Bayesian based similarity assessment of nanomaterials to inform grouping
Tài liệu tham khảo
Ag Seleci, 2022
Arts, 2015, A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping), Regul. Toxicol. Pharmacol., 71, S1, 10.1016/j.yrtph.2015.03.007
Aschberger, 2019, Grouping of multi-walled carbon nanotubes to read-across genotoxicity: a case study to evaluate the applicability of regulatory guidance, Comp. Toxicol., 9, 22, 10.1016/j.comtox.2018.10.001
Bahl, 2020, Nanomaterial categorization by surface reactivity: a case study comparing 35 materials with four different test methods, NanoImpact, 19, 10.1016/j.impact.2020.100234
Baranyi, 1993, Modeling bacterial growth responses, J. Ind. Microbiol. Biotechnol., 12, 190
Crump, 1984, A new method for determining allowable daily intakes, Toxicol. Sci., 4, 854, 10.1093/toxsci/4.5.854
Di Cristo, 2021
Drew, 2017, A quantitative framework to group nanoscale and microscale particles by hazard potency to derive occupational exposure limits: proof of concept evaluation, Regul. Toxicol. Pharmacol., 89, 253, 10.1016/j.yrtph.2017.08.003
ECHA, 2008
ECHA, 2019
ECHA, 2019
Greco, 1990, Application of a new approach for the quantitation of drug synergism to the combination of Cis-Diamminedichloroplatinum and 1-Beta-D arabinofuranosylcytosine, Cancer Res., 50, 5318
Greco, 1995, The search for synergy: a critical review from a response surface perspective, Pharmacol. Rev., 47, 331
Hamza, 2021, A Bayesian dose–response meta-analysis model: a simulations study and application, Stat. Methods Med. Res., 30, 1358, 10.1177/0962280220982643
Hennessey, 2010, A bayesian approach to dose–response assessment and synergy and its application to in vitro dose–response studies, Biometrics, 66, 1275, 10.1111/j.1541-0420.2010.01403.x
Hund-Rinke, 2018, Grouping concept for metal and metal oxide nanomaterials with regard to their Ecotoxicological effects on algae, Daphnids and fish embryos, NanoImpact, 9, 10.1016/j.impact.2017.10.003
Janer, 2021, Rationale and decision rules behind the ECETOC NanoApp to support registration of sets of similar nanoforms within REACH, Nanotoxicology, 15, 145, 10.1080/17435390.2020.1842933
Jeliazkova, 2021, How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity, NanoImpact, 25
Kass, 1995, Bayes factors, J. Am. Stat. Assoc., 90, 773, 10.1080/01621459.1995.10476572
Knudsen, 2019, Physicochemical predictors of multi-walled carbon nanotube–induced pulmonary histopathology and toxicity one year after pulmonary deposition of 11 different multi-walled carbon nanotubes in mice, Basic Clin. Pharmacol. Toxicol., 124, 211, 10.1111/bcpt.13119
Lamon, 2019, Grouping of nanomaterials to read-across hazard endpoints: a review, Nanotoxicology, 13, 100, 10.1080/17435390.2018.1506060
Ma, 2020, Nonlinear dose–response modeling of high-throughput screening data using an evolutionary algorithm, Dose-Response, 18, 10.1177/1559325820926734
OECD, 2014, Guidance on grouping of chemicals
Oomen, 2015, Grouping and read-across approaches for risk assessment of nanomaterials, Int. J. Environ. Res. Public Health, 12, 13415, 10.3390/ijerph121013415
Oomen, 2018, Risk assessment frameworks for nanomaterials: scope, link to regulations, applicability, and outline for future directions in view of needed increase in efficiency, NanoImpact, 9, 1, 10.1016/j.impact.2017.09.001
Peinjnenburg, 2021
Pinheiro, 2014, Model-based dose finding under model uncertainty using general parametric models, Stat. Med., 33, 1646, 10.1002/sim.6052
Pullen, 2014, Bayesian model comparison and parameter inference in systems biology using nested sampling, PLoS One, 9, 10.1371/journal.pone.0088419
Skilling, 2006, Nested sampling for general Bayesian computation, Bayesian Anal., 1, 833, 10.1214/06-BA127
Slob, 2002, Dose-response modeling of continuous endpoints, Toxicol. Sci., 66, 10.1093/toxsci/66.2.298
Stone, 2020, A framework for grouping and read-across of nanomaterials-supporting innovation and risk assessment, Nano Today, 35, 10.1016/j.nantod.2020.100941
Wohlleben, 2017, Nanoenabled products: categories, manufacture, and applications, 409
Zabeo, 2021, OWA Based grouping of nanomaterials with Arsinh and Dose Response similarity models, NanoImpact, 100370