, the things that the
(15:07):
manufacturers put in theirportals, the things that we
build clinical guidelines on.
All that is really reallyimportant and it moves slowly
for good reasons, right the needfor the robust level of data,
the need for appropriateregulatory approvals, for things
for consensus development.
That said, in the researchworld there's the opportunity to
(15:29):
move a lot faster to help eachother answer different kinds of
questions and new questions thatmaybe are more relevant to
specific subsets of patients andpopulations, or in specific
aspects of conditions that mayotherwise not rise to the same
prioritization structure as someof these.
Bigger like this is how wemanage all people with diabetes,
(15:52):
but we can think about morespecifically within a research
context, of how to generate theinformation that might help us
change the way that we makeclinical decisions about the
disease.
David Klonoff (16:05):
Juan and Shahid.
To what extent do you thinkthat the Diabetes Research Hub
is intended to help anindividual researcher understand
their own data better, and towhat extent do you think it's
important or desirable for themto upload their own data and
share data with otherresearchers?
Shahid Shah (16:26):
Yeah.
So the way to think about thatis that we have already built
out enough code so that youcould do both right, if you
don't know how you want thatdata to be used, but you have
some data to share like if Juanis better at it than you know
you are you can upload your dataand Juan can do the analysis.
But at the same time, as soon asyou upload the data, many of
(16:49):
the things that Juan has alreadytalked about we already do as
part of the metrics management.
So as soon as you upload datatoday, we'll do a whole bunch of
standard calculations, standardalgorithms and things like that
, but then open it and make itready for everyone else to use.
So the good news is, as oftoday, it's already in good
shape to do both of what you'resaying.
But the more we get like rightnow we're in a network problem,
(17:12):
which is, you know, we've gotabout 10 or 15 studies that
we've got the data in and we'retrying to load this in.
We'd like to be at hundreds ofstudies, so that those who are
good at collecting data can getdata, but those that are good at
researching can actuallyresearch, and so we get the best
of both worlds.
Juan Espinoza (17:27):
Yeah, and I think what I would add to that is you
know, from a philosophyperspective, our goal is to
advance the field, and I thinkwe advance the field first and
foremost by meeting researcherswhere they are and helping to
solve practical problems thatthey face today.
They are in helping to solvepractical problems that they
face today, and so a lot of ourfocus has been on creating the
software tools that researcherscan use locally on their own
(17:48):
machine, on their own data,without necessarily sharing it
back to us, because, you know,there might be different
institutional reasons why theycan or cannot, and that's okay,
we are here.
There are lots of good reasonswhy there are rules around that.
Some of them are federal, someof them are institutional, and
we're not asking we shouldcomply with those rules, just
like every other researchrepository complies with those
(18:09):
rules.
So what we're saying is let ushelp you solve your problems.
By the way, if you solve yourproblems using the tools that we
provided you, you can then justvery easily upload your data to
the repository that we'rebuilding.
You can then just very easilyupload your data to the
repository that we're buildingand that potentially solves two
different problems for theresearcher.
Right, it solves.
You needed better tools toanalyze your data.
(18:30):
Two, maybe this is anNIH-funded research study where
you're required to deposit yourdata into a public repository.
We are a public repositorywhere you can deposit your data,
so we're trying to solve twodifferent problems and now that
you've deposited your data bythe're trying to solve two
different problems and now thatyou've deposited your data, by
the way.
Now it's accessible to an entireresearch community.
Who can do this secondary useof data, real world approach to?
(18:51):
What new questions might I beable to ask if I had hundreds of
tracings from hundreds ofpatients about how CGMs can be
useful?
David Klonoff (19:00):
One.
Where can people find out moreinformation about the Diabetes
Research Hub?
Juan Espinoza (19:06):
Yeah, so our website is up and running.
It's with the DiabetesTechnology Web, so folks can go
to drh for Diabetes Research Hub, drhdiabetestechnologyorg, and
there they can learn about howto both view some of the data
that we're already hosting, aswell as how to submit their own
data and how to contact us toget a copy of the local software
(19:29):
that they can use on their owndata.
Thank, you.
David Klonoff (19:33):
Well, this is a really good project and I know
that there's more to it than yousaid in this time frame, and we
plan to interview you againlater to find out some of the
additional capabilities of theDiabetes Research Hub.
So for now, on behalf of Davidand myself, I would like to
(19:56):
thank both of you, shahid Shahand Juan Espinosa, for speaking
with us about the DiabetesResearch Hub.
So until our next podcast.
I'm going to say goodbye andthis podcast is available on
Spotify, the Apple Store and theDiabetes Technology Society
website.
So until our next podcast,thank you and goodbye.
(20:17):
Thank you very much.
Thank you for having us.
Shahid Shah (20:20):
Thanks.
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