title: "Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.
abstract: This work describes a novel semi-sequential technique for in silico enhancement of high-throughput screening (HTS) experiments now employed at Novartis. It is used in situations in which the size of the screen is limited by the readout (e.g., high-content screens) or the amount of reagents or tools (proteins or cells) available. By performing computational chemical diversity selection on a per plate basis (instead of a per compound basis), 25% of the 1,000,000-compound screening was optimized for general initial HTS. Statistical models are then generated from target-specific primary results (percentage inhibition data) to drive the cherry picking and testing from the entire collection. Using retrospective analysis of 11 HTS campaigns, the authors show that this method would have captured on average two thirds of the active compounds (IC(50) < 10 microM) and three fourths of the active Murcko scaffolds while decreasing screening expenditure by nearly 75%. This result is true for a wide variety of targets, including G-protein-coupled receptors, chemokine receptors, kinases, metalloproteinases, pathway screens, and protein-protein interactions. Unlike time-consuming "classic" sequential approaches that require multiple iterations of cherry picking, testing, and building statistical models, here individual compounds are cherry picked just once, based directly on primary screening data. Strikingly, the authors demonstrate that models built from primary data are as robust as models built from IC(50) data. This is true for all HTS campaigns analyzed, which represent a wide variety of target classes and assay types.
authors: Lead Discovery Center, Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA.
authors: Thomas J
authors: TJ
authors: Crisman
authors: Jeremy L
authors: JL
authors: Jenkins
authors: Christian N
authors: CN
authors: Parker
authors: W Adam G
authors: WA
authors: Hill
authors: Andreas
authors: A
authors: Bender
authors: Zhan
authors: Z
authors: Deng
authors: James H
authors: JH
authors: Nettles
authors: John W
authors: JW
authors: Davies
authors: Meir
authors: M
authors: Glick
mesh_terms: D001499:Bayes Theorem; D020650:Combinatorial Chemistry Techniques / Q000191:economics* / Q000379:methods*; D004353:Drug Evaluation, Preclinical / Q000191:economics* / Q000379:methods*; D004364:Pharmaceutical Preparations / Q000032:analysis*; D012984:Software; D013997:Time Factors
chemical_list: D004364:Pharmaceutical Preparations