Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Andrea-Nicole Richarz"'
Publikováno v:
Beilstein Journal of Nanotechnology, Vol 6, Iss 1, Pp 1978-1999 (2015)
Analysis of trends in nanotoxicology data and the development of data driven models for nanotoxicity is facilitated by the reporting of data using a standardised electronic format. ISA-TAB-Nano has been proposed as such a format. However, in order to
Externí odkaz:
https://doaj.org/article/ee1cf58238be4952856ab10e3d5aaca4
Publikováno v:
Computational Toxicology. 9:1-11
Read-across as an alternative assessment method for chemical toxicity has growing interest in both the regulatory and industrial communities. The pivotal means of acquiring acceptance of a read-across prediction is identifying and assessing uncertain
Autor:
Andrew Worth, David Asturiol, G. Janer, Andrea-Nicole Richarz, J. Cabellos, Lara Lamon, J. Damásio, A. Vilchez
Publikováno v:
Computational Toxicology. 9:133-142
The development of physiologically based (PB) models to support safety assessments in the field of nanotechnology has grown steadily during the last decade. This review reports on the availability of PB models for toxicokinetic (TK) and toxicodynamic
Autor:
Tomi Peltola, Paul Blomstedt, Paul Whaley, Barbara Raffael, Maurice Whelan, John Paul Gosling, Clemens Wittwehr, Marta Sienkiewicz, Andrea-Nicole Richarz, Andrew Worth
Publikováno v:
Computational Toxicology (Amsterdam, Netherlands)
Highlights • Artificial Intelligence (AI) has potential to improve chemical risk assessment (CRA) and associated regulatory decisions. • AI could influence the scientific-technical evaluation process and the social aspects of the CRA decision mak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aedcb86a45b4fe80033ad2e0ff83dc85
https://aaltodoc.aalto.fi/handle/123456789/101567
https://aaltodoc.aalto.fi/handle/123456789/101567
Autor:
Andrea-Nicole Richarz
Publikováno v:
Big Data in Predictive Toxicology ISBN: 9781782622987
Predictive toxicology and model development rely heavily on data to draw upon and have historically suffered from the paucity of available and good quality datasets. The situation has now dramatically changed from a lack of data hampering model devel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee53bac92fe863a82afce828933416de
https://doi.org/10.1039/9781782623656-00001
https://doi.org/10.1039/9781782623656-00001
Publikováno v:
Big Data in Predictive Toxicology ISBN: 9781782622987
The toxicity of similar chemicals can be read across to fill data gaps. As such, read-across provides a pragmatic solution to data gap filling and is of considerable interest to reduce the reliance on animal testing for regulatory purposes, or where
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa06a4ec59f9c1959bd4e4c5c4a5d8c0
https://doi.org/10.1039/9781782623656-00359
https://doi.org/10.1039/9781782623656-00359
Autor:
Andrea-Nicole Richarz, Katarzyna R. Przybylak, Terry W Schultz, Steven P. Bradbury, Claire L. Mellor, Mark T. D. Cronin
Publikováno v:
Computational Toxicology
© 2017 Elsevier B.V. 2-Alkyl-1-alkanols offer an example whereby the category approach to read-across can be used to predict repeated-dose toxicity for a variety of derivatives. Specifically, the NOAELs of 125 mg/kg bw/d for 2-ethyl-1-hexanol and 2-
Publikováno v:
Computational Nanotoxicology ISBN: 9780429341373
Computational Nanotoxicology
Computational Nanotoxicology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1c917e62ed3767b7e09d876c314ba09
https://doi.org/10.1201/9780429341373-8
https://doi.org/10.1201/9780429341373-8
Autor:
Kirsten Gerloff, J.G.M. Bessems, Andrea-Nicole Richarz, Lara Lamon, Karin Aschberger, David Asturiol, Andrew Worth
Publikováno v:
Computational Nanotoxicology ISBN: 9780429341373
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43af11c38de79ea2aeb958905969d44b
https://doi.org/10.1201/9780429341373-1
https://doi.org/10.1201/9780429341373-1
Publikováno v:
Computational Nanotoxicology ISBN: 9780429341373
This chapter provides an overview of the European Union (EU) project research landscape in computational nanotoxicology, highlights the challenges for development and use of computational approaches in the safety assessment of nanomaterials and analy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b5b0113529ed37012d3969e181fac49
https://doi.org/10.1201/9780429341373-2
https://doi.org/10.1201/9780429341373-2