Biobot Analytics founders Mariana Matus and Newsha Ghaeli first met in a poop lab. Yep, you read that correctly...

Their company has been working with government and corporate clients since 2017 to analyze disease levels and other biomarkers in our wastewater. Their insights have been used to predict spikes in Covid and other infections, help local officials address drug use in their communities, and much more. 

This week on How I Built This Lab, Mariana and Newsha talk with Guy about the innovation that can happen at the intersection of disciplines — Mariana is a scientist from Mexico, Newsha an architect from Canada. The women also share their vision for a future where cities better leverage the ‘data centers’ of our sewers to address chronic health issues and prepare for future pandemics. 

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Hello and welcome to How I Built This Lab.

So every time you go to the bathroom, you are releasing a trove of information.

So much so that wastewater treatment plants are kind of like massive data centers.

There is So much we can find out about our health from our poo and pee.

And the technology to analyze this data has grown at a really fast pace over the past decade.

And so about 5 years ago, 2 women in Boston, 1 a biologist named Mariana Matus, the other an architect, Nusha Ghaeli, got together to start a company to analyze sewage and to find out whether they could detect things like diseases and viral outbreaks in specific communities.

It turns out you can, And you can find out a whole bunch of other things by looking at wastewater, for example, opioid usage.

Mariana Anoush's company, called BioBot Analytics, works with public health agencies and even some private companies to help them understand how to get ahead of potential crises like a new outbreak of COVID.

So I was at MIT, I was doing a PhD in computational biology, and I was working in a poop lab.

A lab where we would get poop samples from people, from mice and other animals, and sequence the community of bacteria that live in the poop, in the gut, to better understand the health of that individual.

So we had begun to look at the collective biome, our wastewater, our collective poop as a source of data, particularly in collaboration with another lab that specializes in smart city technologies.

And that's where Nusha comes in because you are an architect by training.

So in 2014, I finished my graduate studies in architecture in Canada at McGill University.

And I moved to the Boston area to start a fellowship at MIT on the future of our cities.

So I was really interested in looking at various data sources, geolocated data in particular, that we're generating in our cities to help us address some big fundamental urban challenges.

And it was through that lens that I met Mariana.

I learned about the power of sewage or the potential of the data in our sewer systems.

And to me, that was the future of our cities.

You're an architect and working on smart cities, probably you were focused on like gathering data from gas meters or from, you know, cell phone towers.

Like all that kind of data, which is still very valuable, but you probably weren't even thinking about wastewater data.

This is really, I think, exemplary of innovation that happens at the intersection of disciplines.

Because absolutely, like my lab traditionally would look at telco data, mobility data, data streams that are more common in the whole smart city, urban tech space.

I mean, even looking at human waste and trying to analyze it and assess, you know, a bunch of data, I mean, even in 2014, which isn't that long ago, that was pretty innovative, just doing that, wasn't it?

Over time, people have been studying samples that are more easy to collect, like serum or blood samples, saliva, swabs.

But not many people like to collect and give poop for research.

So, it's definitely more of a newer thing.

And in particular, wastewater has been massively overlooked as a critical source of data to understand population health.

And I think that the beauty of tapping into pee, poo, or wastewater as a data source is that we naturally are excreting it out.

So rather than needing to be invasive and need to be poked or swapped in order to get data, we naturally are producing this data every day and actually disposing it and collecting it into our wastewater infrastructure.

I mean, essentially, sewers, right, and wastewater treatment facilities all over the world are these massive data centers, in a sense.

It's like bytes of data flowing under our feet through pipes in the city.

And I think once you realize that, it's kind of impossible to go back and ignore it.

Marc Thiessen Alright, so Nusha, you meet Mariana, she's working on this clinical work at MIT.

And how did, what did you start to work on together?

Yeah, so Mariana had led a grant proposal, and they were awarded a few million dollars in grant funding, which was pretty incredible.

And so when I met Mariana, that funding had just come through, and they were ready to start building out a project team to take this work forward over the next few years.

And so I ended up directly working with the cities.

So a lot of our research was done in the city of Cambridge, city of Boston.

Mariana and I had the opportunity to also travel abroad.

We collected sewage in the Middle East, in Kuwait.

We collected sewage in Asia, in South Korea, sending it all back to Cambridge.

And so through that experience, I also really developed a really strong interest in working directly with government agencies to get this work off the ground.

And so, Guy, I'll just paint the picture for you.

So in all of the early work we did at MIT, Mariana and I, and oftentimes other researchers as well, We were the ones physically collecting the samples.

Aaron Powell You were going to the treatment centers, you were getting the wastewater facilities, you were getting jugs of sewage.

I mean, more than that, we were hovering over manholes in a city, pumping out sewage, and in the middle of the street pouring that sewage between different bottles and taking it back to the lab.

So quite literally getting our hands dirty.

All right, so you get this grant to start gathering samples from sewers and then to to test it.

And what were you looking for in particular?

Was there anything in particular you were looking for, Mariana?

So when we started, the very first thing that we wanted to look for was the flu.

Marc Thiessen And you can detect that through, literally through sewage?

Would it be possible to track the influenza season and see not only the level of disease happening in the city, but also the types of strains that are circulating?

And how is the vaccine matching with what we're seeing in real time from people?

We actually, in our very first experiment, when I was very early in my PhD, we miserably failed running that six-month experiment.

So there was a moment there where I could have sort of like stopped working on it and said this doesn't work.

But instead I decided to dig into it and to try to understand, okay, why didn't it work?

Was it a problem of our methods, of which sites we selected to get wastewater from?

Because we couldn't collect some of the samples during wintertime when there's like snow on the ground.

And see the time of the day that we are getting the sample out.

We already know that flu was tough, but there are so many other biomarkers, potential biomarkers in the wastewater, what can we see?

Or will we be able to extract epidemiologic data that is reflective of what's happening in people?

As she said, 1 of the questions was, what is the best time of day to sample?

So we decided, let's take a sample every hour, over 24 hours, and look at that data and see when is the best time of data sample.

So we had shifts of people out on the street.

So these are researchers, master's students, PhD students at MIT, transporting sewage over the course of 24 hours from the street to the lab and filtering that that wastewater.

We had to train over 30 people to pull it off.

It was a massive effort and we succeeded.

Seems to be the peak poop time, at least for that neighborhood that we were looking at.

And we collected sequencing data to see what types of bacteria are present in the wastewater.

And if they are coming from people's poop, or if they are bacteria that live in the sewer.

And we also collected metabolite data, basically chemicals that we excrete in our pee that can be maybe medications or hormones.

We were able to see that most of the data in the wastewater was coming from people.

So initially, you were really trying to figure out if you could isolate all of these different bacteria and you could categorize them and determine a variety of things, what medications people were using, whether people had influenza.

And you, it sounds like this experiment proved that out, that you could actually do that.

You could actually find out a bunch of things, you know, diseases, medications people are taking, you know, infections, viruses, whatever it was, you could find this out by just collecting the amalgamation of everyone's poo and pee.

Absolutely, and that this was a very data-rich source.

And I think that when I saw that data, for me being a scientist, That's what to this day gave me the conviction that there was something really interesting and important here.

When we come back, how Mariana and Nusha are able to use wastewater to understand the health of cities.

You're listening to How I Built This Lab.

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I'm Guy Raz and I'm speaking with Mariana Matus and Nusha Ghaeli who are developing the science of wastewater epidemiology with their company BioBot Analytics.

All right, So now you've proved this out.

The 2 of you eventually decide together to launch a company, to do this commercially.

I was surprised to learn you're the first company to actually do this commercially.

There were no companies gathering this data and analyzing it, you know, and making it available to business or government, whoever.

When we started BioBot, we were the first company in the world to bring wastewater intelligence to market.

And it was precisely for that reason, I mean, Mariana and I both really had the conviction that this information needed to exist and would exist 1 day, sort of regardless of our efforts.

It was just too rich of a source of information.

And rather than, you know, continue as a research group, we wanted to actually start a company to be able to respond to what our communities wanted and be able to generate the data that our community leaders, our public health leaders actually wanted in order to help them improve public health infrastructure, public safety infrastructure in our cities and actually benefit our communities.

So tell me, let's start with what you can do right now with the technology that you're developing.

What can you measure from wastewater, from basically every time we flush the toilet and you gather that sample, what can you measure right now?

1 of the most important applications of the platform right now is to look at infectious diseases that are circulating in a community, starting with the analysis of wastewater for COVID-19 levels, COVID-19 variants.

We sequence the wastewater and we know which variants, which mutations are circulating in a community as well.

We're doing analysis for monkeypox as well, like an outbreak that surprised everybody.

You know, now with the benefit of having done this work for many years, It was actually 1 of the toughest applications to build on the platform.

Influenza is more sensitive to degradation in the wastewater.

It is possible to look at influenza, RSV, other respiratory viruses, to look at gastrointestinal diseases like norovirus, to look at sexually transmitted diseases like gonorrhea or chlamydia, to look at blood-borne pathogens like hepatitis C.

Based on our research to date and that of other groups, we actually end up excreting most of the infectious diseases that infect our bodies.

Right now, what can't you measure with the technology?

Right now, we cannot measure more complex population characteristics like obesity or cancer rates or diabetes rates.

We're only measuring things where there's a direct one-to-one kind of biomarker and something that we want to report on.

But I absolutely see the future where we will have enough data to start to learn kind of predictive components of data to then be able to look at those other more chronic diseases and ultimately of course be able to flag a new threat before anybody else knows about it.

So essentially I mean it seems so clear that you could get all this data from wastewater, I mean, especially as you're talking about it, but it's relatively new that this has been happening.

And a lot of us heard about this during COVID.

You know, you'd hear about wastewater gathered and they could measure COVID rates, which was remarkable.

You could see COVID rates sort of spiking in wastewater before the hospitalization spiked.

It was like a few days, kind of gives you a few days warning of what was about to happen.

lot of the behavioral sort of differences of the wastewater data compared to clinical data or hospitalization data has to do with, you know, a point we made earlier in the conversation that this is a behavior that we're engaging in every single day.

Whether you're symptomatic or asymptomatic, you're using the bathroom.

And so that data is getting flushed down the toilet.

And you are being counted in that wastewater data as early as day 1 or 2 or 3 of your infection.

Now, if you choose to now go get tested, get a PCR test, which, you know, at this point in the pandemic, not many people are even doing that, but should you choose to get a PCR test to be counted in the official clinical numbers, you're probably not doing that until day 4 or 5 or 6 of your infection when your symptoms are getting worse.

And so what that looks like in the data is a week-long, sometimes two-week-long sort of head start that the wastewater data has on our clinical data.

Aaron Powell Because the wastewater data is going to show that you've got COVID like days before you might even know yourself.

The 2 of you launched this company, BioBot, and you had to raise money.

You've got to have labs, you've got to have lab technicians.

Was it challenging to raise money for this?

I mean, given that this is such a new technology?

Or were there lots of people really interested in supporting this?

What we've seen is a lot of intellectual curiosity about the company and the potential here.

But indeed, It's been a challenge for many investors to wrap their heads around these new type of business model and a startup that is proposing to work with government as a target customer as the core customer from day 1.

So now you've got this company, BioBot, and I think you have about 100 employees.

And help me understand the business model, right?

I mean, obviously, your product is data, right, on pathogens and disease and viruses, etc.

But who are your customers, like hospitals, government agencies, businesses?

Yeah, so our customers are primarily government agencies.

So those are agencies at the local, so municipal, county, state, and federal level.

Our largest customer right now is the CDC.

And so we work with all levels of government.

And when we work with government, We typically work with public health departments, but also elected officials sometimes.

Sometimes in a community, it might be the mayor's office that's driving the data collection from wastewater.

And essentially for these communities, they see the value in not just the COVID data, but rather in wastewater intelligence as a platform.

So that's really how we position the technology is that right now the data that they might need is the COVID data and the variant data.

But this is actually a platform and a long-term shift in how communities should think about their sewer infrastructure.

You know, we see this as being a permanent layer in the urban fabric.

And then we have multiple stakeholders interested in the data.

So we could be working with a city who is only interested in looking at their own data, but then we work with a state that is, you know, monitoring dozens of communities within their state.

And then through our work with the CDC, we're working in over 400 communities across the country.

How would you see private industry maybe leveraging this data?

I mean, Is there an opportunity, a market opportunity there?

Or do you think that ultimately this is really only going to be used by government agencies?

Shannon Salvey, Chief Investment Officer, CNN

So we do work with some enterprise clients as well.

So these are namely office buildings or campuses that are so large that they somewhat operate like a small city or a mini city.

So the types of buildings we monitor can range from large office campuses or parks in Texas or California all the way to skyscrapers in Manhattan.

And they can monitor the sewage coming out of that building or group of buildings and use that information to help them better understand and stay on top of the spread of, you know, in this case, it's mostly COVID, within that community.

It's a much cheaper alternative to clinically testing employee bases.

There are a number of companies that still do that.

So, you know, thinking about how you can leverage wastewater to help guide these other interventions.

And then we also work with university campuses, so a similar value proposition there, and prison systems to help guide, you know, when there might be silent outbreaks in the community and guide when they should deploy clinical tests to identify some of these silent outbreaks.

Give me a sense of how the data can be applied and used to maybe prevent something bad from happening or to throw resources to a certain crisis or challenge.

I mean, let's use opioids, for example, because I know that's something that you can track in wastewater.

You can track how, you know, how intense the problem is in a community, how many people, roughly the percentage of the population using it.

What can you find out about opioids actually from wastewater?

Yeah, with opioids, that's a very valuable proposition for our government customers, because right now, the best data they have to understand the opioid crisis in their community is to look at overdose deaths.

And that's tough, not only because that data is heavily delayed, but also because it only represents a very, very tiny portion of the people who are suffering from substance use disorder.

So that data keeps making them look back rather than be able to respond to the people who are alive and can get help now.

So a very big value proposition of our data is that it reflects consumption from people who are alive, who can get help.

And more importantly, it also gives them intelligence on what are the type of substances that are driving consumption.

Is it street or illicit opioids that are getting consumed in their city or town?

And that necessitates a different intervention.

So just to give you an example, our very first customer for this work was the town of Cary, North Carolina.

And by working with Biobot, they were able to understand that, number 1, opioid use was happening everywhere in their town.

It's already helping them understand that this is widespread everywhere.

And also, second, they were able to see that it was mostly about prescription opioids rather than heroin or other illicit opioids in their town.

So they were able to design an educational campaign and to bring to their town safe disposal boxes for people to get rid of any excess prescription opiates they may have at home.

The message was embraced by the community and they saw a 40% decrease in overdoses, which was also the first ever decrease they'd seen in overdoses in their town in almost a decade.

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HIBT Lab! Biobot Analytics: Mariana Matus and Newsha Ghaeli