1. Development of a High-Throughput Assay to Identify 5-α Reductase Inhibitors for Orthogonal Evaluation in an Androgen-Dependent Human 3D Prostate Microtissue

Leads: Chad Deisenroth, Josh Harrill, Menghang Xia

Goal: Develop additional human-based, cellular test systems to more completely model androgen pathway activity.

• Issue: Environmental factors that alter the metabolism or bioactivity of androgen, a male sex hormone, can harm human reproductive and sexual development. Current guidelines rely on animal testing to evaluate the potential for certain chemicals to disrupt normal androgenic functions. Efforts to evaluate androgen-active chemicals using predictive computational models with in vitro data are limited; unlike animal models, computational models have insufficient coverage of key metabolic outcomes and observable characteristics resulting from gene-environment interactions.
• Project Focus: Develop a high-throughput assay to evaluate the effects of blocking the activity of enzyme 5α-reductase and develop a 3-D human prostate microtissue assay that may enable better assessments of androgen-active chemicals. Together, the assays can provide greater depth for predicting the negative effects of androgen-disrupting compounds.  

2. Cell Line Selection for High-Throughput Transcriptomics (HTT)

Leads: Nisha Sipes, Josh Harrill, Woody Setzer 

Goal: Develop a strategy for selecting maximally diverse cell types/lines to maximally cover biological targets and pathways for high-throughput chemical screening using gene expression (i.e., transcriptomics). 

• Issue: HTT is an efficient means of screening chemicals for bioactivity across a broad range of potential molecular targets. However, no single laboratory (in vitro) model will  express all molecular targets or accurately model the diversity of chemical disturbances observed in different cell types of the human body. As in vitro models derived from diverse tissues and sources have different gene/protein expression patterns, they may respond differently to chemical exposures. A HTT screening panel using diverse cell lines would provide a more comprehensive understanding of chemical bioactivity than studies in any single cell type.
• Project Focus: Use computational modeling of existing transcriptomics data to select a set of "diverse" cell lines, measure transcriptomic responses of "diverse" cells following exposure to a panel of chemicals, determine the degree to which "diverse" cell lines respond differently to chemicals, and analyze the responses among pooled cell lysates.  

3. Profiling Environmental, Drug, and Food-Related Chemicals that Inhibit Acetylcholinesterase Activity

Leads: Menghang Xia, Michael Santillo

Goal: Develop a high-throughput in vitro test system to identify and characterize new compounds that block the activity of acetylcholinesterase. 

• Issue: Acetylcholinesterase (AchE) inhibitors are compounds related to foods, drugs, and the environment that can be toxic to humans.
• Project Focus: To advance existing methods, metabolism will be incorporated into the in vitro screening system, which, in addition to in-depth mechanistic studies, may improve the ability to detect emerging chemical hazards.

4. In Vitro Chemical Disposition

Leads: Katie Paul Friedman, Mike Devito

Goal: Understand the impact of chemical disposition within in vitro test systems across a broad range of chemical categories and develop a computational model to predict differences between the "nominal" concentration of a chemical compared with "true" concentration in the media and cells.

• Issue: In a cell-based laboratory test (in vitro assay), the actual concentration of a chemical inside cells is likely different from the nominal concentration applied to the medium in the well of a microtiter assay plate. Mathematical models exist for predicting in vitro disposition, but very few chemicals have been evaluated for in vitro disposition. Across the Tox21 chemical library, chemical partitioning could affect the accuracy of predictions made from laboratory (in vitro) data about living (in vivo) systems, but the number of chemicals affected and to what degree are unknown. 
• Project Focus: This cross-partner project includes measurement of in vitro disposition of approximately 200 chemicals, with the goal of developing model predictions for the rest of the Tox21 chemical library.​

5. High-Throughput Transcriptomic Analysis

Leads: Steve Ferguson, Josh Harrill, Menghang Xia

Goal: Develop a common chemical reference dataset for interpretation of high-throughput transcriptomic screening data.

• Issue: Gene expression profiling has proven to be an invaluable tool to explore mechanisms of chemical interactions with biological systems (e.g., pharmacology, toxicology). However, these tools have historically lacked sufficient throughput to study a broad range of chemicals, or characterize concentration-response profiles necessary to identify perturbed biological-response pathways.
• Project Focus: Build a robust transcriptomic data set with hundreds of chemicals (largely data-rich reference chemicals with established linkages to biological response-pathways). Transcriptomic signatures are being developed to identify molecular targets and pathways which are perturbed by chemical treatment, as well as the progression of target and pathway perturbations as a function of chemical concentration.

6. Predictive Modeling of Developmental Toxicity with Human Pluripotent Stem Cells

Leads: Thomas Knudsen, Nicole Kleinstreuer, Annie Lumen

Goal: Evaluate a human-based, induced pluripotent stem cell (iPSC) test system to predict developmental toxicity.

• Issue: Traditionally, information from studies using laboratory animals has been used to predict the impact of chemical exposure on the human fetus. However, these studies are slow, costly and unrealistic for assessing tens of thousands of environmental chemicals in commerce, and this approach may not provide adequate coverage of human biology.
• Project Focus: Evaluate an assay (test) based on reducing cellular ornithine's release relative to cystine uptake by iPSCs. Coupled with computational predictive modeling, the in vitro test system findings can be extrapolated to living systems (in vivo) and dose-activity measures translated to the whole-body level. This approach enables exposure-based risk characterization for chemicals considered high priority for developmental toxicity. This cross-program project will work towards the characterization, validation, and implementation of this platform by modeling the predictive and health-protective potential of the assay with regards to fundamental principles of abnormal development in the womb. 

7. Toxicodynamic Variability in Developmental Neurotoxicity

Leads: Mamta Behl, Alison Harrill

Goal: Incorporate genetic variation into cell-based test systems to better understand potential population differences in response to chemicals that may cause toxic neurological effects.

• Issue: Genetic differences between people can have a profound effect on whether an individual is susceptible to negative health outcomes caused by a given chemical.
• Project Focus: Use neural progenitor cells derived from a highly diverse rodent population, called the Diversity Outbred, to determine variability in toxicity outcomes after exposure to known or suspected neurotoxic chemicals. The data collected has the potential to inform human health risk assessments for chemical exposures, replacing default inter-individual uncertainty factors.

8. Performance Based Validation of Alternative Test Systems and Models

Leads: Keith Houck, Richard Judson, Nicole Kleinstreuer

Goal: Develop an evaluation framework for the development of performance standards which can be used to establish confidence in alternative test systems and models.

• Issue: Validation is needed to increase the usefulness of ToxCast and Tox21 high-throughput screening (HTS) data in regulatory applications.
• Project Focus: Develop curated sets of active and inactive reference chemicals as well as known assay interference chemicals. In addition to developing a process for identifying reference chemicals, defining a process for describing the essential test method components, evaluating the assay data for accuracy and reliability, and declaring the assay “validated” is necessary. Finally, both the development of reference chemical sets and a validation process must be streamlined and fast enough to manage the tens to hundreds of assays that can help inform regulatory decisions.