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

Authors
Citation
Md. Barratt, Integrating computer prediction systems with in vitro methods towards a better understanding of toxicology, TOX LETT, 103, 1998, pp. 617-621
Citations number
15
Categorie Soggetti
Pharmacology & Toxicology
Journal title
TOXICOLOGY LETTERS
ISSN journal
03784274 → ACNP
Volume
103
Year of publication
1998
Pages
617 - 621
Database
ISI
SICI code
0378-4274(199812)103:<617:ICPSWI>2.0.ZU;2-9
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 propertie s 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 prope rty. 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 c omplement each other in the development of alternatives to live animal expe riments are described. (C) 1998 Elsevier Science Ireland Ltd. All rights re served.