A Revised Read-across Framework and its Application for the Development of EPA’s Provisional Peer Reviewed Toxicity Values (PPRTVs)
Background and Purpose: Human health assessment has traditionally relied on epidemiological studies and toxicity studies in laboratory animals to characterize adverse apical outcomes associated with chemical exposures. However, most chemicals currently in commerce or in the environment lack sufficient data for hazard identification and dose-response analysis. Read-across is a popular technique that can be used to estimate human health endpoints for a target chemical using information from a similar source analogue(s). Methods: Previously, we introduced a read-across framework for screening-level assessment of data-poor chemicals of interest to the U.S. EPA’s Provisional Peer Reviewed Toxicity Value (PPRTV) program (Wang et al., 2012). Herein, we showcase a revised framework informed by practical knowledge and technological advances in the fields of read-across and new approach methods (NAMs). Results: Key advancements include problem formulation to expand the scope and decision context of read-across applications; systematic review and target chemical profiling to identify relevant information on the target and inform the analogue identification and evaluation strategy; an expanded analogue identification approach based on chemical and biological similarities; considerations for analogue evaluation by weight-of-evidence (WoE); and integration of NAM data and tools to enhance expert judgement for identifying and evaluating analogues. Case studies are presented for data-poor chemicals evaluated under the PPRTV program to illustrate key learnings and ongoing challenges with the implementation of read-across for quantitative human health assessment. In general, our revised approach allows for the identification of a larger and more comprehensive pool of analogues. Data limitations pose a challenge for identifying analogues with existing toxicity values from relevant authoritative sources particularly on the basis of mechanistic/mode-of-action (MOA) considerations. Conclusion: This work demonstrates the application of the revised framework in advancing read-across efforts within the U.S. EPA to continue addressing data gaps for environmental chemicals with limited or no toxicity data. Future efforts will incorporate NAM-based approaches to further expand candidate analogue pools and to explore the use of mechanistic/MOA data for chemical grouping and read-across. The views expressed are those of the authors and do not necessarily reflect the views and policies of the US EPA.