The objective of Project 4 is to develop a translational in vitro-to-in vivo testing strategy for evaluating inter-tissue and inter-individual variability in responses to complex environmental exposures. In the past, we developed a “biological read-across” approach based on the assays in human induced pluripotent stem cells. These studies showed how new approach methodologies (NAMs) can be applied for assessment of risks from real-life exposures. In continuation of this work, our hypothesis remains that a tiered risk-based strategy for safety evaluation using human organotypic in vitro cultures, combined with population-based reverse toxicokinetics, can be used to characterize the risks posed by combined exposures to chemicals during environmental emergencies. Project 4 responds to Superfund mandates (1) advanced techniques for the detection, assessment, and evaluation of the effect of hazardous substances; and (2) methods to assess the risks to health from hazardous substances.
Project 4 will determine what cell-based human model systems best predict potential toxicity, including the extent of inter-individual and inter-tissue variability, in people who may be exposed to hazardous substances as a result of a disaster. We will also create a framework for testing mixtures of chemicals for toxicity in these cell-based systems and for how best to understand at what dose these mixtures may be harmful. The outcome of this project will be a set of experimental tools and computational models that can be used rapidly during/after natural or man-made disasters.
- Develop a population-based human in vitro approach to characterize inter-tissue and inter-individual variability in response to complex environmental exposures.
- Develop a high-throughput reverse toxicokinetics (RTK) modeling approach for complex exposure to enable in vitro-to-in vivo extrapolation (IVIVE) of environmental samples.
- Disaster Research Response (DR2) – Demonstrate the application of human multi-tissue and population-wide high-throughput in vitro models to DR2.