0:00:01.121,0:00:04.110
So, embryonic stem cells

0:00:04.110,0:00:07.410
are really incredible cells.

0:00:07.410,0:00:10.198
They are our body's own repair kits,

0:00:10.198,0:00:13.162
and they're pluripotent, which means they can morph into

0:00:13.162,0:00:15.594
all of the cells in our bodies.

0:00:15.594,0:00:18.282
Soon, we actually will be able to use stem cells

0:00:18.282,0:00:21.267
to replace cells that are damaged or diseased.

0:00:21.267,0:00:23.698
But that's not what I want to talk to you about,

0:00:23.698,0:00:26.376
because right now there are some really

0:00:26.376,0:00:30.322
extraordinary things that we are doing with stem cells

0:00:30.322,0:00:31.929
that are completely changing

0:00:31.929,0:00:34.828
the way we look and model disease,

0:00:34.828,0:00:37.347
our ability to understand why we get sick,

0:00:37.347,0:00:39.778
and even develop drugs.

0:00:39.778,0:00:44.091
I truly believe that stem cell research is going to allow

0:00:44.091,0:00:48.596
our children to look at Alzheimer's and diabetes

0:00:48.596,0:00:52.987
and other major diseases the way we view polio today,

0:00:52.987,0:00:56.188
which is as a preventable disease.

0:00:56.188,0:00:59.411
So here we have this incredible field, which has

0:00:59.411,0:01:03.798
enormous hope for humanity,

0:01:03.798,0:01:07.318
but much like IVF over 35 years ago,

0:01:07.318,0:01:09.652
until the birth of a healthy baby, Louise,

0:01:09.652,0:01:14.721
this field has been under siege politically and financially.

0:01:14.721,0:01:18.993
Critical research is being challenged instead of supported,

0:01:18.993,0:01:23.353
and we saw that it was really essential to have

0:01:23.353,0:01:26.884
private safe haven laboratories where this work

0:01:26.884,0:01:29.714
could be advanced without interference.

0:01:29.714,0:01:32.245
And so, in 2005,

0:01:32.245,0:01:34.857
we started the New York Stem Cell Foundation Laboratory

0:01:34.857,0:01:38.446
so that we would have a small organization that could

0:01:38.446,0:01:41.758
do this work and support it.

0:01:41.758,0:01:45.143
What we saw very quickly is the world of both medical

0:01:45.143,0:01:48.519
research, but also developing drugs and treatments,

0:01:48.519,0:01:52.232
is dominated by, as you would expect, large organizations,

0:01:52.232,0:01:55.351
but in a new field, sometimes large organizations

0:01:55.351,0:01:57.519
really have trouble getting out of their own way,

0:01:57.519,0:01:59.955
and sometimes they can't ask the right questions,

0:01:59.955,0:02:03.311
and there is an enormous gap that's just gotten larger

0:02:03.311,0:02:06.522
between academic research on the one hand

0:02:06.522,0:02:09.223
and pharmaceutical companies and biotechs

0:02:09.223,0:02:12.489
that are responsible for delivering all of our drugs

0:02:12.489,0:02:14.879
and many of our treatments, and so we knew that

0:02:14.879,0:02:18.825
to really accelerate cures and therapies, we were going

0:02:18.825,0:02:21.632
to have to address this with two things:

0:02:21.632,0:02:24.854
new technologies and also a new research model.

0:02:24.854,0:02:28.613
Because if you don't close that gap, you really are

0:02:28.613,0:02:30.220
exactly where we are today.

0:02:30.220,0:02:31.887
And that's what I want to focus on.

0:02:31.887,0:02:35.437
We've spent the last couple of years pondering this,

0:02:35.437,0:02:37.828
making a list of the different things that we had to do,

0:02:37.828,0:02:40.459
and so we developed a new technology,

0:02:40.459,0:02:41.710
It's software and hardware,

0:02:41.710,0:02:45.213
that actually can generate thousands and thousands of

0:02:45.213,0:02:48.383
genetically diverse stem cell lines to create

0:02:48.383,0:02:52.170
a global array, essentially avatars of ourselves.

0:02:52.170,0:02:55.604
And we did this because we think that it's actually going

0:02:55.604,0:02:59.019
to allow us to realize the potential, the promise,

0:02:59.019,0:03:02.099
of all of the sequencing of the human genome,

0:03:02.099,0:03:04.603
but it's going to allow us, in doing that,

0:03:04.603,0:03:09.611
to actually do clinical trials in a dish with human cells,

0:03:09.611,0:03:13.770
not animal cells, to generate drugs and treatments

0:03:13.770,0:03:17.019
that are much more effective, much safer,

0:03:17.019,0:03:20.275
much faster, and at a much lower cost.

0:03:20.275,0:03:22.659
So let me put that in perspective for you

0:03:22.659,0:03:24.075
and give you some context.

0:03:24.075,0:03:28.907
This is an extremely new field.

0:03:28.907,0:03:31.739
In 1998, human embryonic stem cells

0:03:31.739,0:03:35.251
were first identified, and just nine years later,

0:03:35.251,0:03:39.556
a group of scientists in Japan were able to take skin cells

0:03:39.556,0:03:42.751
and reprogram them with very powerful viruses

0:03:42.751,0:03:46.993
to create a kind of pluripotent stem cell

0:03:46.993,0:03:49.083
called an induced pluripotent stem cell,

0:03:49.083,0:03:52.091
or what we refer to as an IPS cell.

0:03:52.091,0:03:55.289
This was really an extraordinary advance, because

0:03:55.289,0:03:57.833
although these cells are not human embryonic stem cells,

0:03:57.833,0:03:59.627
which still remain the gold standard,

0:03:59.627,0:04:03.097
they are terrific to use for modeling disease

0:04:03.097,0:04:05.827
and potentially for drug discovery.

0:04:05.827,0:04:08.867
So a few months later, in 2008, one of our scientists

0:04:08.867,0:04:12.067
built on that research. He took skin biopsies,

0:04:12.067,0:04:14.095
this time from people who had a disease,

0:04:14.095,0:04:17.009
ALS, or as you call it in the U.K., motor neuron disease.

0:04:17.009,0:04:18.707
He turned them into the IPS cells

0:04:18.707,0:04:21.393
that I've just told you about, and then he turned those

0:04:21.393,0:04:24.097
IPS cells into the motor neurons that actually

0:04:24.097,0:04:25.558
were dying in the disease.

0:04:25.558,0:04:28.577
So basically what he did was to take a healthy cell

0:04:28.577,0:04:30.291
and turn it into a sick cell,

0:04:30.291,0:04:33.849
and he recapitulated the disease over and over again

0:04:33.849,0:04:37.209
in the dish, and this was extraordinary,

0:04:37.209,0:04:39.457
because it was the first time that we had a model

0:04:39.457,0:04:43.645
of a disease from a living patient in living human cells.

0:04:43.645,0:04:46.765
And as he watched the disease unfold, he was able

0:04:46.765,0:04:49.776
to discover that actually the motor neurons were dying

0:04:49.776,0:04:51.903
in the disease in a different way than the field

0:04:51.903,0:04:54.397
had previously thought. There was another kind of cell

0:04:54.397,0:04:56.598
that actually was sending out a toxin

0:04:56.598,0:04:59.109
and contributing to the death of these motor neurons,

0:04:59.109,0:05:00.467
and you simply couldn't see it

0:05:00.467,0:05:02.257
until you had the human model.

0:05:02.257,0:05:04.924
So you could really say that

0:05:04.924,0:05:08.830
researchers trying to understand the cause of disease

0:05:08.830,0:05:12.982
without being able to have human stem cell models

0:05:12.982,0:05:15.742
were much like investigators trying to figure out

0:05:15.742,0:05:18.983
what had gone terribly wrong in a plane crash

0:05:18.983,0:05:22.980
without having a black box, or a flight recorder.

0:05:22.980,0:05:25.582
They could hypothesize about what had gone wrong,

0:05:25.582,0:05:28.694
but they really had no way of knowing what led

0:05:28.694,0:05:30.866
to the terrible events.

0:05:30.866,0:05:35.049
And stem cells really have given us the black box

0:05:35.049,0:05:39.017
for diseases, and it's an unprecedented window.

0:05:39.017,0:05:42.262
It really is extraordinary, because you can recapitulate

0:05:42.262,0:05:45.509
many, many diseases in a dish, you can see

0:05:45.509,0:05:49.045
what begins to go wrong in the cellular conversation

0:05:49.045,0:05:51.469
well before you would ever see

0:05:51.469,0:05:54.005
symptoms appear in a patient.

0:05:54.005,0:05:56.528
And this opens up the ability,

0:05:56.528,0:05:59.342
which hopefully will become something that

0:05:59.342,0:06:01.989
is routine in the near term,

0:06:01.989,0:06:06.135
of using human cells to test for drugs.

0:06:06.135,0:06:11.599
Right now, the way we test for drugs is pretty problematic.

0:06:11.599,0:06:14.917
To bring a successful drug to market, it takes, on average,

0:06:14.917,0:06:17.103
13 years — that's one drug —

0:06:17.103,0:06:20.491
with a sunk cost of 4 billion dollars,

0:06:20.491,0:06:25.358
and only one percent of the drugs that start down that road

0:06:25.358,0:06:27.606
are actually going to get there.

0:06:27.606,0:06:29.731
You can't imagine other businesses

0:06:29.731,0:06:31.180
that you would think of going into

0:06:31.180,0:06:32.935
that have these kind of numbers.

0:06:32.935,0:06:34.737
It's a terrible business model.

0:06:34.737,0:06:38.726
But it is really a worse social model because of

0:06:38.726,0:06:42.054
what's involved and the cost to all of us.

0:06:42.054,0:06:45.806
So the way we develop drugs now

0:06:45.806,0:06:49.006
is by testing promising compounds on --

0:06:49.006,0:06:50.886
We didn't have disease modeling with human cells,

0:06:50.886,0:06:54.350
so we'd been testing them on cells of mice

0:06:54.350,0:06:58.017
or other creatures or cells that we engineer,

0:06:58.017,0:07:01.078
but they don't have the characteristics of the diseases

0:07:01.078,0:07:03.414
that we're actually trying to cure.

0:07:03.414,0:07:06.460
You know, we're not mice, and you can't go into

0:07:06.460,0:07:08.878
a living person with an illness

0:07:08.878,0:07:11.806
and just pull out a few brain cells or cardiac cells

0:07:11.806,0:07:14.095
and then start fooling around in a lab to test

0:07:14.095,0:07:17.656
for, you know, a promising drug.

0:07:17.656,0:07:21.241
But what you can do with human stem cells, now,

0:07:21.241,0:07:25.578
is actually create avatars, and you can create the cells,

0:07:25.578,0:07:27.545
whether it's the live motor neurons

0:07:27.545,0:07:30.555
or the beating cardiac cells or liver cells

0:07:30.555,0:07:34.664
or other kinds of cells, and you can test for drugs,

0:07:34.664,0:07:37.789
promising compounds, on the actual cells

0:07:37.789,0:07:41.420
that you're trying to affect, and this is now,

0:07:41.420,0:07:44.234
and it's absolutely extraordinary,

0:07:44.234,0:07:47.390
and you're going to know at the beginning,

0:07:47.390,0:07:51.134
the very early stages of doing your assay development

0:07:51.134,0:07:54.523
and your testing, you're not going to have to wait 13 years

0:07:54.523,0:07:57.842
until you've brought a drug to market, only to find out

0:07:57.842,0:08:02.898
that actually it doesn't work, or even worse, harms people.

0:08:02.898,0:08:07.238
But it isn't really enough just to look at

0:08:07.238,0:08:11.020
the cells from a few people or a small group of people,

0:08:11.020,0:08:12.664
because we have to step back.

0:08:12.664,0:08:14.515
We've got to look at the big picture.

0:08:14.515,0:08:17.651
Look around this room. We are all different,

0:08:17.651,0:08:20.391
and a disease that I might have,

0:08:20.391,0:08:23.268
if I had Alzheimer's disease or Parkinson's disease,

0:08:23.268,0:08:27.034
it probably would affect me differently than if

0:08:27.034,0:08:28.675
one of you had that disease,

0:08:28.675,0:08:33.020
and if we both had Parkinson's disease,

0:08:33.020,0:08:35.288
and we took the same medication,

0:08:35.288,0:08:38.035
but we had different genetic makeup,

0:08:38.035,0:08:40.320
we probably would have a different result,

0:08:40.320,0:08:44.051
and it could well be that a drug that worked wonderfully

0:08:44.051,0:08:47.630
for me was actually ineffective for you,

0:08:47.630,0:08:52.322
and similarly, it could be that a drug that is harmful for you

0:08:52.322,0:08:56.624
is safe for me, and, you know, this seems totally obvious,

0:08:56.624,0:08:59.352
but unfortunately it is not the way

0:08:59.352,0:09:02.538
that the pharmaceutical industry has been developing drugs

0:09:02.538,0:09:06.524
because, until now, it hasn't had the tools.

0:09:06.524,0:09:08.816
And so we need to move away

0:09:08.816,0:09:11.770
from this one-size-fits-all model.

0:09:11.770,0:09:14.947
The way we've been developing drugs is essentially

0:09:14.947,0:09:16.326
like going into a shoe store,

0:09:16.326,0:09:18.609
no one asks you what size you are, or

0:09:18.609,0:09:20.819
if you're going dancing or hiking.

0:09:20.819,0:09:23.627
They just say, "Well, you have feet, here are your shoes."

0:09:23.627,0:09:27.227
It doesn't work with shoes, and our bodies are

0:09:27.227,0:09:30.699
many times more complicated than just our feet.

0:09:30.699,0:09:33.240
So we really have to change this.

0:09:33.240,0:09:38.424
There was a very sad example of this in the last decade.

0:09:38.424,0:09:41.072
There's a wonderful drug, and a class of drugs actually,

0:09:41.072,0:09:43.752
but the particular drug was Vioxx, and

0:09:43.752,0:09:48.128
for people who were suffering from severe arthritis pain,

0:09:48.128,0:09:51.520
the drug was an absolute lifesaver,

0:09:51.520,0:09:56.600
but unfortunately, for another subset of those people,

0:09:56.600,0:10:01.369
they suffered pretty severe heart side effects,

0:10:01.369,0:10:04.097
and for a subset of those people, the side effects were

0:10:04.097,0:10:07.994
so severe, the cardiac side effects, that they were fatal.

0:10:07.994,0:10:12.036
But imagine a different scenario,

0:10:12.036,0:10:16.338
where we could have had an array, a genetically diverse array,

0:10:16.338,0:10:19.964
of cardiac cells, and we could have actually tested

0:10:19.964,0:10:25.045
that drug, Vioxx, in petri dishes, and figured out,

0:10:25.045,0:10:28.789
well, okay, people with this genetic type are going to have

0:10:28.789,0:10:33.789
cardiac side effects, people with these genetic subgroups

0:10:33.789,0:10:38.933
or genetic shoes sizes, about 25,000 of them,

0:10:38.933,0:10:41.693
are not going to have any problems.

0:10:41.693,0:10:44.308
The people for whom it was a lifesaver

0:10:44.308,0:10:45.985
could have still taken their medicine.

0:10:45.985,0:10:50.371
The people for whom it was a disaster, or fatal,

0:10:50.371,0:10:52.462
would never have been given it, and

0:10:52.462,0:10:55.045
you can imagine a very different outcome for the company,

0:10:55.045,0:10:57.813
who had to withdraw the drug.

0:10:57.813,0:11:00.629
So that is terrific,

0:11:00.629,0:11:02.463
and we thought, all right,

0:11:02.463,0:11:05.222
as we're trying to solve this problem,

0:11:05.222,0:11:07.419
clearly we have to think about genetics,

0:11:07.419,0:11:10.253
we have to think about human testing,

0:11:10.253,0:11:11.832
but there's a fundamental problem,

0:11:11.832,0:11:14.531
because right now, stem cell lines,

0:11:14.531,0:11:16.241
as extraordinary as they are,

0:11:16.241,0:11:17.985
and lines are just groups of cells,

0:11:17.985,0:11:22.317
they are made by hand, one at a time,

0:11:22.317,0:11:24.541
and it takes a couple of months.

0:11:24.541,0:11:28.907
This is not scalable, and also when you do things by hand,

0:11:28.907,0:11:30.450
even in the best laboratories,

0:11:30.450,0:11:33.611
you have variations in techniques,

0:11:33.611,0:11:36.792
and you need to know, if you're making a drug,

0:11:36.792,0:11:38.690
that the Aspirin you're going to take out of the bottle

0:11:38.690,0:11:41.130
on Monday is the same as the Aspirin

0:11:41.130,0:11:43.211
that's going to come out of the bottle on Wednesday.

0:11:43.211,0:11:47.002
So we looked at this, and we thought, okay,

0:11:47.002,0:11:50.154
artisanal is wonderful in, you know, your clothing

0:11:50.154,0:11:53.098
and your bread and crafts, but

0:11:53.098,0:11:56.081
artisanal really isn't going to work in stem cells,

0:11:56.081,0:11:58.471
so we have to deal with this.

0:11:58.471,0:12:02.391
But even with that, there still was another big hurdle,

0:12:02.391,0:12:05.955
and that actually brings us back to

0:12:05.955,0:12:08.339
the mapping of the human genome, because

0:12:08.339,0:12:11.050
we're all different.

0:12:11.050,0:12:13.882
We know from the sequencing of the human genome

0:12:13.882,0:12:16.439
that it's shown us all of the A's, C's, G's and T's

0:12:16.439,0:12:18.907
that make up our genetic code,

0:12:18.907,0:12:23.176
but that code, by itself, our DNA,

0:12:23.176,0:12:27.775
is like looking at the ones and zeroes of the computer code

0:12:27.775,0:12:30.600
without having a computer that can read it.

0:12:30.600,0:12:33.888
It's like having an app without having a smartphone.

0:12:33.888,0:12:37.772
We needed to have a way of bringing the biology

0:12:37.772,0:12:39.981
to that incredible data,

0:12:39.981,0:12:43.096
and the way to do that was to find

0:12:43.096,0:12:45.783
a stand-in, a biological stand-in,

0:12:45.783,0:12:49.808
that could contain all of the genetic information,

0:12:49.808,0:12:52.336
but have it be arrayed in such a way

0:12:52.336,0:12:55.200
as it could be read together

0:12:55.200,0:12:58.456
and actually create this incredible avatar.

0:12:58.456,0:13:02.160
We need to have stem cells from all the genetic sub-types

0:13:02.160,0:13:05.112
that represent who we are.

0:13:05.112,0:13:07.872
So this is what we've built.

0:13:07.872,0:13:11.192
It's an automated robotic technology.

0:13:11.192,0:13:13.800
It has the capacity to produce thousands and thousands

0:13:13.800,0:13:18.039
of stem cell lines. It's genetically arrayed.

0:13:18.039,0:13:21.788
It has massively parallel processing capability,

0:13:21.788,0:13:25.108
and it's going to change the way drugs are discovered,

0:13:25.108,0:13:28.943
we hope, and I think eventually what's going to happen

0:13:28.943,0:13:31.142
is that we're going to want to re-screen drugs,

0:13:31.142,0:13:33.633
on arrays like this, that already exist,

0:13:33.633,0:13:35.504
all of the drugs that currently exist,

0:13:35.504,0:13:38.415
and in the future, you're going to be taking drugs

0:13:38.415,0:13:41.287
and treatments that have been tested for side effects

0:13:41.287,0:13:43.590
on all of the relevant cells,

0:13:43.590,0:13:46.743
on brain cells and heart cells and liver cells.

0:13:46.743,0:13:50.072
It really has brought us to the threshold

0:13:50.072,0:13:52.286
of personalized medicine.

0:13:52.286,0:13:56.727
It's here now, and in our family,

0:13:56.727,0:13:59.665
my son has type 1 diabetes,

0:13:59.665,0:14:02.313
which is still an incurable disease,

0:14:02.313,0:14:05.755
and I lost my parents to heart disease and cancer,

0:14:05.755,0:14:09.488
but I think that my story probably sounds familiar to you,

0:14:09.488,0:14:13.718
because probably a version of it is your story.

0:14:13.718,0:14:17.662
At some point in our lives, all of us,

0:14:17.662,0:14:20.398
or people we care about, become patients,

0:14:20.398,0:14:23.007
and that's why I think that stem cell research

0:14:23.007,0:14:26.390
is incredibly important for all of us.

0:14:26.390,0:14:30.058
Thank you. (Applause)

0:14:30.058,0:14:37.166
(Applause)