Abstract
In silico models are evolving toward a more mature view, which integrates several perspectives. This integration proceeds on the application side toward a deeper exploitation of the data and information available, coping toward more challenging tasks. On a theoretical point of view, the QSAR models are nowadays most typically general models, at least in their ambition, while read-across is local. There are also general tools for prioritization. There are common aspects between these approaches, but also peculiar aspects. On the other side, users are interested in the application of these tools, for the evaluation of specific chemicals (which may relate to read-across and QSAR models), or for the assessment of populations of substances, also quite large (which may relate to QSAR and prioritization tools). In the development of VEGA, we tried to be as close as possible to the user’s need, reducing the barriers between the different approaches, and providing a series of tools which may fit different purposes. We describe below the philosophy of VEGA, and how the user may take advantage of the complex tools for different purposes.
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- AD:
-
Applicability domain
- ADI:
-
Applicability domain index
- BCF:
-
Bioconcentration factor
- CLP:
-
Classification, labeling, and packaging
- CMR:
-
Carcinogenic, mutagenic, or reprotoxicants
- ED:
-
Endocrine disruptors
- kNN:
-
k-nearest neighbor
- NTM:
-
Non-testing methods
- PBT:
-
Persistent, bioaccumulative, and toxic
- SA:
-
Structural alerts
- SOM:
-
Self-organizing map
- WoE:
-
Weight-of-evidence
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Acknowledgements
We acknowledge the LIFE + Program for funding, through the LIFE VERMEER project (LIFE16/ENV/IT 000167).
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Benfenati, E., Roncaglioni, A., Lombardo, A., Manganaro, A. (2019). Integrating QSAR, Read-Across, and Screening Tools: The VEGAHUB Platform as an Example. In: Hong, H. (eds) Advances in Computational Toxicology. Challenges and Advances in Computational Chemistry and Physics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-16443-0_18
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