Jui-Hua Hsieh, Ph.D., is a Staff Scientist in the Predictive Toxicology Branch of the Division of Translational Toxicology (DTT). Her primary roles involve method development and applications on concentration-response data, web application development for data visualization, and model development for prioritizing and predicting potential human toxicants. Prior to joining the DTT in 2011, she received her B.S. degree in Pharmacy from National Taiwan University and her Ph.D. degree in Pharmaceutical Sciences from University of North Carolina at Chapel Hill. Her Ph.D. work involves the development and application of cheminformatics tools for drug discovery projects, particularly hit identification in virtual screening.
NIEHS DIVER Platforms: Integrating and Visualizing Data from In Vitro Developmental Neurotoxicity (DNT) and Zebrafish Developmental Toxicity (DT) Screening Programs
Jui-Hua Hsieh1, Skylar Marvel1, Zicong Wang1, Sue Nolte2, Christopher McPherson1, Kristen Ryan1
1Divistion of Translational Toxicology, National Institute of Environmental Health Sciences, RTP, NC, USA
2Office of Data Science, National Institute of Environmental Health Sciences, RTP, NC, USA
Abstract:
The National Institute of Environmental Health Sciences (NIEHS) is committed to advancing toxicology through innovative tools and strategies. This presentation highlights two key NIEHS programs—the Developmental Neurotoxicity-Health Effects Innovation (DNT-HEI) and the Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT)—to showcase our use of New Approach Methods (NAMs) in generating screening-level data on substances for developmental toxicity and neurotoxicity. The DNT-HEI program leverages NAMs to assess hazards and prioritize substances with unknown DNT potential for further in-depth evaluation. This program includes a pilot phase followed by three additional phases, aiming to target over 400 substances, including defined compounds, complex mixtures (such as botanicals), and designed mixtures. In parallel, the SEAZIT program has conducted interlaboratory zebrafish DT screening on a standardized set of 41 substances under four different test conditions. This research seeks to understand how varying conditions influence toxicity outcomes, such as phenotypic changes. Both programs have generated substantial and growing datasets on toxicity. To ensure transparent and effective communication of these findings, we developed the Data Integration and Visualization Enabling Resource (DIVER) platforms: DNT-DIVER and SEAZIT-DIVER. This presentation will cover the data generation process, database development, visualization capabilities in DIVER, and chemical prioritization based on benchmark concentration (BMC). Both DIVER platforms are publicly accessible: DNT-DIVER 2.0 Beta (https://www.niehs.nih.gov/research/atniehs/dtt/tools/dnt-diver) and SEAZIT-DIVER (https://manticore.niehs.nih.gov/seazit).
