Background: Computational exposure science represents a frontier of environmental science that is emerging and quickly evolving.
Objectives: In this commentary, we define this burgeoning discipline, describe a framework for implementation, and review some key ongoing research elements that are advancing the science with respect to exposure to chemicals in consumer products.
Discussion: The fundamental elements of computational exposure science include the development of reliable, computationally efficient predictive exposure models; the identification, acquisition, and application of data to support and evaluate these models; and generation of improved methods for extrapolating across chemicals. We describe our efforts in each of these areas and provide examples that demonstrate both progress and potential.
Conclusions: Computational exposure science, linked with comparable efforts in toxicology, is ushering in a new era of risk assessment that greatly expands our ability to evaluate chemical safety and sustainability and to protect public health.
Citation: Egeghy PP, Sheldon LS, Isaacs KK, Özkaynak H, Goldsmith M-R, Wambaugh JF, Judson RS, Buckley TJ. 2016. Computational exposure science: an emerging discipline to support 21st-century risk assessment. Environ Health Perspect 124:697-702; http://dx.doi.org/10.1289/ehp.1509748.
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http://dx.doi.org/10.1289/ehp.1509748 | DOI Listing |
EMBO Mol Med
January 2025
Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.
The exposome is the measure of all the exposures of an individual in a lifetime and how those exposures relate to health. Exposomics is the emerging field of research to measure and study the totality of the exposome. Exposomics can assist with molecular medicine by furthering our understanding of how the exposome influences cellular and molecular processes such as gene expression, epigenetic modifications, metabolic pathways, and immune responses.
View Article and Find Full Text PDFAutoimmun Rev
January 2025
Department of Gastroenterology, Postgraduate Institute of Medical Education and Research, Chandigarh, India. Electronic address:
Tuberculosis (TB), caused by Mycobacterium TB, is the most significant infectious cause of mortality across the globe. While TB disease can prey on immunocompetent individuals, it is more likely to occur in immunocompromised individuals. Immune-mediated inflammatory diseases (IMIDs) are a group of diseases (rheumatoid arthritis, inflammatory bowel disease, ankylosing spondylitis, psoriasis, hidradenitis suppurative, autoimmune blistering diseases, and others) where there may be a need for systemic immunosuppression to control the disease manifestations, treat symptoms and improve long term outcomes.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Division of Micro and Nanosystems (MST), School of Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology, Stockholm SE-10044, Sweden.
Controlled breakdown has emerged as an effective method for fabricating solid-state nanopores in thin suspended dielectric membranes for various biomolecular sensing applications. On an unpatterned membrane, the site of nanopore formation by controlled breakdown is random. Nanopore formation on a specific site on the membrane has previously been realized using local thinning of the membrane by lithographic processes or laser-assisted photothermal etching under immersion in an aqueous salt solution.
View Article and Find Full Text PDFLearn Mem
January 2025
Department of Psychology, Harvard University, Cambridge, Massachusetts 02138, USA
Agency beliefs influence how humans learn from different contexts and outcomes. Research demonstrates that stressors, such as exposure to early-life adversity (ELA), are associated with both agency beliefs and learning, but how these processes interact remains unclear. The current study investigated whether exposure to ELA influences agency and interacts with reinforcement learning in adults.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Vaccine Study Center, Northern California Division of Research, Kaiser Permanente, Oakland, CA, United States.
Background: Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial.
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