期刊
MOLECULAR INFORMATICS
卷 35, 期 8-9, 页码 294-308出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/minf.201501017
关键词
data quality; read-across; applicability domain; toxicology databases; drug discovery
类别
资金
- program FIRB (Futuro in Ricerca) [RBFR12SJA8_003]
- Programma IDEA
Computational methods have advanced toxicology towards the development of target-specific models based on a clear cause-effect rationale. However, the predictive potential of these models presents strengths and weaknesses. On the good side, in silico models are valuable cheap alternatives to in vitro and in vivo experiments. On the other, the unconscious use of in silico methods can mislead end-users with elusive results. The focus of this review is on the basic scientific and regulatory recommendations in the derivation and application of computational models. Attention is paid to examine the interplay between computational toxicology and drug discovery and development. Avoiding the easy temptation of an overoptimistic future, we report our view on what can, or cannot, realistically be done. Indeed, studies of safety/toxicity represent a key element of chemical prioritization programs carried out by chemical industries, and primarily by pharmaceutical companies.
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