کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1222336 | 967861 | 2009 | 8 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins](/preview/png/1222336.png)
Developing a process that generates robust immunoassays that can be used to support studies with tight timelines is a common challenge for bioanalytical laboratories. Design of experiments (DOEs) is a tool that has been used by many industries for the purpose of optimizing processes. The approach is capable of identifying critical factors and their interactions with a minimal number of experiments. The challenge for implementing this tool in the bioanalytical laboratory is to develop a user-friendly approach that scientists can understand and apply. We have successfully addressed these challenges by eliminating the screening design, introducing automation, and applying a simple mathematical approach for the output parameter.A modified central composite design (CCD) was applied to three ligand binding assays. The intra-plate factors selected were coating, detection antibody concentration, and streptavidin–HRP concentrations. The inter-plate factors included incubation times for each step. The objective was to maximize the log S/B (S/B) of the low standard to the blank. The maximum desirable conditions were determined using JMP 7.0. To verify the validity of the predictions, the log S/B prediction was compared against the observed log S/B during pre-study validation experiments.The three assays were optimized using the multi-factorial DOE. The total error for all three methods was less than 20% which indicated method robustness. DOE identified interactions in one of the methods. The model predictions for log S/B were within 25% of the observed pre-study validation values for all methods tested. The comparison between the CCD and hybrid screening design yielded comparable parameter estimates.The user-friendly design enables effective application of multi-factorial DOE to optimize ligand binding assays for therapeutic proteins. The approach allows for identification of interactions between factors, consistency in optimal parameter determination, and reduced method development time.
Journal: Journal of Pharmaceutical and Biomedical Analysis - Volume 49, Issue 2, 20 February 2009, Pages 311–318