The database makes the poison: How the selection of datasets in QSAR models impacts toxicant prediction of higher tier endpoints.

As the United States and the European Union continue their steady march towards the acceptance of new approach methodologies (NAMs), we need to ensure that the available tools are fit for purpose. Critics will be well-positioned to caution against NAMs acceptance and adoption if the tools turn out to be inadequate. In this paper, we focus on Quantitative Structure Activity-Relationship (QSAR) models and highlight how the training database affects quality and performance of these models. Our analysis goes to the point of asking, "are the endpoints extracted from the experimental studies in the database trustworthy, or are they false negatives/positives themselves?" We also discuss the impacts of chemistry on QSAR models, including issues with 2-D structure analyses when dealing with isomers, metabolism, and toxicokinetics. We close our analysis with a discussion of challenges associated with translational toxicology, specifically the lack of adverse outcome pathways/adverse outcome pathway networks (AOPs/AOPNs) for many higher tier endpoints. We recognize that it takes a collaborate effort to build better and higher quality QSAR models especially for higher tier toxicological endpoints. Hence, it is critical to bring toxicologists, statisticians, and machine learning specialists together to discuss and solve these challenges to get relevant predictions.

The physiological and biochemical basis of potency thresholds modeled using human estrogen receptor alpha: implications for identifying endocrine disruptors.

The endocrine system functions by interactions between ligands and receptors. Ligands exhibit potency for binding to and interacting with receptors. Potency is the product of affinity and efficacy. Potency and physiological concentration determine the ability of a ligand to produce physiological effects. The kinetic behavior of ligand-receptor interactions conforms to the laws of mass action. The laws of mass action define the relationship between the affinity of a ligand and the fraction of cognate receptors that it occupies at any physiological concentration. We previously identified the minimum ligand potency required to produce clinically observable estrogenic agonist effects via the human estrogen receptor-alpha (ERα). By examining data on botanical estrogens and dietary supplements, we demonstrated that ERα ligands with potency lower than one one-thousandth that of the primary endogenous hormone 17ß-estradiol (E2) do not produce clinically observable estrogenic effects. This allowed us to propose a Human-Relevant Potency Threshold (HRPT) for ERα ligands of 1 × 10-4 relative to E2. Here, we test the hypothesis that the HRPT for ERα arises from the receptor occupancy by the normal metabolic milieu of endogenous ERα ligands. The metabolic milieu comprises precursors to hormones, metabolites of hormones, and other normal products of metabolism. We have calculated fractional receptor occupancies for ERα ligands with potencies below and above the previously established HRPT when normal circulating levels of some endogenous ERα ligands and E2 were also present. Fractional receptor occupancy calculations showed that individual ERα ligands with potencies more than tenfold higher than the HRPT can compete for occupancy at ERα against individual components of the endogenous metabolic milieu and against mixtures of those components at concentrations found naturally in human blood. Ligands with potencies less than tenfold higher than the HRPT were unable to compete successfully for ERα. These results show that the HRPT for ERα agonism (10-4 relative to E2) proposed previously is quite conservative and should be considered strong evidence against the potential for disruption of the estrogenic pathway. For chemicals with potency 10-3 of E2, the potential for estrogenic endocrine disruption must be considered equivocal and subject to the presence of corroborative evidence. Most importantly, this work demonstrates that the endogenous metabolic milieu is responsible for the observed ERα agonist HRPT, that this HRPT applies also to ERα antagonists, and it provides a compelling mechanistic explanation for the HRPT that is grounded in basic principles of molecular kinetics using well characterized properties and concentrations of endogenous components of normal metabolism.

Range of the perfluorooctanoate (PFOA) safe dose for human health: An international collaboration.

Many government agencies and expert groups have estimated a dose-rate of perfluorooctanoate (PFOA) that would protect human health. Most of these evaluations are based on the same studies (whether of humans, laboratory animals, or both), and all note various uncertainties in our existing knowledge. Nonetheless, the values of these various, estimated, safe-doses vary widely, with some being more than 100,000 fold different. This sort of discrepancy invites scrutiny and explanation. Otherwise what is the lay public to make of this disparity? The Steering Committee of the Alliance for Risk Assessment (2022) called for scientists interested in attempting to understand and narrow these disparities. An advisory committee of nine scientists from four countries was selected from nominations received, and a subsequent invitation to scientists internationally led to the formation of three technical teams (for a total of 24 scientists from 8 countries). The teams reviewed relevant information and independently developed ranges for estimated PFOA safe doses. All three teams determined that the available epidemiologic information could not form a reliable basis for a PFOA safe dose-assessment in the absence of mechanistic data that are relevant for humans at serum concentrations seen in the general population. Based instead on dose-response data from five studies of PFOA-exposed laboratory animals, we estimated that PFOA dose-rates 10-70 ng/kg-day are protective of human health.