There is growing evidence that single substances present below their individual thresholds of effect may still contribute to combined effects. Here, the possible use of ecotoxicological threshold concentrations of no concern (i.e. 5th percentile of statistical distribution of ecotoxicological values) is investigated to fill data gaps in MRA.
Pluripotent stem cells offer the potential for an unlimited source for cell therapy products. However, there is concern regarding the tumorigenicity of these products in humans, mainly due to the possible unintended contamination of undifferentiated cells or transformed cells. Here, we critically review currently available in vivo and in vitro testing methods for tumorigenicity evaluation against expectations in international regulatory guidelines.
Robust genomic approaches are now available to realize improvements in efficiencies and translational relevance of cancer risk assessments for drugs and chemicals. The authors propose a path for implementation of innovative cancer risk assessment including incorporating genomic signatures to assess mechanistic relevance of carcinogenicity and enhanced use of genomics in benchmark dose and point of departure evaluations.
Voltage-sensitive optical (VSO) sensors offer a minimally invasive method to study the time course of repolarization of the cardiac action potential (AP). This Comprehensive in vitro Proarrhythmia Assay (CiPA) cross-platform study investigates protocol design and measurement variability of VSO sensors for preclinical cardiac electrophysiology assays.
Genotoxicity testing is an essential component of the safety assessment paradigm required by regulatory agencies world-wide for analysis of drug candidates, and environmental and industrial chemicals. Current genotoxicity testing batteries feature a high incidence of irrelevant positive findings – particularly for in vitro chromosomal damage (CD) assays. Thus, regulators are urgently in need of new testing approaches to meet legislated mandates. Using machine learning, we identified a set of transcripts that responds predictably to DNA-damage in human cells that we refer to as the TGx-DDI biomarker, which was originally referred to as TGx-28.65.