Optimizing ELISAs for precision and robustness using laboratory automation and statistical design of experiments.
Transferring manual ELISAs to automated platforms requires optimizing the assays for each particular robotic platform. These optimization experiments are often time consuming and difficult to perform using a traditional one-factor-at-a-time strategy. In this manuscript we describe the development of an automated process using statistical design of experiments (DOE) to quickly optimize immunoassays for precision and robustness on the Tecan EVO liquid handler. By using fractional factorials and a split-plot design, five incubation time variables and four reagent concentration variables can be optimized in a short period of time.
Bioprocess & Bioanalytical Research, Merck & Co. Inc., West Point, PA 19486, USA. daniel_joelsson@merck.com
Daniel
D
Joelsson
Phil
P
Moravec
Matthew
M
Troutman
Joseph
J
Pigeon
Pete
P
DePhillips
D000818:Animals; D001331:Automation / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D004797:Enzyme-Linked Immunosorbent Assay / Q000592:standards* / Q000706:statistics & numerical data*; D005163:Factor Analysis, Statistical; D006801:Humans; D015233:Models, Statistical; D015203:Reproducibility of Results; D012107:Research Design / Q000706:statistics & numerical data*; D012371:Robotics; D013997:Time Factors