Application of the Key Characteristics of Carcinogens to Bisphenol A.

The ten key characteristics (KCs) of carcinogens are based on characteristics of known human carcinogens and encompass many types of endpoints. We propose that an objective review of the large amount of cancer mechanistic evidence for the chemical bisphenol A (BPA) can be achieved through use of these KCs. A search on metabolic and mechanistic data relevant to the carcinogenicity of BPA was conducted and web-based software tools were used to screen and organize the results.

Research Recommendations for Selected IARC-Classified Agents: Impact and Lessons Learned.

Background: The International Agency for Research on Cancer (IARC) Monographs program assembles expert working groups who publish a critical review and evaluation of data on agents of interest. These comprehensive reviews provide a unique opportunity to identify research needs to address classification uncertainties. A multidisciplinary expert review and workshop held in 2009 identified research gaps and needs for 20 priority occupational chemicals, metals, dusts, and physical agents, with the goal of stimulating advances in epidemiological studies of cancer and carcinogen mechanisms.

Conducting evaluations of evidence that are transparent, timely and can lead to health-protective actions.

Background: In February 2021, over one hundred scientists and policy experts participated in a web-based Workshop to discuss the ways that divergent evaluations of evidence and scientific uncertainties are used to delay timely protection of human health and the environment from exposures to hazardous agents. The Workshop arose from a previous workshop organized by the European Environment Agency (EEA) in 2008 and which also drew on case studies from the EEA reports on 'Late Lessons from Early Warnings' (2001, 2013). These reports documented dozens of hazardous agents including many chemicals, for which risk reduction measures were delayed for decades after scientists and others had issued early and later warnings about the harm likely to be caused by those agents.

Modeling the transplacental transfer of small molecules using machine learning: a case study on per- and polyfluorinated substances (PFAS).

Background: Despite their large numbers and widespread use, very little is known about the extent to which per- and polyfluoroalkyl substances (PFAS) can cross the placenta and expose the developing fetus.

Objective: The aim of our study is to develop a computational approach that can be used to evaluate the of extend to which small molecules, and in particular PFAS, can cross to cross the placenta and partition to cord blood.

Methods: We collected experimental values of the concentration ratio between cord and maternal blood (R) for 260 chemical compounds and calculated their physicochemical descriptors using the cheminformatics package Mordred.