00:00hi and welcome to the a 16z podcast I'm
00:02Hannah and today's episode is about a
00:04pretty universal topic which is the idea
00:06of lunge evety and by that we mean
00:08everything from increasing the amount of
00:10time that we're healthy to increasing
00:12our lifespan and even combating aging we
00:15cover everything from the latest
00:16research to tools for what we can do in
00:18our own personal lives this episode is
00:21based on a conversation at our summit
00:22event in November 2017 and includes Jeff
00:25kata its CEO and co-founder of QBO who's
00:28the first voice you'll hear after mine
00:29Mike Schneider professor and chair of
00:32the department of genetics at Stanford
00:33the second voice David Sinclair
00:35co-director of the glens Center for
00:38biology of Aging at Harvard Medical
00:39School and Kristin Fortney CEO and
00:42co-founder of bio age this is a question
00:45I'd actually like to ask all of you
00:47which is why now why is this the moment
00:49in which we can either find disease
00:51before it occurs or actually extend our
00:53lives what is it that's setting the
00:55stage for this I think it has to do with
00:56the explosion and technology we have to
00:58measure biology because in almost any
01:00area of scientific discipline the first
01:02step is kind of turning it into more or
01:05less an information science and once we
01:07have enough information and we can start
01:09to model these complex processes which
01:11are traditionally you know thought of as
01:13being too complex for us to understand
01:14but with the tremendous gains in
01:16computing power we have any amount
01:18information we can now measure about
01:19biology it's starting become tractable
01:22there's kind of two aspects going on one
01:24it's extending healthspan and the thing
01:27that David works on is actually trying
01:28to actually reverse aging there are
01:31somewhat different they both have the
01:32same goal of extending people's lives
01:34you know 40% of Americans will get
01:37cancer and that number is only going to
01:38go up so what you want to do is prevent
01:41that from happening and we can now catch
01:43this much earlier with these new
01:45technologies the biomarkers hopefully
01:47that will come out of some of these new
01:48ventures and so if you can catch it
01:51early you can actually you know then
01:52treat this before it happens an ideally
01:55treated in a personal fashion and that
01:57will extend people's health span they
01:59will live longer lives healthier lives
02:00we hope and there are analogies for that
02:03with heart issues as well another
02:04leading killing those are the two major
02:06killers people in the country so I think
02:09if we can catch these things early which
02:11I think we're capable of doing Alan
02:13measurements we can extend people's
02:14health span pretty easily and it's
02:16already a reason why people are living
02:17much much longer than they used to
02:19because what is the simple biomarker
02:21have to do with the aging process and
02:23how did you start down that path yeah a
02:25real biomarker has to predict the future
02:27that's how I think of a biomarker so we
02:29focus on bio age at finding molecular
02:31signatures of aging and what I mean by
02:34that is that something we can measure in
02:35your blood that predicts basically your
02:37future then we can measure about your
02:39body that says what's your life
02:41expectancy you know are you at higher
02:43risk of getting heart disease in ten
02:44years or Alzheimer's disease we focus on
02:47mapping out these signatures using
02:49modern genomic technologies like the
02:50proteome the metabolome so then we look
02:53for modifiable risk factors so they're
02:55useful not just as biomarkers but
02:56potentially is novel targets themselves
02:58to interfere in the aging process and
02:59where did those biomarkers come from we
03:02want biomarkers of all cause mortality
03:03we want something that predicts future
03:04mortality and I could go out and measure
03:06all your blood samples right now and
03:08then wait 30 years and then I'd be able
03:09to predict mortality and that's not
03:11going to work right first start up so
03:12what's really key for us is to partner
03:14with bio banks and there's a lot of
03:15these especially in European countries
03:17with socialized medicine systems where
03:19they have like tens of thousands of
03:21samples in the freezer that are 10 or 20
03:23years old and full electronic health
03:25records for those people going forward
03:26into the future so we can take these
03:28samples that are 20 years old and we can
03:30query them with all the modern
03:31technologies and measure hundreds of
03:33thousands of variables and then
03:34integrate that with our electronic
03:35health records to try to predict their
03:36future health course and that's where
03:38all our discoveries have come home so
03:39far so David you've worked across a
03:41large number of startups in the area
03:43what is the kind of breakdown of the
03:46tools that we're starting to see
03:47actually help us with aging well there
03:49are three main areas that I'm seeing
03:51really explode in the field first of all
03:53there's addressing actual causes of
03:55Aging and there are many of those then
03:57the second area is harnessing the body's
03:59natural defenses against aging which
04:02we've now known for about 20 years
04:03initially from little model organisms in
04:05yeast Mike and I used to work on that
04:07stuff and now we're seeing the
04:09improvement of healthcare this is you
04:11know it's a theme in this conference but
04:12the ability to predict diseases before
04:15they actually take hold and those three
04:17combined I think are going to
04:18dramatically increase human health span
04:20and lifespan by somewhere between five
04:23and 15 years in our lifetimes we're
04:27started with genomics of we refer to as
04:29multi scale biological digitization and
04:32multiple skills both in length and in
04:34time of processes right so molecular
04:36processes happen on a links cover a
04:39billionth of a meter and very short
04:40timescales and then we can measure
04:42things like Satou mix on the scale of a
04:44millionth of a meter and then we have
04:46technology biomedical imaging that's
04:47more of a thousandth of a meter and as
04:50we're able to capture more and more of a
04:52snapshot at multiple scales both in time
04:54and length scales that's ultimately
04:56gonna lead to multi scale models of
04:58biology that can be used for prevention
05:00not just measuring but modeling in a
05:03personalized way the trajectory of
05:05somebody and personalized treatment
05:06we've all heard a lot by now about this
05:08idea of precision medicine with these
05:10new sources of data what does that
05:12actually mean for increasing our healthy
05:15time in the immediate future
05:17well precision medicine is based on the
05:19premise that we're all different we all
05:21have individual baselines and such and I
05:24would argue the related field by the way
05:25is precision health so trying to keep
05:27people healthy based on their individual
05:29characterizations so you know precision
05:32medicine at some levels been around for
05:34a long time at least personalized
05:35medicine but it's different now
05:36is the fact that we can collect data at
05:39a level that's never been possible
05:40before so you can try and understand at
05:43an individual level what it means to be
05:45healthy and how people will respond to
05:46treatments for disease and such and so I
05:49think coming back to the longitudinal
05:50aspect by following people over time at
05:53an individual level you can see
05:55differences in people and catch disease
05:57early when it happens try and keep the
05:59boil healthy based on the personal
06:00signatures and it catches these early
06:02and treat them based on their personal
06:04and precision characterization so do
06:07very precise treatment Kristin doesn't
06:09know this but I actually have a personal
06:10aging marker because I've been following
06:12me for eight years and it may be
06:14actionable I don't know how does
06:18precision medicine precision health how
06:20is that going to change in our actual
06:21experience of the way we get treated or
06:23be healthy or preventive medicine I mean
06:25is a physical gonna be the same as it is
06:27now is that gonna change I think the way
06:29we do medicine now is totally Byzantine
06:31it's just really ridiculous how crude we
06:34are at what we do and
06:35how many of you have had your genome
06:36sequence or exomes out there a few you
06:40know I think 10 years from now everybody
06:41is gonna raise their hands right that's
06:43gonna just part of health care and then
06:45on but to me that's only just the start
06:47of things I think we're gonna collect
06:48lots of other measurements and there are
06:50just some amazing technologies out there
06:52that should lead us to be able to do
06:54this and as a study we've been running
06:55on a hundred people we've actually
06:57caught at least two cases of hard issues
07:00early because we were following them
07:02closely in one case right from simple
07:04wearable device we also caught a
07:06pre-cancer and a case of early lymphoma
07:08by again just careful monitoring those
07:10are a few of many examples just by
07:12following people with these kinds of new
07:14measurements so I think that will become
07:16the norm in the future at least we would
07:17like to make it tall and just starting
07:19to commercialize now I would say but it
07:22will be you know an integral part of
07:23healthcare how about your aging what are
07:25the kinds of tools we'll start to see
07:27that we might see in our lifetime that
07:28actually prevent aging well often people
07:31are surprised that there are already
07:33molecules in human trials already a
07:36couple of companies that I work with
07:37have been doing trials for a number of
07:39years now and they seem to be working as
07:41advertised but it's pretty hard to
07:43actually show that they're reversing
07:44aging so we're going off two particular
07:46diseases but some of the approaches that
07:48are really new they're really exciting
07:50is addressing causes of aging one of the
07:53main causes that's emerged recently are
07:55senescence cells that build up in the
07:56body these are zombie-like cells that
07:59take themselves out of the cell cycle
08:01they're not dividing but they cause
08:02havoc and there's new technologies
08:04emerging able to delete these cells with
08:06either small molecules or other
08:08approaches and if you do that to a mouse
08:10they seem to be rejuvenated and the hope
08:12is of course that'll happen with us as
08:13well more on the cutting edge we're
08:16talking about information in the body my
08:18personal view is that we have two types
08:20of information our body we have the
08:21digital which is the DNA and the analog
08:23system which is the epigenome how those
08:25genes are read out and that's becoming
08:27more and more popular as an idea the
08:29challenge though if it truly is
08:31epigenetic and analog that's really hard
08:33to correct and not cause havoc not cause
08:36cancer but there are new tools there is
08:37actually evidence in a mouse that you
08:39can reverse some of those so-called
08:41epigenetic analog changes with aging and
08:44that's truly the next frontier in my
08:46view because that really could lead to
08:49and you just go to the doctor every five
08:51years and get a complete reset or you
08:53know almost complete reset I think
08:54there's also a little bit of dogma in
08:56medicine that you shouldn't run tests or
08:59take measurements on people that are
09:00asymptomatic by the time you're
09:02symptomatic a lot of times it's too late
09:03yeah right and so we need to get to a
09:05place where we know well before you're
09:08symptomatic that there's a problem right
09:09and then you know there's a lot more
09:11options as far as intervention and
09:13treatment in terms of the system though
09:15are we set up so who pays to keep us
09:17healthy how do we incentivize the system
09:19as the cost of these measurements go
09:21down at some point I think it will
09:23actually be more economical to prevent
09:25these things than to sit back and wait
09:27mm-hm I mean we have proof of principle
09:29already for like cholesterol right
09:31that's us used as a surrogate marker of
09:33a pre disease state and it can be used
09:35as an endpoint in a clinical trial as
09:36well so I think the sort of thing can
09:38certainly work with the current
09:40healthcare system it's just a matter of
09:41finding newer and better markers and
09:43that's what these sort of technologies
09:44are enabling the key is a show proof you
09:49know the clinical trial or clinical sis
09:52are designed to isolate the information
09:54value of a single variable for
09:56predicting a specific pathology but
09:59imagine if Google tried to give you
10:01search results based on a single
10:03parameter they use millions we should be
10:05using millions of inputs to determine
10:07what is wrong with you and what is the
10:10prognosis and diagnosis and as we had
10:12these longitudinal you know models that
10:15is complex sets of variables over
10:18individual time series and deltas and
10:21the precision is gonna go way up I'll
10:23tell you a personal example which is
10:25that I actually caught my Lyme disease
10:27early and one reason I could do that is
10:28because I knew what my baseline
10:30measurements were I had all the data I
10:32knew from my SmartWatch from the simple
10:34pulse ox because my blood oxygen was
10:36running low and my heart rate was
10:38elevated on these simple devices that's
10:40one example that told me something
10:42wasn't right which I then got treated
10:43and cleared it all up but that's one
10:45simple example and I think we just need
10:47to do that at scale with other kinds of
10:50measurements and other sorts of things
10:52I knew the deviations from the data and
10:54so I could catch it because I knew what
10:56was going on and we need that for
10:57everybody basically how do you think
10:59about who owns these big pools of data
11:02do we think about privacy and who has
11:04ownership over these streamlets I mean I
11:06think we all should owner now it's easy
11:08to say it's not always easy to execute
11:10because a lot of providers think they
11:12own the data and such and that's where a
11:14little bit of a tug of war comes in
11:16we'll see how this all plays out but I
11:18think in the end you should own your own
11:19data and should be able to share it with
11:22now how to interpret the data is still
11:24tricky and that's why there's a lot of
11:25opportunity out here and how to capture
11:28the day to get meaning from it and such
11:29how about the societal considerations
11:32what will change if we end up spending
11:35lots more decades healthy or adding more
11:38decades to our lives well frankly and
11:40right now three quarters of annual
11:42healthcare costs go towards chronic
11:44diseases in the elderly and that's
11:45adding those are years of sick life so
11:48if we could really compress morbidity to
11:49the extent that we already can in mice I
11:51mean we have a lot of different
11:52treatments senescent cells removal which
11:54David mentioned mapa myosin metformin
11:57probably - that already work in mammals
11:59and if we can bring these to humans and
12:01I think that's gonna be really wonderful
12:02for a mesocycle perspective yes probably
12:05the age of retirement will shift etc but
12:07I mean who doesn't want a decade of
12:09extra healthy life as opposed to a few
12:10more months of a second is it should if
12:13you think that should make the economy
12:14more efficient it's really really
12:16expensive to educate a human and make
12:18them a productive member of society if
12:20you get more years of productivity you
12:22know it's actually a better ROI right
12:23first society as a whole yeah well there
12:25are a whole academic theses on this and
12:27so the economists have calculated that
12:30just reducing one major disease let's
12:32say cancer by just 10% the US would save
12:35about 3 4 trillion dollars in the long
12:37run Wow and what we're talking about
12:39here is much bigger than that Italian
12:41and that's money that can be put back
12:42into education the environment and so we
12:46see a very bright future not a land of
12:49old people in nursing homes but vibrant
12:5180 90 year olds that aren't taxing
12:53health care system the name of the games
12:55keep people healthy ldlt event pump
12:58that's really and actually if you look
13:03at these super centenarians that's
13:04basically what happens and then they
13:05live incredibly healthy lives they don't
13:07have many chronic diseases and then
13:09suddenly they just pass away and
13:11everybody so that's great look they were
13:13a healthy all the way to the end and
13:14that's kind of what we're trying to
13:15everybody any mice it's not that hard
13:17these days if you extend the lifespan of
13:19a mouse 1020 percent people say yeah
13:21what's new and these mice you look at
13:23them in the cage and you can tell the
13:25difference between the controls and
13:26these other mice they're running around
13:27the other mice sir shivering in the
13:29corner and all gray and ragged but then
13:32they die quickly these long live mice
13:33it's a relatively quick death I think we
13:35can achieve that in humans there's no
13:36reason why we can't since I'm not a
13:38mouse what can I do to actually increase
13:41my age my lifespan or my health span so
13:45that my picture looks like that so I
13:46just keep going and then stop exercising
13:49eat your vegetables drink lots of
13:52caffeine very robust results with all
13:54cause mortality there and baby aspirin
13:55and probably metformin you know in a few
13:57years I was gonna say exercise and eat
14:00your vegetables too but we hope to
14:01change it and if you have 400 sensors on
14:04your car and it's measuring you all the
14:06time and the average number of sensors
14:08on a person is zero and you think about
14:11that's crazy right we should be
14:13following ourselves much more carefully
14:14and we can do this with these new kinds
14:16of measurements we've talked about and
14:18follow ourselves the way we keep our car
14:20run and keep our bodies running the same
14:21way and so in the future I hope that's
14:24what will have the area that I get asked
14:26a lot about is harnessing the body's
14:28natural defenses against aging we all
14:29know that if we exercise and we diet the
14:32state lean calorie restrict even if
14:33you're strong enough to do that the body
14:35has these inbuilt pathways that turn on
14:37the defenses that take care of seemingly
14:39all the major causes of Aging how do you
14:42mimic that in a pill that's the
14:43challenge and some of the pathways that
14:45we work on there are these genetic
14:46pathways like soar to ins there are
14:48others called mTOR NP kinase but there's
14:52a network that controls our body and
14:54some of the molecules that I work on
14:56kick the body into that defensive mode
14:58and get the body back to a youthful
15:01state and you know into that defensive
15:03mode without necessarily having to run a
15:06marathon every few weeks or stay super
15:08skinny and hungry I would say that the
15:10best kind of insurance policy you can
15:12have in the future is to start
15:14aggregating and tracking data by
15:16yourself because you know something is
15:17gonna go wrong like death and taxes they
15:18say you know those are two things that
15:20are guaranteed so you're gonna have in
15:22health incident the question is is what
15:24information are your doctors gonna have
15:26at their disposal to determine what's
15:27wrong with you and even if we don't know
15:29right now technology is changing and our
15:31understanding of human biology is
15:33changing is advancing so fast that we
15:35will likely by the time something is
15:37wrong with you so build a time capsule
15:39of information and continually deposit
15:42to it and you don't even have to look at
15:43it right now save it for a rainy day and
15:45you do that with devices with monitoring
15:47with what kinds of ways do you click
15:49yeah I mean there's just simple even
15:51just starting with tracking your pulse
15:53and your activity like that's a huge
15:56increase from zero to one you didn't
15:58yeah but you know I regularly get a
16:01number of clinical assays done to track
16:04changes in my biochemistry and I think
16:07there's more and more services they're
16:08making that cheaper and cheaper and it's
16:10not necessarily for everyone yet but I
16:11think it will be so this is gonna sound
16:13strange but I've been experimenting on
16:14myself and by demand on my family for
16:17the last decade Wow so I have a fair
16:19amount of data on one side we do a bio
16:21tracking and so I've seen my calculated
16:24by Oh H go up dramatically
16:26scarily so about three years ago it went
16:29up to over a decade older than my actual
16:33I was sitting around and not watching
16:35what I was eating and so then I took
16:38I took metformin Kristin mentioned which
16:40is a diabetes drug I took another
16:41molecule that we've worked on called it
16:43raises nad we call them nad boosters and
16:46I saw that my bio aged according to this
16:48algorithm went down to thirty one point
16:50four from fifty seven point something
16:52and I've stayed down there so that's
16:55been a dramatic improvement in
16:56biomarkers and if I hadn't been
16:58monitoring myself I would have had no
17:00idea of my physician wouldn't have said
17:02anything I was still within the normal
17:04range but it's crazy to let us become
17:06diseased before we take actions often
17:08it's too late I mean my father 78 he's
17:11running around like he's 25 again he
17:13says he feels great he feels better than
17:15he ever did he's dating my ex-girlfriend
17:16a great time I'm okay with it my wife
17:22feels a bit strange right okay thank you
17:26so much hopefully we're here in 60 years
17:27still talking about do all the work
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