title: A factorial design to optimize cell-based drug discovery analysis.
abstract: Drug discovery is dependent on finding a very small number of biologically active or potent compounds among millions of compounds stored in chemical collections. Quantitative structure-activity relationships suggest that potency of a compound is highly related to that compound's chemical makeup or structure. To improve the efficiency of cell-based analysis methods for high throughput screening, where information of a compound's structure is used to predict potency, we consider a number of potentially influential factors in the cell-based approach. A fractional factorial design is implemented to evaluate the effects of these factors, and lift chart results show that the design scheme is able to find conditions that enhance hit rates.
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695-8203, USA.
authors.forename: Bingming
authors.initials: B
authors.lastname: Yi
authors.forename: Jacqueline M
authors.initials: JM
authors.lastname: Hughes-Oliver
authors.forename: Lei
authors.initials: L
authors.lastname: Zhu
authors.forename: S Stanley
authors.initials: SS
authors.lastname: Young
mesh_terms: D019380:Anti-HIV Agents / Q000737:chemistry / Q000494:pharmacology; D002477:Cells; D003198:Computer Simulation; D016208:Databases, Factual; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000706:statistics & numerical data*; D006801:Humans; D008826:Microbial Sensitivity Tests / Q000706:statistics & numerical data; D021281:Quantitative Structure-Activity Relationship
chemical_list: D019380:Anti-HIV Agents