Historically, safety assessments of ingredients present in consumer products (e.g. cosmetics, food) have relied on apical endpoints derived from animal testing. However, ethical and regulatory considerations on excessive animal use, in addition to scientific need to use more human-relevant data, have led to emergence of next-generation risk assessment (NGRA). NGRA is an exposure-led and hypothesis-driven approach, wherein safety assessments are conducted in a tiered manner — using detailed information on levels of consumer exposure to the ingredient — together with appropriate new approach methodologies — including in silico, in chemico, and in cell culture approaches.
For exposures in which systemic toxicity is predicted to be significant, physiologically based kinetic (PBK) models can be used to simulate distribution of the substance throughout the body (i.e. bioavailability). Output from such models can be combined with high-throughput cell culture assays where toxicity biomarkers of concern, and concentrations at which they are perturbed (i.e. the point of departure [PoD]), are identified. Developing suitable high-throughput assays for different toxicity outcomes remain a major challenge within NGRA. In particular, studies have suggested that many substances are associated with nonspecific toxicity modes-of-action — leading to cellular stress or mitochondrial toxicity — which, in turn, are associated with various organ toxicities.
Perhaps the most comprehensive datasets (looking at general bioactivity of substances) are those from U.S. EPA Toxcast and U.S. federal cross agency Tox21 programs. Analysis of these datasets revealed that there is a disproportionate increase in positive assay responses at concentrations that coincide with cytotoxicity and cell stress. In that analysis, it was generally not possible, however, to distinguish between specific stress responses triggered by a chemical at sub-cytotoxic concentrations (which may have subsequently led to cytotoxicity at higher concentrations, or later time-points), and cell stress events that coincided with, and potentially occurred as a consequence of, cytotoxicity (referred to in this article as a “cytotoxic burst”). This dilemma limits the degree to which data could be used to develop a hypothesis on a potential mechanism-of-toxicity. As such, developing a suitable set of assays and analysis to unravel these events is an ongoing challenge in the field of NGRA.
The objective of this work [see attached article] was to develop and evaluate a cellular stress response panel that could form part of an early tier screen for identifying substances that could, at relevant exposure levels, be associated with adverse effects caused in humans. The panel consisted of biomarkers covering the key cellular stress pathways already identified, together with mitochondrial toxicity and various cell-health parameters. To evaluate the suitability of the panel for chemical risk assessment, authors generated data using two sets of benchmark chemicals. The first set included chemicals that, at defined human exposures, are known to cause adverse systemic effects due to cellular stress in a subset of exposed individuals.
The second set included chemicals that, at relevant human exposures, have not been associated with adverse systemic effects related to cellular stress. A key principle of NGRA is that the various sources of uncertainty (e.g. identifying positive biomarkers and estimating the associated PoDs) should be robustly characterized. To this end, a novel concentration-response model was developed. The authors’ approach used Bayesian statistics, which allowed for uncertainties in the model outputs (i.e. PoD estimates) to be quantified in a probabilistic manner. Using the stress panel — together with the statistical approach described herein — it was possible for the authors largely to distinguish between chemical exposures that are associated with adverse health outcomes and chemical exposures that pose a low risk for the consumer.
The cellular stress panel — comprising 36 biomarkers representing mitochondrial toxicity, cell stress, and cell health [see Table 1 of attached article] — were measured predominantly using high content imaging. To evaluate the panel, authors generated data for 13 substances at exposures consistent with typical use-case scenarios [see Table 2 of attached article]; these included some that have been shown to cause adverse effects in a proportion of exposed humans and that have a toxicological mode-of-action associated with cellular stress (e.g. doxorubicin, troglitazone, diclofenac), and some that are not associated with adverse effects due to cellular stress at human-relevant exposures (e.g. caffeine, niacinamide, phenoxyethanol).
For each substance, concentration response data were generated for each biomarker at 3 time-points (Figures 3 & 5). A Bayesian model was then developed to quantify evidence for a biological response, and if present, a credibility range for the estimated PoD was determined. PoDs were compared with the plasma Cmax levels associated with typical substance exposures. These data indicated a clear differentiation between “low risk” and “high risk” chemical exposure scenarios. Developing robust methods to characterize the cell culture bioactivity of foreign chemicals is an important part of non-animal safety assessment. The results presented in this work show that the cellular stress panel can be used, together with other new approach methodologies, to identify chemical exposures that are protective of consumer health. 😊
Toxicol Sci July 2020; 176: 11–33