Optimizing assays
The need to screen large libraries of chemical compounds has been enabled in recent years by developments in high-throughput technologies
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BASEL—The need to screen large libraries of chemical compounds has been enabled in recent years by developments in high-throughput technologies, but according to researchers at the Novartis Institutes for Biomedical Research, this has also had the side effect of moving the lead discovery bottleneck toward assay development and miniaturization. At the recent SBS conference, however, they report on a possible solution to this bottleneck.
Because traditional one-factor-at-a-time (OFAT) methods of optimization are both time and resource intensive, the researchers looked for ways to combine design-of-experiment (DOE) and automated assay optimization (AAO). They found they achieved the best results when they conducted the initial screening phase with more factors (>7), and once the key factors have been identified, use a response surface model design in the optimization phase.
They used this approach to optimize a serine protease assay and found that whereas an OFAT approach could require weeks or months, the DOE/AAO approach resulted in optimized conditions within 3 days, saving significant resources such as reagents.
