4.4 Review

Mind the Gap! A Journey towards Computational Toxicology

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

资金

  1. program FIRB (Futuro in Ricerca) [RBFR12SJA8_003]
  2. Programma IDEA

向作者/读者索取更多资源

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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