Computational Toxicology Workshop
Learn how to apply computational methods to predict human health risks from toxic chemical exposure.
Modules/Weeks
Weekly Effort
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Course Description
Computational approaches are becoming essential for understanding how chemical exposures impact human health. Traditional toxicology methods cannot keep pace with the growing number of chemicals requiring evaluation, creating an urgent need for scalable, data-driven solutions.
The Computational Toxicology Workshop is an intensive, hands-on training designed to introduce participants to modern computational methods for assessing chemical toxicity and human health risk. Drawing on high-throughput in vitro and in vivo data, the course explores how predictive models and integrated datasets can be used to evaluate chemicals not fully tested by conventional approaches.
Over two days, participants will work directly with publicly available datasets, learn how to manipulate and visualize complex data, and begin conducting their own analyses. The training emphasizes practical application, helping you move from understanding key concepts to generating meaningful insights.
In this training, you will:
- Learn how to apply computational methods to predict human health risks from chemical exposure
- Work with high-throughput toxicology data from publicly available sources
- Use tools such as the EPA CompTox dashboard and ToxPi framework
- Build skills in data visualization, curve fitting, and multidimensional analysis
- Explore approaches for integrating multiple datasets to assess exposure and risk
- Apply statistical techniques to analyze chemical mixtures and health outcomes
This course is ideal for:
- Graduate students and PhD candidates in public health, toxicology, or related fields
- Early-career researchers and investigators seeking practical computational skills
- Public health professionals and scientists working with environmental exposure data
- Academic researchers interested in predictive toxicology and data-driven methods
- Anyone looking for a foundational, applied introduction to computational toxicology
Whether you are new to computational toxicology or looking to strengthen your analytical capabilities, this workshop provides a practical foundation for working with complex data and advancing research in environmental health.
Course Prerequisites
There are no formal prerequisites for this course. A basic familiarity with toxicology, public health, or data analysis concepts is helpful but not required.
Participants must bring a personal laptop. Setting up a basic RStudio Cloud account in advance is recommended to support hands-on exercises during the training.
Prior to the workshop, participants will receive introductory materials and a short set of preparatory exercises to help familiarize themselves with key concepts and tools.
What You Will Learn
This workshop is designed to equip you with practical skills in computational toxicology, enabling you to analyze complex datasets and assess human health risks from chemical exposure. Through hands-on exercises and real-world tools, you will develop the ability to work with high-throughput toxicology data, apply predictive approaches, and generate meaningful insights that support research and decision-making in environmental health.
By the end of the workshop, participants will be familiar with the following topics:
- How best to curve fit and display cytotoxicity data
- How to create highly dimensional and informative data visualizations
- The EPA’s CompTox dashboard and database
- ToxPi: the Toxicological Prioritization Index (ToxPi) framework
- How to interpolate and extrapolate human exposure risk across multiple data sources and techniques
- How to find and choose relevant databases and repositories of high-throughput toxicological data and navigate their interfaces
- Statistical techniques to analyze chemical mixtures and their relationships to health outcomes
Instructors
Dr. Norman J. Kleiman is an expert in environmental health, radiation research, and ocular biology, with a focus on how environmental exposures impact human health. His work examines the effects of radiation, heavy metals, and other toxic agents on biological systems, including DNA damage, mutagenesis, and disease risk. He has led and contributed to major research initiatives funded by organizations such as NASA, the Department of Energy, and the National Institute of Environmental Health Sciences. Dr. Kleiman also serves as a technical cooperation expert for the International Atomic Energy Agency and contributes to scientific committees for leading international radiation protection organizations. His research supports the development of risk assessment frameworks and public health guidelines for environmental exposures.
Dr. Brandon L. Pearson is a researcher focused on understanding how environmental exposures influence human health, particularly in relation to brain development and aging. His work investigates gene-environment interactions, including how environmental stressors affect gene expression, mutagenesis, and neurological function. Dr. Pearson has held academic and research positions at Columbia University and leading international institutions, and his work spans molecular biology, toxicology, and public health. He is an active contributor to the scientific community, serving as a reviewer for major funding agencies and participating in research initiatives related to environmental health and disease.