Suchergebnisse

Traditional additivity models provide little flexibility in modeling the dose–response relationships of the single agents in a mixture. While the flexible single chemical required (FSCR) methods allow greater flexibility, its implicit nature is an obstacle in the formation of the parameter covariance matrix, which forms the basis for many statistical optimality design criteria. The goal of this effort is to develop a method for constructing the parameter covariance matrix for the FSCR models, so that (local) alphabetic optimality criteria can be applied. Data from Crofton et al. are provided as motivation; in an experiment designed to determine the effect of 18 polyhalogenated aromatic hydrocarbons on serum total thyroxine (T4), the interaction among the chemicals was statistically significant. Gennings et al. fit the FSCR interaction threshold model to the data. The resulting estimate of the interaction threshold was positive and within the observed dose region, providing evidence of a dose‐dependent interaction. However, the corresponding likelihood‐ratio‐based confidence interval was wide and included zero. In order to more precisely estimate the location of the interaction threshold, supplemental data are required. Using the available data as the first stage, the Ds‐optimal second‐stage design criterion was applied to minimize the variance of the hypothesized interaction threshold. Practical concerns associated with the resulting design are discussed and addressed using the penalized optimality criterion. Results demonstrate that the penalized Ds‐optimal second‐stage design can be used to more precisely define the interaction threshold while maintaining the characteristics deemed important in practice.

When assessing risks posed by environmental chemical mixtures, whole mixture approaches are preferred to component approaches. When toxicological data on whole mixtures as they occur in the environment are not available, Environmental Protection Agency guidance states that toxicity data from a mixture considered "sufficiently similar" to the environmental mixture can serve as a surrogate. We propose a novel method to examine whether mixtures are sufficiently similar, when exposure data and mixture toxicity study data from at least one representative mixture are available. We define sufficient similarity using equivalence testing methodology comparing the distance between benchmark dose estimates for mixtures in both data‐rich and data‐poor cases. We construct a "similar mixtures risk indicator"(SMRI) (analogous to the hazard index) on sufficiently similar mixtures linking exposure data with mixtures toxicology data. The methods are illustrated using pyrethroid mixtures occurrence data collected in child care centers (CCC) and dose‐response data examining acute neurobehavioral effects of pyrethroid mixtures in rats. Our method shows that the mixtures from 90% of the CCCs were sufficiently similar to the dose‐response study mixture. Using exposure estimates for a hypothetical child, the 95th percentile of the (weighted) SMRI for these sufficiently similar mixtures was 0.20 (i.e., where SMRI <1, less concern; >1, more concern).

Abstract
The adverse outcome pathway (AOP) framework serves as a practical tool for organising scientific knowledge that can be used to infer cause–effect relationships between stressor events and toxicity outcomes in intact organisms. However, a major challenge in the broader application of the AOP concept within regulatory toxicology is the development of a robust AOPs that can withstand peer review and acceptance. This is mainly due to the considerable amount of work required to substantiate the modular units of a complete AOP, which can take years from inception to completion. The methodology used here consisted of an initial assessment of a single chemical hazard using the Integrated Approach to Testing and Assessment (IATA) framework. An evidence‐based approach was then used to gather empirical evidence combining systematic literature review methods with expert knowledge to ensure the effectiveness of the AOP development methodology. The structured framework used assured transparency, objectivity and comprehensiveness, and included expert knowledge elicitation for the evaluation of key event relationships (KERs). This stepwise approach led to the development of an AOP that begins with binding of chemicals to Voltage Gate Sodium Channels (VGSC/Nav) during mammalian development leading to adverse consequences in neurodevelopment evidenced as deficits in cognitive functions. Disruption of the formation of precise neural circuits by alterations in VGSC kinetics during the perinatal stages of brain development may also underlie neurodevelopmental disorders. Gaps in our understanding include the specific critical developmental windows and the quantitative relationship of binding to VGSC and subsequent disruption and cognitive function. Despite the limited quantitative information at all KER levels, regulatory applications of this AOP for DNT assessment have been identified.

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and nongovernmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathway-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this.

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and nongovernmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathway-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this.

In this manuscript, which appeared in ALTEX 35 , 306-352 ( doi:10.14573/altex.1712081 ), the Acknowledgements should read: This work was supported by the Doerenkamp-Zbinden Foundation, EFSA, the BMBF, JPI-NutriCog-Selenius, and it has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 681002 (EU-ToxRisk).