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Statistical Decoding of Potent Pools Based on Chemical Structure
Author(s) -
Zhu Lei,
HughesOliver Jacqueline M.,
Young S. Stanley
Publication year - 2001
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2001.00922.x
Subject(s) - pooling , drug discovery , decoding methods , computer science , computational biology , process (computing) , false discovery rate , chemical structure , combinatorial chemistry , data mining , chemistry , bioinformatics , algorithm , artificial intelligence , biology , biochemistry , gene , operating system , organic chemistry
Summary. Pooling experiments are used as a cost‐effective approach for screening chemical compounds as part of the drug discovery process in pharmaceutical companies. When a biologically potent pool is found, the goal is to decode the pool, i.e., to determine which of the individual compounds are potent. We propose augmenting the data on pooled testing with information on the chemical structure of compounds in order to complete the decoding process. This proposal is based on the well‐known relationship between biological potency of a compound and its chemical structure. Application to real data from a drug discovery process at GlaxoSmithKline reveals a 100% increase in hit rate, namely, the number of potent compounds identified divided by the number of tests required.