Chemical Safety for Sustainability

Advancing Chemical Testing by the Thousands

Reposted from EPA Connect, the official blog of EPA leadership.

By Bob Kavlock

Bob Kavlock PortraitStudying thousands of chemicals at a time with the use of high-tech computer screening models and automated, often robot-assisted processes sounds like science fiction. But it’s not. EPA scientists are doing just that, leading the advancement of “high-throughput screening,” fast, efficient processes used to expose hundreds of living cells or isolated proteins to chemicals and then screen them for changes in biological activity—clues to potential adverse health effects related to chemical exposure.

This scientific advance is positioned to transform how we understand the safety of chemicals going forward. Twenty years ago, using high-throughput screening to test chemicals for potential human health risks seemed like technology that belonged in a science fiction television series rather than in real life.

Back then there were several large data gaps that would not allow us to extrapolate from the isolated biological changes we observe on a cellular level to adverse human health effects. However, through our computational toxicology (CompTox) research, which integrates, biology,

Robotic arm moving samples for screening

Robotic arm moves samples for automated chemical screening.

biotechnology, chemistry, and computer science, that is changing. We are helping to transform the paradigm of chemical testing from one that relies almost solely on expensive and time-consuming animal testing methods to one that uses the full power of modern molecular biology and robotics.

A significant part of this effort is the Toxicity Forecaster (ToxCast), launched in 2007. ToxCast allows us to prioritize potentially toxic chemicals for more extensive testing as well as giving us the opportunity to test newer, possibly safer alternatives to existing chemicals. By 2013, we evaluated more than 2,000 chemicals from industrial and consumer products to food additives using more than 500 high-throughput screening assays.

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Editor's Note: The opinions expressed here are those of the author. They do not reflect EPA policy, endorsement, or action.

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MCnest: Fly Away Home

Flying geese in a "V" formation against a sunset. By Thomas Landreth 

While recent winter weather storms may suggest otherwise, we are getting closer to the time that birds in this hemisphere begin their journey northward. Just like in the 1996 movie, Fly Away Home, last year’s crop of fledglings will begin their first return journey toward mating and nesting grounds.

However, a host of different variables can affect the success of these new populations year after year. Fly Away Home highlights how habitat loss might threaten migrating geese. But what about other, perhaps less obvious factors, such as those affecting bird breeding cycles?

EPA researchers have been working on a digital, easy-to-use model called the Markov Chain Nest Productivity Model, or MCnest, that estimates the impact of pesticide exposures on the reproductive success of bird populations.

MCnest combines existing avian (bird) toxicity test results, species life history information, and the timing of pesticide application(s) with breeding seasons to quantitatively estimate the potential impact of pesticide exposure on annual bird reproductive success.

McNest developer Matthew Etterson said, “This model is an important first step in moving avian pesticide risk assessment forward.”

Future MCnest results that indicate potential adverse affects on avian reproduction may be cited in Agency orders to regulate pesticide use under the Federal Insecticide Fungicide and Rodenticide Act (FIFRA), and in support of the Endangered Species Act (ESA). The ESA is administered by the U.S. Fish and Wildlife Service and the National Marine Fisheries Service, and requires federal agencies to ensure that any action they authorize won’t jeopardize listed threatened or endangered species.

Though MCnest is still in its early stages of development, work continues on a more advanced version that will improve exposure estimates and more realistically describe the length of avian breeding seasons.  The researchers are also applying the concepts behind MCnest to develop a model for fish, and a similar model is possible for mammals.

As its capability grows to take in data about more species, MCnest can play a greater role in EPA’s approach to ecological risk assessment. In time, MCnest may provide a greater understanding of pesticides and their impact on wildlife and our environment.

Click here for more information on MCnest, data libraries and program instructions.

About the author: Thomas Landreth is a student services contractor working with EPA’s Office of Research and Development.

Editor’s note: for more information on McNest and other EPA ecosystems-related research, please see the latest edition of our newsletter, “Science Matters.”

Editor's Note: The opinions expressed here are those of the author. They do not reflect EPA policy, endorsement, or action.

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Taking a Page from Nature’s Playbook: Innovation for Human Health

By Dustin Renwick

Illustration of lungsProtecting human health through chemical safety remains a priority for EPA, but it’s difficult and expensive to test all the 83,000 or so chemicals currently listed or registered for use.

That’s where innovation comes in. With new tools and models, EPA researchers aim to dramatically increase the pace of research and screening methods to provide the best information on how chemicals might affect us wherever we encounter them.

Researchers need to understand how chemicals affect the human body. One method of testing toxic effects of aerosols (chemicals and other pollutants in the air) uses human cells submerged in liquid at the bottom of a well plate. That means scientists have to capture pollutants and pipette them into the liquid medium to reach the cells for testing.

But human breathing takes place in a more dynamic environment. Our respiratory system operates with only a thin liquid layer of mucus separating lung cells from air.

Amy Wang, an EPA biologist, and her Pathfinder Innovation Project (PIP) team invented a system that mimics how our airway cells come in contact with air pollutants.

The system, which has progressed through several prototypes, can generate and control aerosols in multiple wells in one plate at the same time.

“The great advantage of this system is you expose the cells to aerosols in a way similar to the complex conditions in the human lungs,” Wang said.

The team’s invention has the potential to allow researchers to test multiple compounds in airborne mixtures, a scenario that more closely represents how people come in contact with chemicals outside a laboratory setting.

“We could take combustion emissions from an engine and expose cells directly at concentrations we choose,” Wang said. “The integrity of that emission would be maintained – all the vapors, all the gases, all the aerosols produced.”

Wang said the system helps eliminate variables that can sometimes hinder traditional testing that uses cells under a column of liquid. Additionally, the new system will allow scientists to run tests more rapidly.

Next-generation systems like the one Wang and her team created can produce enormous amounts of data. Any research EPA conducts depends on high-quality data, and EPA has released lots of it as part of an initiative called ToxCast.

You can use the interactive Chemical Safety for Sustainability Dashboards to view toxicity data for 1,800 chemicals.

And as part of the ToxCast project, we’ve launched a series of data challenges. If you want to help find new ways to use EPA data, check out the descriptions and sign up to submit your ideas. The current challenge is open until January 19, and we need ideas to help create a strategic framework for using EPA data.


About the author: Dustin Renwick works as part of the innovation team in the EPA Office of Research and Development.


Editor's Note: The opinions expressed here are those of the author. They do not reflect EPA policy, endorsement, or action.

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Release the Data! New Chemical Data, Workshops, and Challenges

By Matthew T. Martin

Scientist prepares a well-plate for high-throughput screening.

Scientist preparing a well-plate for high-throughput screening.

Ever open that cabinet under the kitchen sink, grab that bright blue bottle of window cleaner and wonder exactly what sort of chemicals are floating around in it? Many of you have at one time or another, and for those of you who have never given it a second thought rest assured that my colleagues and I at EPA are dedicated to identifying and categorizing all of the chemicals we might be exposed to on any given day. However, due the expensive, time-consuming process of traditional testing, which assesses one chemical at a time, only a small fraction of the tens of thousands of chemicals currently in commerce have been adequately assessed for potential human and environmental health risks.

To close this data gap and better evaluate potential health risks, we have worked hard in recent years to accelerate the pace of chemical testing. I am proud to say that we have now completed phase two of the multi-year Toxicity Forecaster (ToxCast) project and are publically releasing ToxCast data on 1,800 chemicals evaluated in over 700 high-throughput screening assays. This is a significant accomplishment that we want to share with the scientific community.

The new data is accessible through the new interactive Chemical Safety for Sustainability (iCSS) Dashboard, a web-based application for users to access and interact with the data freely at their own discretion. Users can select the chemicals and data of interest and then score the information to help inform chemical safety decisions.

As part of the data release, I hope the scientific community will take advantage of this new windfall of data and become involved in the ToxCast project by participating in the Predictive Toxicology Challenges. The first two challenges of the series, available through TopCoder and InnoCentive crowd sourcing technology, will ask the scientific and technology community to develop new algorithms to predict lowest effect levels (LELs) of chemicals using the new ToxCast data. Winners will receive monetary prizes to help fund their own planned research, and their solutions will help us determine innovative ways to use ToxCast data to inform decisions made about the chemical safety.

Also, beginning January 14,we are also hosting several stakeholder outreach workshops and webinars to address potential challenges with data translation, accessibility, and any other troubleshooting issues that might arise during the initial data launch. This is an opportunity for the scientific community to provide input on data usage and offer immediate feedback about the new data and the iCSS dashboard.

About the author: Matthew T. Martin is a research biologist within EPA’s National Center for Computational Toxicology, where he is part of the ToxCast team and leads the CSS task for developing predictive models of toxicity using high-throughput screening data. He also serves as the project lead for developing the new CSS Dashboard Web Application.

Editor's Note: The opinions expressed here are those of the author. They do not reflect EPA policy, endorsement, or action.

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