>> Nicole: You know what, it is a fragment.
>> Jim: All right, I'm gonna crank it up a notch.
I'll give you Jim on seven.
[upbeat music]
Welcome to the Blue Sky podcast,
nanotechnology versus the superbugs.
I'm your host Jim Lynch.
>> Nicole: And I'm Nicole Casal Moore.
>> Jim: Today, we're gonna talk about a new way
to fight a growing threat to modern medicine.
Nicole, did you know
that antibiotic resistant superbugs will kill someone
in the United States every 15 minutes?
>> Nicole: Technically, I did know that
because it came up at the news meeting this morning.
I remember something in one of your stories
about how long it takes to develop a new antibiotic
and how difficult it is.
>> Jim: For years and years we've been able to sit back
and just rely on old antibiotics.
Situations where one didn't work,
you just moved onto the other one.
And then in the worst case scenarios
where there were multiple drugs that didn't do the job,
at one point you should bring in that was
at the antibiotic of last resort, you know,
there are one for the heavy hitters that are supposed
to just come in and do the job.
And some of those don't work now either.
So we've been able to rely on old drugs for far too long.
And now that we need new ones,
the economic incentive isn't there.
Actually getting something from the early stages
through testing, through trials
and then onto market,
it takes an awful long time
and antibiotic resistance is not sitting around waiting.
>> Nicole: Do you have any good news
or is this another episode of Jim's podcast of doom?
>> Jim: All I can say is something
about your climate change episode,
but I'll take the high road here
'cause in fact, I do have good news.
Engineers are getting into the antibiotics game
with a mix of big data and made order nanoparticles
that they're calling nanobiotics.
>> Nicole: Nanobiotics. It sounds small.
>> Jim: Yes. Nano is actually the Greek word for we.
Actually they're relatively big.
Regular antibiotics tend to be small molecules,
just a few dozen atoms stuck together.
Nanoparticles on the other hand,
those tend to be a few hundred atoms across.
>> Nicole: Okay. But why would we want nanoparticles
as antibiotics.
>> Jim: I'm gonna get to that
but first I want you to hear how Angela Violi,
a professor of mechanical engineering
and the leader of the Blue Sky project on nanobiotics.
Let's hear how she explains
where we are with regular antibiotics.
What's the situation with antibiotics right now?
Why is there a need to develop a new class of treatments?
>> Angela: Over the last 75 years,
we've been using those miracle drugs
that have cured any type of infection
that we have been seeing.
But there're already infections across the world
for which out of the hundred antibiotics
that we have maybe one two work.
And some cases, none of them works.
The problem is that bacteria are very smart.
And so what they have done is becoming resistant
to our antibiotics at this point.
>> Nicole: I understand that resistance makes bacteria hard
or impossible to kill,
but how do they actually become resistant?
>> Jim: Professor Violi explained
that evolution gave bacteria the mechanism they need
to become resistant to antibiotics,
but we're the ones who gave them the conditions needed
to actually do it.
When bacteria are exposed to antibiotics,
the ones that are susceptible to the antibiotic die.
In our bodies,
that gives us a leg up
so that our immune systems can kill the ones
that stay behind.
>> Nicole: Okay.
So too much exposure to antibiotics means that
by the time the bacteria are infecting our bodies,
it's already only the resistant ones
>> Jim: Yup.
>> Nicole: that are left behind?
>> Jim: Yup. That's it.
And when you dose a person with antibiotics,
it doesn't cut down the number of bacteria.
They're mostly resistant.
It's all on the immune system
to sink or swim just like it was before we had antibiotics.
>> Nicole: That's pretty grim.
So this is all because we go to the doctor with a cold virus
>> Jim: Yup.
>> Nicole: and they prescribed us antibiotics
so we feel like we got our money's worth for the copay.
>> Jim: Yeah. That's part of the story.
But the other part is in the way we farm.
Here's Angela again.
>> Angela: One of the main reason why we have this crisis
at this point is that
if we look at for example the United States,
80% of the prescription in the last years
for antibiotics were mainly not for humans
but more for poultry,
for farm conditions, livestock.
So, antibiotics are given not only, you know,
to survive the crummy condition of a farm.
Once they get in the meat,
then they get in the water also,
and we are exposed to that once we eat meat for example.
Every time the bacteria get exposed to an antibiotic,
he has a chance to break the code for the resistance.
>> Nicole: 80% Of the problem is in agriculture?
>> Jim: Yeah. But things are getting better in that front.
As of 2017, antibiotics that are used
to treat human infections can't be mixed
into animal feed at low doses anymore.
>> Nicole: Wait, they were actually doing that before.
>> Jim: Yeah, weirdly.
It resulted in meat that was lower in fat.
>> Nicole: But we're still treating sick livestock
with antibiotics that are also used by humans?
>> Jim: Yeah, we also treat groups of livestock
when there's a risk of infection spreading.
Other antibiotics used exclusively
for animals can still be mixed into the feed.
We use a lot of antibiotics
in agriculture even now.
>> Nicole: And then the human prescriptions are the other
20% of the problem?
>> Jim: Well, not all of that 20% is a problem
but the centers for disease control estimate
that about a third
of those human prescriptions are actually unnecessary.
>> Nicole: A full third of them.
So people who didn't have a bacterial infection
or were going to get better soon anyway.
So where is this heading?
>> Jim: Well, Professor Violi decided to study
out of the United Kingdom that said
by 2050 deaths due to infections could outpace those
due to cancer.
And those are currently 10 million per year.
To put that in perspective,
global deaths due to antibiotic resistant bacteria are
about 700,000 per year today.
>> Nicole: Okay.
So what are the pharmaceutical companies doing about this?
Are they looking at this new demand
and trying to develop new drugs?
>> Jim: Now that's a quirk of capitalist economics.
Let's hear some more from Professor Violi on this.
>> Angela: If you think about, you know,
like a pharmaceutical company,
it's more interesting to put money in a blood pressure drug
or cholesterol drugs rather than an antibiotic
that people take for like 10 days.
The idea is that it's more convenient
to develop a drug that someone take for the lifetime,
the whole lifetime rather than for 10 days.
>> Nicole: So it's not worth it for them
to make new antibiotics
because bacterial infections aren't chronic conditions.
>> Jim: Yeah, that's the idea.
The economic incentive isn't there.
For me to develop something like an antibiotic
for something that's rare
or is not affecting a huge percentage of the population,
at best I'm gonna make this much money off of that.
The same time,
I can be investing all of my research
and development money in Viagra,
which apparently is very popular drug I've heard.
So that's where pharma puts its eggs.
>> Nicole: You know, it's hard to get money
to treat rare diseases.
It's hard to get money to research them.
Maybe the answer is this fund research
into innovative ideas like we're doing right now.
>> Jim: I also spoke with one of our collaborators,
Scott VanEpps.
He's a Professor of Emergency Medicine.
Not only does big pharma not have a strong incentive
to make new antibiotics,
they also don't have a good technique.
>> Scott: I don't think having big pharma make
a little tweak around the edges
of the current antibiotics that are out there
or even just screening these huge libraries
of chemical compounds that they have.
They've been doing that.
We've doing that for a long time.
We're pretty much dried up that well in my personal opinion
and so it really does need a different approach to it,
and I think that this group is sort of the answer to that.
>> Nicole: He's referring to this Blue Sky project?
>> Jim: Yes.
The nanobiotics Blue Sky team.
When you talk about a different approach,
you mean something drastic.
I think when you and I spoke a year or two ago,
you were talking about the minuscule changes
to drugs can have a big impact,
but it doesn't take much then for the pathogen
to make its own changes, right?
>> Scott: Yeah. They evolve very, very fast, right.
It's a new generation of Ecola every 20 minutes, right.
That's evolutionary speed that humans don't move at at all.
If you're just taking a class of antibiotics we already know
and given a little umph here
to try get around a resistance mechanism,
the next resistance mechanism is equally
as fast around the corner.
In fact, since the advent of penicillin,
the time from the discovery of a new antibiotic
to the discovery of its resistance has been getting shorter.
[upbeat music]
>> Nicole: That is terrifying.
>> Jim: Well, it's not good.
This explanation is really illuminating
in that it's not just the way we use antibiotics
that's the problem,
it's the way we make them.
We're always in this evolutionary arms race,
and we're losing.
Here's Angela again.
>> Angela: The weird things is that the people get excited
about drugs for diabetes for example like insulin.
Insulin can allow you to survive
or a blood pressure drug allow you to survive.
But there are only few drugs that actually can cure you
and antibiotics can institute a cure within days.
They are amazing.
And what people don't understand is that
if we lost antibiotic,
we lose a lot of things including a lot of surgery.
They require a prophylactic,
you know, taking over the antibiotic.
Anything that can install a foreign object in your body.
But I guess more than anything,
we lose the ability to I say leave the daily life.
Because you know, in the moment you can imagine that
even if you scratch yourself,
you can get an infection that can not be solved.
Then I think your way,
your confidence towards life will change.
>> Jim: Already our deaths in the United States
due to antibiotic resistance are about
as high as those from car accidents.
>> Nicole: Wow.
>> Jim: Antibiotic resistance are projected
to increase about tenfold.
>> Nicole: Or you could get into a car accident,
get taken to the hospital
and then die of an antibiotic resistant infection.
>> Jim: You sound like you could use some good news.
>> Nicole: Tell me how nanobiotics can save the day.
>> Jim: Well, antibiotic development is usually a trial
and error process.
Researchers test various molecules
to see if they can kill bacteria without harming us.
Once we have a kind of molecule that works,
we make variations on that.
That's how most of our new antibiotics are made.
That's the strategy that is no longer good enough.
>> Nicole: Like Professor VanEpps was saying
about the pharma companies.
>> Jim: Exactly.
Now what his Blue Sky team wants to do is design a way
to keep producing new classes of antibiotics.
Antibiotics that work in a whole new way.
Before we had to find those antibiotics
in part through luck.
And Professor Violi is trying
to make that serendipity intentional.
>> Angela: The idea is
to intelligently design a nanomaterial.
The reason why we do a nanoparticle
instead of the molecule is that
when you have a nanoparticle,
your degree of freedom, the ability to design,
it's much bigger.
You can look at shape.
You can have a chemical composition.
You can look at charges.
There are a lot of parameters that you can tweak.
>> Jim: It's basically a blank slate for you.
>> Angela: Yes.
That basically you can tweak or tune for your goal.
>> Nicole: So they have more options
for designing nanoparticles than they do with molecules.
>> Jim: Yup.
>> Nicole: Too many options can be overwhelming though.
>> Jim: They're getting some computational help.
It can be overwhelming to try to choose a movie on Netflix
but then they have that algorithm
that sifts through the galaxy of films for recommendations.
>> Nicole: Oh, they're doing machine learning?
>> Jim: Yes. Yes.
And this is one of the really interesting things about it.
>> Angela: We are also creating new database,
collecting data from different resources.
So we are trying to gather as much information as possible
from whatever is available in the literature
but also collaboration with other institutions.
>> Nicole: Help me understand
why they need the other institutions
if they also have the literature.
>> Jim: Well, because what they really need is the failures.
A failed antibiotic doesn't get a paper written about it.
So you wanna basically learn from the mistakes
that've been made.
>> Nicole: Yeah. I've heard about a movement in science
to publish more about what doesn't work.
People have even launched some journals specifically
for negative results.
>> Jim: I'm sure those make trawling reading.
>> Nicole: Well those journals tend to fail too.
>> Jim: Well in this case,
Professor Violi's team does want those pouring results.
They can feed the data into the nanobiotics computer model.
Here's Scott again.
>> Scott: It is a hungry monster for data, right?
The more data it has, the smarter it gets.
And there's such a dearth of that information out there.
We only publish what we're successful with.
If you look at it that way,
then the computer just thinks that everything works
'cause it only ever sees positives.
We actually benefit from our failures a lot more
in this particular case
'cause every failure is a place
where the computer go this is something I shouldn't do.
>> Jim: So we should be rooting for you to fail?
>> Scott: To some degree, yeah. Yeah, I mean.
>> Nicole: So we're hoping for failure?
>> Jim: Well, just enough failure
so that the computer model knows what not to do.
>> Nicole: Okay. But what do they want the computer model
to do?
Why do they think that nanobiotics could be better?
>> Jim: Earlier, we had Professor Violi talk
about how they have more degrees of freedom to play
with when they're designing nanoparticles.
And they do with conventional drugs.
Conventional drugs attack bacteria on just one front
but nanoparticles could work in more ways at once.
>> Nicole: I see.
So they could target more
of the bacteria's potential weak points all
at the same time.
>> Jim: That and also one of their big, strong points.
>> Angela: Biofilm is the structures,
the house if you want.
They're bacteria built together.
>> Scott: And what's interesting about that is
that bacteria that are in a biofilm are pretty resistant
to antibiotics even when there are susceptible to them.
>> Jim: Is that the sort of the strength
in numbers aspect for them?
>> Scott: Yeah. They sort of build like a fortress, right.
It's the best way to think of it.
And that fortress allows them to sort of go sleep
and not be very active
and most of our antibiotics target
the things they're active against.
>> Nicole: So is it that
if the bacterium isn't active,
then the thing that the antibiotic is targeting
basically isn't exposed
so there's nothing for to target?
>> Jim: Well, that's what I got from it
but the biofilms have a couple more tricks.
>> Scott: The other one is they do build a fortress
that limits the amount of antibiotic they can diffuse
to them.
>> Nicole: The antibiotic might not even be able
to reach the bacteria,
let alone hit the target once it gets there.
>> Jim: That and the biofilms actually have one more trick.
>> Scott: There are these what we call persister cells
inside of biofilms that are...
They are like the stem cell of a biofilm.
So you eradicate 90% of the biofilm
in this on one stem cell,
persister cell can then start to repopulate it.
Those things in biofilms make them very difficult to treat
even with conventional antibiotics that an individual cell
in the population would normally be susceptible to.
>> Nicole: Even if we do kill most of the bacteria,
if there's this biofilm fortress thing,
and you've got one
of these nasty persister cells left alive,
your whole infection can come raging back.
>> Jim: Yeah. That's the challenge.
And it's worse for implants like pacemaker electrodes
and artificial knees.
Biofilms, they seem to be able to build safe havens
around these non-living structures
where immune cells can't come from sides.
>> Nicole: So this is what Professor Violi was talking about
when she said that eventually we could not be able
to perform surgeries.
Do I have that right?
>> Jim: Yeah. This is part of it.
Surgeries with implants are gonna be at particular risk.
>> Nicole: So what can you do about a biofilm?
>> Jim: You break it up.
That's one of the things that the team is trying to do,
and they've even had some early success.
You'll hear more about that in a future episode.
For now, I wanna talk more about the big picture
for this project, the computer model.
[upbeat music]
They wanted to have that up and running
at the end of the first year of the project.
>> Nicole: Wow. They thought they could get that going
inside a year?
>> Jim: Professor Violi is not to be underestimated.
The job basically entails collecting
whatever data they can find about what chemicals
and nanoparticles affect what bacteria.
And then making the machine learning computer program
that control the database
and look for trends.
What features seem to be best
for attacking a particular type of bacteria.
>> Angela: So basically, we wanna be able to classify data.
What that means is that relate
to somehow nanoparticle characteristic and the efficacy.
Also, we are interested in identifying the hypothesis
of the interactions between nanoparticle and bacteria
so that eventually the final goal is
to have a target profile of nanoparticles.
>> Jim: Basically, a checklist for what you want
at nanoparticle to include.
>> Angela: So I would like to say to this is engine
if you wanna call an engine.
>> Jim: I'm just gonna note here
that our producer Kate wanted to call the engine an Oracle.
Angela was definitely not comfortable with that.
>> Nicole: Some kind of prophecy maker?
>> Jim: A prophet of antibacterial activity.
>> Nicole: Intelligent designer of nanoparticles.
>> Jim: I can see you rolling your eyes Kate.
Professor Violi went with computational engine.
>> Angela: Engine. If you wanna call an engine,
a computational engine
to tell me your ideal nanoparticle should have.
About this a shape, this a charge, this composition
so that we can intelligently design that.
So the expensive part like the first step,
when we talk about 10,000 molecules is going
to disappear at this point
because with this kind of a trick if you want,
we can use only 500 nanoparticles.
That's what we hope.
And so 500 experiments are doable.
It's a paradigm shift going from screening compounds
to intelligently design.
What I mean by intelligently is using machine learning
to provide hypothesis of what could be the best design.
>> Nicole: Wait, they have to start with 10,000 molecules?
>> Jim: That's how antibiotic discovery works
at pharma companies right now.
They'll make 10,000 molecules
because molecules they just aren't that hard to make.
Then they'll see how well they work
against whatever bacteria they're targeting.
Nanoparticles on the other hand,
those are a bit harder to make.
So the Blue Sky team can't do the brute force route.
They need to be smart
about which nanoparticles they produce.
>> Nicole: So they are making this computational engine
to filter out the possibilities
and find their 500 best candidates.
>> Jim: Right. Then they'll make those.
>> Nicole: They're still gonna have to do some trial
and error with their 500 nanoparticles.
But it's like 5% of the trial and error
that they were doing with the molecules.
>> Jim: Angela, you used the word paradigm,
the words paradigm shift.
>> Angela: Yeah.
>> Jim: When you're finished here,
what do you hope
that the pharmaceutical industry would take away
from what you've done?
>> Angela: I'm hoping
to get the pharmaceutical company involved much earlier.
So I'm not thinking about the end of the Blue Sky,
but awfully if we are able already
to come up with this computational engine
that can demonstrate the ability to, first of all,
create classification or correlation
between structures and activity in terms of bacteria,
that will be a great advancement
for the pharmaceutical company also
because basically what we are saying is the ability
to reduce the timeline
to develop a product.
>> Nicole: That's really exciting
that the nanobiotics group is trying to get this
to industry before Blue Sky is even over.
>> Jim: Well that's their hope
and one thing she stresses that this isn't
about making next nanobiotic,
it's about the method
that will help us keep winning the arms race
against bacteria.
>> Angela: If we develop the nanobiotic right now
in the next, you know, hundred years,
they will not be useful anymore.
But with this Blue Sky what we are aiming is
to just develop this computational machine.
Is a framework that can be...
It's like spinning the wheel
and then maybe something else comes up
and then we can still use the same approach
to come up with a solution.
>> Nicole: Are they also making some antibiotics?
>> Jim: They are.
[upbeat music]
We'll hear about their biofilm buster made
from quantum dots next time along with an update
on the computational engine.
Till then I'm your host, Jim Lynch.
>> Nicole: And I'm Nicole Casal Moore.
>> Jim: See you next time, everybody.