Analysis and prediction of combinatorial chemistry synthesis and screening data.
The goal of combinatorial chemistry is to simultaneously synthesize sets of compounds possessing properties that are then distinguished through screening. As the size of a compound set increases, data analysis becomes more challenging. Analysis of Variance (ANOVA) is an accepted statistical method that offers a straightforward solution to this problem. Two steps encountered by combinatorial scientists appear well suited to ANOVA: the prediction of synthetic outcomes (purity and yield) of set members and the analysis of screening data to identify combinations of reagent inputs that result in molecules with a desired property. To illustrate, a subset of a combinatorial array, referred to as a reaction rehearsal set, is evaluated to create a model predictive of the individual synthetic outcomes of the full matrix. In a second exercise, the biochemical screening data obtained from a combinatorial library is analyzed to identify reagent interactions that result in molecules possessing the sought activity.
Ge
Nanxiang
N
Daiichi-Sankyo, Inc., Edison, NJ 08837, USA. nge@daiichisankyo-us.com
Fogel
Paul
P
Young
Sidney S
SS
Austin
Richard E
RE
Wegrzyniak
Eric
E
Connelly
James A
JA
D000704:Analysis of Variance; D020650:Combinatorial Chemistry Techniques; D004353:Drug Evaluation, Preclinical / Q000706:statistics & numerical data*; D016014:Linear Models; D008956:Models, Chemical; D011237:Predictive Value of Tests