About this Research Topic
Chemical risk assessment has been widely applied in industry and government as an important tool to evaluate chemical toxicity in support of chemical registration, safety evaluation, and exposure limitation development protecting human and environmental health. However, traditional animal-based toxicological experiments are labor-intensive and time-consuming. To address the challenges of assessing potential human health risks for large chemicals in the market and chemicals introduced into the environment, New Approach Methodologies (NAMs) that are less resource intensive and faster are needed. Advances in in silico, in vitro high-throughput screenings, and in vivo omic technologies have created unique opportunities to transform chemical risk assessment from an observational science to an integrative field. This transformation will fundamentally advance the practice of next-generation chemical risk assessment.
The advances in toxicogenomics, high-throughput screening, molecular pathways, and adverse outcome pathways create unique opportunities to speed hazard identification, transform dose-response assessment, facilitate exposure assessment and fundamentally improve risk characterization. These advances substantially rely on big data that require advanced computational methodologies to process. This section focuses on collecting state-of-the-art works in assisting the transformations to the next generation risk assessment. The goal of this section is to provide the scientific basis for modernizing the risk assessment process. We focus on the incorporation of state-of-the-art advancements to make the risk assessment an efficient and mechanically explainable practice to meet the challenges of assessing potential human health risks for a variety of chemicals on the market and chemicals introduced into the environment.
All chemical risk assessment-related articles types are welcome. The scope of this Research Topic focuses on the use of new technologies and methodologies in chemical risk assessment, with an emphasis on submissions related to:
(1) the use of non-animal-based NAM (new approach methodologies) approaches to provide information for chemical hazard identification and risk assessment,
(2) new computational methods to process the NAM data for application in health risk assessments,
(3) new approaches to health risk assessment of chemical mixtures,
(4) adverse outcome pathway for assessing hazards to human health and the environment,
(5) computational models for risk prediction and the development of predictive toxicology,
(6) methodologies to quantify the uncertainty in toxicological risk assessment.
The advances in toxicogenomics, high-throughput screening, molecular pathways, and adverse outcome pathways create unique opportunities to speed hazard identification, transform dose-response assessment, facilitate exposure assessment and fundamentally improve risk characterization. These advances substantially rely on big data that require advanced computational methodologies to process. This section focuses on collecting state-of-the-art works in assisting the transformations to the next generation risk assessment. The goal of this section is to provide the scientific basis for modernizing the risk assessment process. We focus on the incorporation of state-of-the-art advancements to make the risk assessment an efficient and mechanically explainable practice to meet the challenges of assessing potential human health risks for a variety of chemicals on the market and chemicals introduced into the environment.
All chemical risk assessment-related articles types are welcome. The scope of this Research Topic focuses on the use of new technologies and methodologies in chemical risk assessment, with an emphasis on submissions related to:
(1) the use of non-animal-based NAM (new approach methodologies) approaches to provide information for chemical hazard identification and risk assessment,
(2) new computational methods to process the NAM data for application in health risk assessments,
(3) new approaches to health risk assessment of chemical mixtures,
(4) adverse outcome pathway for assessing hazards to human health and the environment,
(5) computational models for risk prediction and the development of predictive toxicology,
(6) methodologies to quantify the uncertainty in toxicological risk assessment.
Keywords: Risk assesment, toxicogenomics, computational toxicology, biostatistics, high throughput screening
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