Our best hope in fighting global disease is open collaboration | Alexis Kaushansky | TEDxSeattle

I’m a scientist I was trained to define

I’m a scientist I was trained to define a specific problem make a hypothesis and

a specific problem make a hypothesis and

a specific problem make a hypothesis and then generate data that either supports

then generate data that either supports

then generate data that either supports or disproves it well in theory this

or disproves it well in theory this

or disproves it well in theory this process should allow us to answer

process should allow us to answer

process should allow us to answer questions both small and large in

questions both small and large in

questions both small and large in practice I found that when I did this

practice I found that when I did this

practice I found that when I did this work alone I typically only asked

work alone I typically only asked

work alone I typically only asked questions where I could already see a

questions where I could already see a

questions where I could already see a clear path to the answer but for many of

clear path to the answer but for many of

clear path to the answer but for many of the most important questions that we

the most important questions that we

the most important questions that we have to ask in the world we’ve tried the

have to ask in the world we’ve tried the

have to ask in the world we’ve tried the clear path doesn’t always work when I

clear path doesn’t always work when I

clear path doesn’t always work when I started to think about working on a big

started to think about working on a big

started to think about working on a big problem like malaria

problem like malaria

problem like malaria I heard words like crazy insane

I heard words like crazy insane

I heard words like crazy insane intractable and plenty of other phrases

intractable and plenty of other phrases

intractable and plenty of other phrases that I won’t share with you today and

that I won’t share with you today and

that I won’t share with you today and rightfully so

rightfully so

rightfully so malaria kills half a million people each

malaria kills half a million people each

malaria kills half a million people each year and debilitates

year and debilitates

year and debilitates a quarter of a billion mainly pregnant

a quarter of a billion mainly pregnant

a quarter of a billion mainly pregnant women and children it compresses the

women and children it compresses the

women and children it compresses the economies of nations this is not only

economies of nations this is not only

economies of nations this is not only because so many people die of the

because so many people die of the

because so many people die of the disease but because others are too sick

disease but because others are too sick

disease but because others are too sick to get the education that they both need

to get the education that they both need

to get the education that they both need and deserve

and deserve

and deserve over time I started to work think that

over time I started to work think that

over time I started to work think that working on a problem like malaria a big

working on a problem like malaria a big

working on a problem like malaria a big global social justice problem thought to

global social justice problem thought to

global social justice problem thought to be intractable thought to be crazy

be intractable thought to be crazy

be intractable thought to be crazy required that we asked different

required that we asked different

required that we asked different questions

questions

questions I wondered if working with people from a

I wondered if working with people from a

I wondered if working with people from a diverse range of backgrounds would allow

diverse range of backgrounds would allow

diverse range of backgrounds would allow us to ask questions that we dare not ask

us to ask questions that we dare not ask

us to ask questions that we dare not ask by ourselves well it’s a nice idea but

by ourselves well it’s a nice idea but

by ourselves well it’s a nice idea but if we’re really considering the

if we’re really considering the

if we’re really considering the unexpected if we’re really throwing

unexpected if we’re really throwing

unexpected if we’re really throwing ourselves open to all possibilities

ourselves open to all possibilities

ourselves open to all possibilities where do we start when do we stop

where do we start when do we stop

where do we start when do we stop considering and start actually do

considering and start actually do

considering and start actually do believe it or not reality can actually

believe it or not reality can actually

believe it or not reality can actually help us here the reality of the problem

help us here the reality of the problem

help us here the reality of the problem creates constraints and as engineers

creates constraints and as engineers

creates constraints and as engineers will tell us constraints can be key to

will tell us constraints can be key to

will tell us constraints can be key to problem solving while some might see

problem solving while some might see

problem solving while some might see constraints as hurdles roadblocks to

constraints as hurdles roadblocks to

constraints as hurdles roadblocks to getting the job done if they’re applied

getting the job done if they’re applied

getting the job done if they’re applied correctly constraints can be the origin

correctly constraints can be the origin

correctly constraints can be the origin of creative and innovative solutions let

of creative and innovative solutions let

of creative and innovative solutions let me give you a couple of examples first

me give you a couple of examples first

me give you a couple of examples first there are technical constraints the

there are technical constraints the

there are technical constraints the malaria parasite is transmitted to

malaria parasite is transmitted to

malaria parasite is transmitted to humans by mosquito bite we can’t grow

humans by mosquito bite we can’t grow

humans by mosquito bite we can’t grow the form of the parasite that infects us

the form of the parasite that infects us

the form of the parasite that infects us in the lab without mosquitoes so doing

in the lab without mosquitoes so doing

in the lab without mosquitoes so doing malaria research means growing tens of

malaria research means growing tens of

malaria research means growing tens of thousands of mosquitoes essentially as

thousands of mosquitoes essentially as

thousands of mosquitoes essentially as little malaria production factories we

little malaria production factories we

little malaria production factories we then hand/eye sect the salivary glands

then hand/eye sect the salivary glands

then hand/eye sect the salivary glands to isolate the parasite after some

to isolate the parasite after some

to isolate the parasite after some practice it’s not quite as hard as it

practice it’s not quite as hard as it

practice it’s not quite as hard as it sounds it’s also not exactly easy it

sounds it’s also not exactly easy it

sounds it’s also not exactly easy it makes studying malaria tough after hours

makes studying malaria tough after hours

makes studying malaria tough after hours of dissection we can isolate millions of

of dissection we can isolate millions of

of dissection we can isolate millions of parasites unfortunately what’s typically

parasites unfortunately what’s typically

parasites unfortunately what’s typically considered a good starting point is

considered a good starting point is

considered a good starting point is billions that means that after we

billions that means that after we

billions that means that after we dissect and dissect and dissect and

dissect and dissect and dissect and

dissect and dissect and dissect and dissect we still don’t have enough

dissect we still don’t have enough

dissect we still don’t have enough material to do even a conventional

material to do even a conventional

material to do even a conventional experiment next there are economic

experiment next there are economic

experiment next there are economic constraints of working on malaria there

constraints of working on malaria there

constraints of working on malaria there are drugs that you and I take when we

are drugs that you and I take when we

are drugs that you and I take when we travel to malaria endemic areas but

travel to malaria endemic areas but

travel to malaria endemic areas but these drugs are only effective for a few

these drugs are only effective for a few

these drugs are only effective for a few years before drug resistance emerges and

years before drug resistance emerges and

years before drug resistance emerges and we need a new drug but it takes ten

we need a new drug but it takes ten

we need a new drug but it takes ten years two billion dollars to make a drug

years two billion dollars to make a drug

years two billion dollars to make a drug from scratch and the average person who

from scratch and the average person who

from scratch and the average person who gets malaria lives on only $2 a day you

gets malaria lives on only $2 a day you

gets malaria lives on only $2 a day you don’t have to be an economist to see the

don’t have to be an economist to see the

don’t have to be an economist to see the writing on the wall the numbers just

writing on the wall the numbers just

writing on the wall the numbers just don’t add up

don’t add up

don’t add up there’s just not much economic incentive

there’s just not much economic incentive

there’s just not much economic incentive to make new anti malarial drugs

to make new anti malarial drugs

to make new anti malarial drugs now these technical and economic

now these technical and economic

now these technical and economic constraints could have caused us to

constraints could have caused us to

constraints could have caused us to throw up our hands but instead they

throw up our hands but instead they

throw up our hands but instead they forced us to look broadly for a solution

forced us to look broadly for a solution

forced us to look broadly for a solution a solution based on these constraints

a solution based on these constraints

a solution based on these constraints started with what might sound a bit like

started with what might sound a bit like

started with what might sound a bit like a Rube Goldberg device a 1990s style

a Rube Goldberg device a 1990s style

a Rube Goldberg device a 1990s style dot-matrix printer that we use to print

dot-matrix printer that we use to print

dot-matrix printer that we use to print malaria parasites perhaps some of you

malaria parasites perhaps some of you

malaria parasites perhaps some of you have fond memories of your first printer

have fond memories of your first printer

have fond memories of your first printer at home it made a funny sound as the

at home it made a funny sound as the

at home it made a funny sound as the print head moved back and forth

print head moved back and forth

print head moved back and forth essentially stamping ink on the page we

essentially stamping ink on the page we

essentially stamping ink on the page we do something similar but instead of

do something similar but instead of

do something similar but instead of printing ink we print malaria parasites

printing ink we print malaria parasites

printing ink we print malaria parasites in teeny teeny droplets each droplet

in teeny teeny droplets each droplet

in teeny teeny droplets each droplet then becomes a site of an experiment

then becomes a site of an experiment

then becomes a site of an experiment because the droplets are so small they

because the droplets are so small they

because the droplets are so small they don’t require much material and we can

don’t require much material and we can

don’t require much material and we can do thousands of experiments on a single

do thousands of experiments on a single

do thousands of experiments on a single microscope slide this workaround allows

microscope slide this workaround allows

microscope slide this workaround allows us to ask bigger broader questions

us to ask bigger broader questions

us to ask bigger broader questions leaving open the possibility that we’ll

leaving open the possibility that we’ll

leaving open the possibility that we’ll come up with unexpected results these

come up with unexpected results these

come up with unexpected results these experiments are greater than any single

experiments are greater than any single

experiments are greater than any single experiment we would do in isolation what

experiment we would do in isolation what

experiment we would do in isolation what we came up with was something we never

we came up with was something we never

we came up with was something we never would have considered had we not first

would have considered had we not first

would have considered had we not first used our printer to miniaturize our

used our printer to miniaturize our

used our printer to miniaturize our experiments that malaria parasites bear

experiments that malaria parasites bear

experiments that malaria parasites bear striking resemblance to another disease

striking resemblance to another disease

striking resemblance to another disease that’s much better studied cancer now

that’s much better studied cancer now

that’s much better studied cancer now I’ll be honest the day that we made this

I’ll be honest the day that we made this

I’ll be honest the day that we made this discovery was a very exciting day in the

discovery was a very exciting day in the

discovery was a very exciting day in the lab but before we could fully celebrate

lab but before we could fully celebrate

lab but before we could fully celebrate we realized we didn’t really know what

we realized we didn’t really know what

we realized we didn’t really know what to do with these data this is where the

to do with these data this is where the

to do with these data this is where the economic constraints came in because

economic constraints came in because

economic constraints came in because there’s really not much of a budget to

there’s really not much of a budget to

there’s really not much of a budget to make new anti malarial drugs from

make new anti malarial drugs from

make new anti malarial drugs from scratch we decided to consider the

scratch we decided to consider the

scratch we decided to consider the possibility that drugs that had all

possibility that drugs that had all

possibility that drugs that had all even developed for other diseases might

even developed for other diseases might

even developed for other diseases might be effective against malaria but how do

be effective against malaria but how do

be effective against malaria but how do we know what drugs to use

we know what drugs to use

we know what drugs to use fortunately computer scientists and

fortunately computer scientists and

fortunately computer scientists and mathematicians have a wide variety of

mathematicians have a wide variety of

mathematicians have a wide variety of tools at their disposal that aim to take

tools at their disposal that aim to take

tools at their disposal that aim to take data and turn it into predictions so we

data and turn it into predictions so we

data and turn it into predictions so we reached out to our colleagues and asked

reached out to our colleagues and asked

reached out to our colleagues and asked a simple question given all the data we

a simple question given all the data we

a simple question given all the data we had collected what drugs might be

had collected what drugs might be

had collected what drugs might be effective against malaria and what drugs

effective against malaria and what drugs

effective against malaria and what drugs aren’t worth a shot given the limited

aren’t worth a shot given the limited

aren’t worth a shot given the limited resources we have at our disposal by

resources we have at our disposal by

resources we have at our disposal by working with computer scientists we were

working with computer scientists we were

working with computer scientists we were able to identify specific drugs that had

able to identify specific drugs that had

able to identify specific drugs that had already been developed against cancer

already been developed against cancer

already been developed against cancer and might be effective against malaria

and might be effective against malaria

and might be effective against malaria what’s more is that these drugs have

what’s more is that these drugs have

what’s more is that these drugs have already been found to be safe in people

already been found to be safe in people

already been found to be safe in people but in some cases they’re not very

but in some cases they’re not very

but in some cases they’re not very effective against cancer so they’re just

effective against cancer so they’re just

effective against cancer so they’re just sitting on a shelf but against malaria

sitting on a shelf but against malaria

sitting on a shelf but against malaria these drugs can prevent some laboratory

these drugs can prevent some laboratory

these drugs can prevent some laboratory mice from ever getting sick after

mice from ever getting sick after

mice from ever getting sick after they’ve been exposed to the infection

they’ve been exposed to the infection

they’ve been exposed to the infection what’s even more exciting is the way

what’s even more exciting is the way

what’s even more exciting is the way that these drugs work they don’t target

that these drugs work they don’t target

that these drugs work they don’t target the parasite directly and instead they

the parasite directly and instead they

the parasite directly and instead they change the environment that the parasite

change the environment that the parasite

change the environment that the parasite needs in order to thrive one example of

needs in order to thrive one example of

needs in order to thrive one example of this is drugs that target a family of

this is drugs that target a family of

this is drugs that target a family of proteins called tumor suppressors just

proteins called tumor suppressors just

proteins called tumor suppressors just as the name suggests when there are high

as the name suggests when there are high

as the name suggests when there are high levels of these proteins they suppress

levels of these proteins they suppress

levels of these proteins they suppress tumors meaning no cancer what we found

tumors meaning no cancer what we found

tumors meaning no cancer what we found was that these proteins are not just

was that these proteins are not just

was that these proteins are not just tumor suppressors they’re malaria

tumor suppressors they’re malaria

tumor suppressors they’re malaria suppressors as well what this means is

suppressors as well what this means is

suppressors as well what this means is that drugs that were originally

that drugs that were originally

that drugs that were originally developed to suppress tumors can also

developed to suppress tumors can also

developed to suppress tumors can also make our bodies into better malaria

make our bodies into better malaria

make our bodies into better malaria fighting machines and since these drugs

fighting machines and since these drugs

fighting machines and since these drugs don’t target the parasite directly

don’t target the parasite directly

don’t target the parasite directly there’s almost no chance that the

there’s almost no chance that the

there’s almost no chance that the parasite will develop resistance to the

parasite will develop resistance to the

parasite will develop resistance to the drugs not only could this approach bring

drugs not only could this approach bring

drugs not only could this approach bring old drugs back to life it might make

old drugs back to life it might make

old drugs back to life it might make them effective

them effective

them effective for longer we’re even starting to ask if

for longer we’re even starting to ask if

for longer we’re even starting to ask if it could these drugs could be effective

it could these drugs could be effective

it could these drugs could be effective against other infections as well in this

against other infections as well in this

against other infections as well in this case it was a combination of working

case it was a combination of working

case it was a combination of working with computer scientists the

with computer scientists the

with computer scientists the appropriation of an unusually engineered

appropriation of an unusually engineered

appropriation of an unusually engineered instrument and the economic constraints

instrument and the economic constraints

instrument and the economic constraints placed on us by working on malaria that

placed on us by working on malaria that

placed on us by working on malaria that led to the real breakthrough by working

led to the real breakthrough by working

led to the real breakthrough by working together with unpredictable allies we

together with unpredictable allies we

together with unpredictable allies we were able to carve out a path forward in

were able to carve out a path forward in

were able to carve out a path forward in the fight against malaria we never could

the fight against malaria we never could

the fight against malaria we never could have done it alone

have done it alone

have done it alone now I’m a scientist through and through

now I’m a scientist through and through

now I’m a scientist through and through everybody who knows me will tell you

everybody who knows me will tell you

everybody who knows me will tell you that I absolutely love it

that I absolutely love it

that I absolutely love it but I can’t help but think that one of

but I can’t help but think that one of

but I can’t help but think that one of the most important things I do as a

the most important things I do as a

the most important things I do as a scientist is to incorporate and truly

scientist is to incorporate and truly

scientist is to incorporate and truly truly appreciate the insights that come

truly appreciate the insights that come

truly appreciate the insights that come from other disciplines the most

from other disciplines the most

from other disciplines the most important problems that we have to face

important problems that we have to face

important problems that we have to face together now and in the years to come

together now and in the years to come

together now and in the years to come simply are interdisciplinary I actually

simply are interdisciplinary I actually

simply are interdisciplinary I actually spent my early 20s working in political

spent my early 20s working in political

spent my early 20s working in political activism jobs when I started graduate

activism jobs when I started graduate

activism jobs when I started graduate school I thought I was giving up my

school I thought I was giving up my

school I thought I was giving up my passion for social justice in order to

passion for social justice in order to

passion for social justice in order to become a scientist I had no idea how

become a scientist I had no idea how

become a scientist I had no idea how intertwine the two pursuits would become

intertwine the two pursuits would become

intertwine the two pursuits would become the insights that we’ve gained from

the insights that we’ve gained from

the insights that we’ve gained from computer science engineering and biology

computer science engineering and biology

computer science engineering and biology along with the constraints placed on us

along with the constraints placed on us

along with the constraints placed on us by economics and the very real political

by economics and the very real political

by economics and the very real political realities of the world are greater than

realities of the world are greater than

realities of the world are greater than anything we could do alone the

anything we could do alone the

anything we could do alone the infections that shape our lives our

infections that shape our lives our

infections that shape our lives our communities and our world are willing to

communities and our world are willing to

communities and our world are willing to do anything and everything in order to

do anything and everything in order to

do anything and everything in order to keep spreading around the globe we too

keep spreading around the globe we too

keep spreading around the globe we too then must be willing to take advantage

then must be willing to take advantage

then must be willing to take advantage of anything and everything

of anything and everything

of anything and everything in order to eradicate them from the face

in order to eradicate them from the face

in order to eradicate them from the face of the earth to do this we must work

of the earth to do this we must work

of the earth to do this we must work together thanks