The promise of research with stem cells

Calling them "our bodies' own repair kits," Susan Solomon advocates research using lab-grown stem cells. By growing individual pluripotent stem cell lines, her team creates testbeds that could accelerate research into curing diseases -- and perhaps lead to individualized treatment, targeted not just to a particular disease but a particular person.

So, embryonic stem cells

are really incredible cells.

They are our body's own repair kits,

and they're pluripotent, which means they can morph into

all of the cells in our bodies.

Soon, we actually will be able to use stem cells

to replace cells that are damaged or diseased.

But that's not what I want to talk to you about,

because right now there are some really

extraordinary things that we are doing with stem cells

that are completely changing

the way we look and model disease,

our ability to understand why we get sick,

and even develop drugs.

I truly believe that stem cell research is going to allow

our children to look at Alzheimer's and diabetes

and other major diseases the way we view polio today,

which is as a preventable disease.

So here we have this incredible field, which has

enormous hope for humanity,

but much like IVF over 35 years ago,

until the birth of a healthy baby, Louise,

this field has been under siege politically and financially.

Critical research is being challenged instead of supported,

and we saw that it was really essential to have

private safe haven laboratories where this work

could be advanced without interference.

And so, in 2005,

we started the New York Stem Cell Foundation Laboratory

so that we would have a small organization that could

do this work and support it.

What we saw very quickly is the world of both medical

research, but also developing drugs and treatments,

is dominated by, as you would expect, large organizations,

but in a new field, sometimes large organizations

really have trouble getting out of their own way,

and sometimes they can't ask the right questions,

and there is an enormous gap that's just gotten larger

between academic research on the one hand

and pharmaceutical companies and biotechs

that are responsible for delivering all of our drugs

and many of our treatments, and so we knew that

to really accelerate cures and therapies, we were going

to have to address this with two things:

new technologies and also a new research model.

Because if you don't close that gap, you really are

exactly where we are today.

And that's what I want to focus on.

We've spent the last couple of years pondering this,

making a list of the different things that we had to do,

and so we developed a new technology,

It's software and hardware,

that actually can generate thousands and thousands of

genetically diverse stem cell lines to create

a global array, essentially avatars of ourselves.

And we did this because we think that it's actually going

to allow us to realize the potential, the promise,

of all of the sequencing of the human genome,

but it's going to allow us, in doing that,

to actually do clinical trials in a dish with human cells,

not animal cells, to generate drugs and treatments

that are much more effective, much safer,

much faster, and at a much lower cost.

So let me put that in perspective for you

and give you some context.

This is an extremely new field.

In 1998, human embryonic stem cells

were first identified, and just nine years later,

a group of scientists in Japan were able to take skin cells

and reprogram them with very powerful viruses

to create a kind of pluripotent stem cell

called an induced pluripotent stem cell,

or what we refer to as an IPS cell.

This was really an extraordinary advance, because

although these cells are not human embryonic stem cells,

which still remain the gold standard,

they are terrific to use for modeling disease

and potentially for drug discovery.

So a few months later, in 2008, one of our scientists

built on that research. He took skin biopsies,

this time from people who had a disease,

ALS, or as you call it in the U.K., motor neuron disease.

He turned them into the IPS cells

that I've just told you about, and then he turned those

IPS cells into the motor neurons that actually

were dying in the disease.

So basically what he did was to take a healthy cell

and turn it into a sick cell,

and he recapitulated the disease over and over again

in the dish, and this was extraordinary,

because it was the first time that we had a model

of a disease from a living patient in living human cells.

And as he watched the disease unfold, he was able

to discover that actually the motor neurons were dying

in the disease in a different way than the field

had previously thought. There was another kind of cell

that actually was sending out a toxin

and contributing to the death of these motor neurons,

and you simply couldn't see it

until you had the human model.

So you could really say that

researchers trying to understand the cause of disease

without being able to have human stem cell models

were much like investigators trying to figure out

what had gone terribly wrong in a plane crash

without having a black box, or a flight recorder.

They could hypothesize about what had gone wrong,

but they really had no way of knowing what led

to the terrible events.

And stem cells really have given us the black box

for diseases, and it's an unprecedented window.

It really is extraordinary, because you can recapitulate

many, many diseases in a dish, you can see

what begins to go wrong in the cellular conversation

well before you would ever see

symptoms appear in a patient.

And this opens up the ability,

which hopefully will become something that

is routine in the near term,

of using human cells to test for drugs.

Right now, the way we test for drugs is pretty problematic.

To bring a successful drug to market, it takes, on average,

13 years — that's one drug —

with a sunk cost of 4 billion dollars,

and only one percent of the drugs that start down that road

are actually going to get there.

You can't imagine other businesses

that you would think of going into

that have these kind of numbers.

It's a terrible business model.

But it is really a worse social model because of

what's involved and the cost to all of us.

So the way we develop drugs now

is by testing promising compounds on --

We didn't have disease modeling with human cells,

so we'd been testing them on cells of mice

or other creatures or cells that we engineer,

but they don't have the characteristics of the diseases

that we're actually trying to cure.

You know, we're not mice, and you can't go into

a living person with an illness

and just pull out a few brain cells or cardiac cells

and then start fooling around in a lab to test

for, you know, a promising drug.

But what you can do with human stem cells, now,

is actually create avatars, and you can create the cells,

whether it's the live motor neurons

or the beating cardiac cells or liver cells

or other kinds of cells, and you can test for drugs,

promising compounds, on the actual cells

that you're trying to affect, and this is now,

and it's absolutely extraordinary,

and you're going to know at the beginning,

the very early stages of doing your assay development

and your testing, you're not going to have to wait 13 years

until you've brought a drug to market, only to find out

that actually it doesn't work, or even worse, harms people.

But it isn't really enough just to look at

the cells from a few people or a small group of people,

because we have to step back.

We've got to look at the big picture.

Look around this room. We are all different,

and a disease that I might have,

if I had Alzheimer's disease or Parkinson's disease,

it probably would affect me differently than if

one of you had that disease,

and if we both had Parkinson's disease,

and we took the same medication,

but we had different genetic makeup,

we probably would have a different result,

and it could well be that a drug that worked wonderfully

for me was actually ineffective for you,

and similarly, it could be that a drug that is harmful for you

is safe for me, and, you know, this seems totally obvious,

but unfortunately it is not the way

that the pharmaceutical industry has been developing drugs

because, until now, it hasn't had the tools.

And so we need to move away

from this one-size-fits-all model.

The way we've been developing drugs is essentially

like going into a shoe store,

no one asks you what size you are, or

if you're going dancing or hiking.

They just say, "Well, you have feet, here are your shoes."

It doesn't work with shoes, and our bodies are

many times more complicated than just our feet.

So we really have to change this.

There was a very sad example of this in the last decade.

There's a wonderful drug, and a class of drugs actually,

but the particular drug was Vioxx, and

for people who were suffering from severe arthritis pain,

the drug was an absolute lifesaver,

but unfortunately, for another subset of those people,

they suffered pretty severe heart side effects,

and for a subset of those people, the side effects were

so severe, the cardiac side effects, that they were fatal.

But imagine a different scenario,

where we could have had an array, a genetically diverse array,

of cardiac cells, and we could have actually tested

that drug, Vioxx, in petri dishes, and figured out,

well, okay, people with this genetic type are going to have

cardiac side effects, people with these genetic subgroups

or genetic shoes sizes, about 25,000 of them,

are not going to have any problems.

The people for whom it was a lifesaver

could have still taken their medicine.

The people for whom it was a disaster, or fatal,

would never have been given it, and

you can imagine a very different outcome for the company,

who had to withdraw the drug.

So that is terrific,

and we thought, all right,

as we're trying to solve this problem,

clearly we have to think about genetics,

we have to think about human testing,

but there's a fundamental problem,

because right now, stem cell lines,

as extraordinary as they are,

and lines are just groups of cells,

they are made by hand, one at a time,

and it takes a couple of months.

This is not scalable, and also when you do things by hand,

even in the best laboratories,

you have variations in techniques,

and you need to know, if you're making a drug,

that the Aspirin you're going to take out of the bottle

on Monday is the same as the Aspirin

that's going to come out of the bottle on Wednesday.

So we looked at this, and we thought, okay,

artisanal is wonderful in, you know, your clothing

and your bread and crafts, but

artisanal really isn't going to work in stem cells,

so we have to deal with this.

But even with that, there still was another big hurdle,

and that actually brings us back to

the mapping of the human genome, because

we're all different.

We know from the sequencing of the human genome

that it's shown us all of the A's, C's, G's and T's

that make up our genetic code,

but that code, by itself, our DNA,

is like looking at the ones and zeroes of the computer code

without having a computer that can read it.

It's like having an app without having a smartphone.

We needed to have a way of bringing the biology

to that incredible data,

and the way to do that was to find

a stand-in, a biological stand-in,

that could contain all of the genetic information,

but have it be arrayed in such a way

as it could be read together

and actually create this incredible avatar.

We need to have stem cells from all the genetic sub-types

that represent who we are.

So this is what we've built.

It's an automated robotic technology.

It has the capacity to produce thousands and thousands

of stem cell lines. It's genetically arrayed.

It has massively parallel processing capability,

and it's going to change the way drugs are discovered,

we hope, and I think eventually what's going to happen

is that we're going to want to re-screen drugs,

on arrays like this, that already exist,

all of the drugs that currently exist,

and in the future, you're going to be taking drugs

and treatments that have been tested for side effects

on all of the relevant cells,

on brain cells and heart cells and liver cells.

It really has brought us to the threshold

of personalized medicine.

It's here now, and in our family,

my son has type 1 diabetes,

which is still an incurable disease,

and I lost my parents to heart disease and cancer,

but I think that my story probably sounds familiar to you,

because probably a version of it is your story.

At some point in our lives, all of us,

or people we care about, become patients,

and that's why I think that stem cell research

is incredibly important for all of us.

Thank you. (Applause)

(Applause)