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The primary screening of hybridoma cells is a time-critical and laborious step during the development of monoclonal antibodies. Often, critical errors occur in this phase, which supports the notion that the generation of monoclonal antibodies with hybridoma technology is difficult to control and hence, a risky venture. We think that it is crucial to improve the screening process to eliminate most of the critical deficits of the conventional approach. With this new microarray-based procedure, several advances could be achieved: Selectivity for excellent binders, high-throughput, reproducible signals, avoidance of misleading avidity (multivalency) effects, and performance of simultaneous competition experiments. The latter can also be used to select clones of desired cross-reactivity properties. In this paper, a model system with two excellent clones against carbamazepine, two weak clones, and blank supernatant containing fetal bovine serum was designed to examine the effectiveness of the new system. The excellent clones could be detected largely independent of the immunoglobulin G (IgG) concentration, which is usually unknown during the clone screening since the determination and subsequent adjustment of the antibody concentration are not feasible in most cases. Furthermore, in this approach, the enrichment, isolation, and purification of IgG for characterization is not necessary. Raw cell culture supernatant can be used directly, even when fetal calf serum (FCS) or other complex media is used. In addition, an improved method for the oriented antibody-immobilization on epoxy-silanized slides is presented. Based on the results of this model system with simulated hybridoma supernatants, we conclude that this approach should be preferable to most other protocols leading to many false positives, causing expensive and lengthy elimination steps to weed out the poor clones.
The demands for the assessment of water quality are increasing steadily, making it necessary to routinely monitor multiple contaminants in water samples. For this application a hapten microarray was developed. In order to reach the required low detection limits a design of experiments (DoE) approach was used to optimize the assay performance. Here we show that a Box-Behnken design plan is an adequate choice for the straightforward exploration of hapten microarray assay parameters. For both read-out systems studied (fluorophore-labelled detection antibodies or enzymatic signal development followed by reflectometric scan, respectively), it was possible to significantly extend the measurement ranges. Furthermore, it could be shown that multivariate data analysis, here partial least squares regression (PLS), can improve the prediction accuracy of 'unknown' samples when used as calibration model, compared to classical, univariate data evaluation methods.