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Accurate Hit Estimation for Iterative Screening Using Venn-ABERS Predictors
Department of Information Technology, University of Borås, Borås, Sweden.
Discovery Sciences, AstraZeneca IMED Biotech Unit, Mölndal, Sweden.
Discovery Sciences, AstraZeneca IMED Biotech Unit, Mölndal, Sweden.
Discovery Sciences, AstraZeneca IMED Biotech Unit, Mölndal, Sweden.
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2019 (English)In: Journal of Chemical Information and Modeling, ISSN 1549-9596, E-ISSN 1549-960X, Vol. 59, no 3, p. 1230-1237Article in journal (Refereed) Published
Abstract [en]

Iterative screening has emerged as a promising approach to increase the efficiency of high-throughput screening (HTS) campaigns in drug discovery. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models. One of the challenges of iterative screening is to decide how many iterations to perform. This is mainly related to difficulties in estimating the prospective hit rate in any given iteration. In this article, a novel method based on Venn - ABERS predictors is proposed. The method provides accurate estimates of the number of hits retrieved in any given iteration during an HTS campaign. The estimates provide the necessary information to support the decision on the number of iterations needed to maximize the screening outcome. Thus, this method offers a prospective screening strategy for early-stage drug discovery.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2019. Vol. 59, no 3, p. 1230-1237
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-43510DOI: 10.1021/acs.jcim.8b00724ISI: 000462943700027PubMedID: 30726080Scopus ID: 2-s2.0-85063371683Local ID: ;JTHDatateknikISOAI: oai:DiVA.org:hj-43510DiVA, id: diva2:1306285
Funder
Knowledge Foundation, 20150185Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-08-22Bibliographically approved

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Johansson, Ulf

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