title: Classification models for safe drug molecules.
abstract: Frequent failure of drug candidates during development stages remains the major deterrent for an early introduction of new drug molecules. The drug toxicity is the major cause of expensive late-stage development failures. An early identification/optimization of the most favorable molecule will naturally save considerable cost, time, human efforts and minimize animal sacrifice. (Quantitative) Structure Activity Relationships [(Q)SARs] represent statistically derived predictive models correlating biological activity (including desirable therapeutic effect and undesirable side effects) of chemicals (drugs/toxicants/environmental pollutants) with molecular descriptors and/or properties. (Q)SAR models which categorize the available data into two or more groups/classes are known as classification models. Numerous techniques of diverse nature are being presently employed for development of classification models. Though there is an increasing use of classification models for prediction of either biological activity or toxicity, the future trend will naturally be towards the development of classification models capable of simultaneous prediction of biological activity, toxicity, and pharmacokinetic parameters so as to accelerate development of bioavailable safe drug molecules.
authors.affiliation: Department of Pharmaceutical Sciences, Pt. B.D. Sharma University of Health Sciences, Rohtak, India. madan_ak@yahoo.com
authors.forename: A K
authors.initials: AK
authors.lastname: Madan
authors.forename: Sanjay
authors.initials: S
authors.lastname: Bajaj
authors.forename: Harish
authors.initials: H
authors.lastname: Dureja
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D016000:Cluster Analysis; D003663:Decision Trees; D016002:Discriminant Analysis; D005163:Factor Analysis, Statistical; D006801:Humans; D010363:Pattern Recognition, Automated; D004364:Pharmaceutical Preparations / Q000145:classification*; D025341:Principal Component Analysis; D021281:Quantitative Structure-Activity Relationship; D060388:Support Vector Machine; D057188:Workflow
chemical_list: D004364:Pharmaceutical Preparations