title: A model validation and consensus building environment.
abstract: Over half of the failures in drug development are due to problems with the absorption, distribution, metabolism, excretion, and toxicity, or ADME/Tox properties of a candidate compound. The utilization of in silico tools to predict ADME/Tox and physicochemical properties holds great potential for reducing the attrition rate in drug research and development, as this technology can prioritize candidate compounds in the pharmaceutical R&D pipeline. However, a major concern surrounding the use of in silico ADME/Tox technology is the reliability of the property predictions. Bio-Rad Laboratories, Inc. has created a computational environment that addresses these concerns. This environment is referred to as KnowItAll. Within this platform are encoded a number of ADME/Tox predictors, the ability to validate these predictors with/without in-house data and models, as well as build a 'consensus' model that may be a much better model than any of the individual predictive model. The KnowItAll system can handle two types of predictions: real number and categorical classification.
authors.affiliation: Bio-Rad Laboratories, 3316 Spring Garden Street, Philadelphia, PA 19104, USA. Michelle_D'Souza@Bio-Rad.com
authors.forename: T
authors.initials: T
authors.lastname: Abshear
authors.forename: G M
authors.initials: GM
authors.lastname: Banik
authors.forename: M L
authors.initials: ML
authors.lastname: D'Souza
authors.forename: K
authors.initials: K
authors.lastname: Nedwed
authors.forename: C
authors.initials: C
authors.lastname: Peng
mesh_terms: D016208:Databases, Factual; D015195:Drug Design; D008954:Models, Biological; D008956:Models, Chemical; D008970:Molecular Weight; D009152:Mutagenicity Tests; D016571:Neural Networks, Computer; D010599:Pharmacokinetics; D011485:Protein Binding; D015203:Reproducibility of Results; D012995:Solubility; D014116:Toxicology