Citation:

Harrill, J., I. Shah, R. Setzer, D. Haggard, S. Auerbach, R. Judson, AND R. Thomas. Considerations for Strategic Use of High-Throughput Transcriptomics Chemical Screening Data in Regulatory Decisions. Current Opinion in Toxicology. Elsevier BV, AMSTERDAM, Netherlands, 15:64-75, (2019). https://doi.org/10.1016/j.cotox.2019.05.004

Impact/Purpose:

Transcriptomic technologies have been used in toxicology, and other scientific fields, for many years. These technologies provide broad insight into the molecular signaling networks that are perturbed following chemical exposures and that underlie functional and pathological changes in tissues upon which traditional chemical risk assessments are based. To date, data from transcriptomics studies have not been routinely used in chemical risk assessment dossiers submitted to regulatory agencies outside of the pharmaceutical field. However, transcriptomics data has been used to a limited extent in risk assessment approaches employed by private industry to support internal decision-making processes. These approaches have primarily focused on hazard identification, specifically elucidation, establishment and categorization of mode(s)-of-action in the context of a product development pipeline. Recently, numerous organizations, including some with regulatory authority, have proposed the use of data from New Approach Methodologies (NAMs) to modernize and increase the pace of chemical safety assessments. NAMs are defined as any technology, methodology, approach or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. Therefore, HTTr assays performed in in vitro test systems can be considered NAMs. Also in recent years, a variety of research groups have explored how low-throughput in vitro and in vivo transcriptomics data as well as HTS data, respectively, may be used in the context of chemical risk assessment. The utility of transcriptomics for risk assessment has been evaluated in a number of areas. With respect to HTS and risk assessment, a general framework for in vitro-to-in vivo extrapolation (IVIVE) has emerged that involves concentration-response modeling of HTS data to identify biological pathway altering concentrations (BPAC), and conversion to administered dose equivalents (ADEs) using high-throughput toxicokinetic modeling (HTTK) modeling and reverse dosimetry. Here we will examine these concepts in greater detail and propose a framework where methodologies from the transcriptomics and HTS research fields are combined for analysis of HTTr data and potential application to chemical risk assessment.

Description:

Recently, numerous organizations, including governmental regulatory agencies in the U.S. and abroad, have proposed using data from New Approach Methodologies (NAMs) for augmenting and increasing the pace of chemical assessments. NAMs are broadly defined as any technology, methodology, approach or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. High-throughput transcriptomics (HTTr) is a type of NAM that uses gene expression profiling as an endpoint for rapidly evaluating the effects of large numbers of chemicals on in vitro cell culture systems. As compared to targeted high-throughput screening (HTS) approaches that measure the effect of chemical X on target Y, HTTr is a non-targeted approach that allows researchers to more broadly characterize the integrated response of an intact biological system to chemicals that may affect a specific biological target or many biological targets under a defined set of treatments conditions (time, concentration, etc.). HTTr screening performed in concentration-response mode can provide potency estimates for the concentrations of chemicals that produce perturbations in cellular response pathways. Here, we discuss study design considerations for HTTr concentration-response screening and present a framework for the use of HTTr-based biological pathway-altering concentrations (BPACs) in a screening-level, risk-based chemical prioritization approach. The framework involves concentration-response modeling of HTTr data, mapping gene level responses to biological pathways, determination of BPACs, in vitro-to-in vivo extrapolation (IVIVE) and comparison to human exposure predictions. The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.

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