Literature DB >> 10022323

Integrating computer prediction systems with in vitro methods towards a better understanding of toxicology.

M D Barratt1.   

Abstract

Structure Activity Relationships (SARs) or Quantitative Structure Activity Relationships (QSARs) form the basis of most computer prediction systems in toxicology. The underlying premise of SARs and QSARs is that the properties of a chemical are implicit in its molecular structure. For an SAR or QSAR to be valid and reliable, the dependent property for all of the chemicals covered by the relationship has to be elicited by a mechanism which is both common to the set of chemicals as well as relevant to that dependent property. Similar principles must also be applied to the development of in vitro alternatives to animal tests if those methods are to be reliable. A number of ways in which computer prediction systems and in vitro toxicology can complement each other in the development of alternatives to live animal experiments are described.

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Year:  1998        PMID: 10022323     DOI: 10.1016/s0378-4274(98)00266-5

Source DB:  PubMed          Journal:  Toxicol Lett        ISSN: 0378-4274            Impact factor:   4.372


  2 in total

Review 1.  Drug Adverse Reaction Target Database (DART) : proteins related to adverse drug reactions.

Authors:  Zhi Liang Ji; Lian Yi Han; Chun Wei Yap; Li Zhi Sun; Xin Chen; Yu Zong Chen
Journal:  Drug Saf       Date:  2003       Impact factor: 5.606

2.  Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

Authors:  Patricia Ruiz; Gino Begluitti; Terry Tincher; John Wheeler; Moiz Mumtaz
Journal:  Molecules       Date:  2012-07-27       Impact factor: 4.411

  2 in total

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