Assay Optimization: A Statistical Design of Experiments Approach - 09/08/11
Doi : 10.1016/j.cll.2007.01.001
Maneesha Altekar, PhD a, Carol A. Homon, MS b, Mohammed A. Kashem, PhD b, Steven W. Mason, PhD b, Richard M. Nelson, PhD b, Lori A. Patnaude, MS b, Jeffrey Yingling, PhD c, Paul B. Taylor, MS b, ⁎ 
a Hercules, 1313 North Market Street, Wilmington, DE 19894-0001, USA
b Boehringer Ingelheim Pharmaceuticals, Inc., 900 Ridgebury Road, PO Box 368, Ridgefield, CT 06877, USA
c Aerie Pharmaceuticals, Inc., 7020 Kit Creek Road, Suite 270, PO Box 12320, Research Triangle Park, NC 27709, USA
Corresponding author.Abstract |
With the transition from manual to robotic HTS in the last several years, assay optimization has become a significant bottleneck. Recent advances in robotic liquid handling have made it feasible to reduce assay optimization timelines with the application of statistically designed experiments. When implemented, they can efficiently optimize assays by rapidly identifying significant factors, complex interactions, and nonlinear responses. This article focuses on the use of statistically designed experiments in assay optimization.
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© 2007
Elsevier Inc. Tous droits réservés.
Vol 27 - N° 1
P. 139-154 - mars 2007 Retour au numéro
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