
GUIDE
RUN STATISTICALLY POWERED STRAIN SCREENING EXPERIMENTS
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Running an inadequate number of replicates can have serious consequences for your strain development programs and overall progress. If your sample size is too small, you may be getting false-positive results, meaning you’re promoting strains that are no better than the control strain. Or, you may be getting false negatives and missing the strain that could be your new production strain. Either way, you’re wasting time and resources, slowing progress, and potentially missing milestones.
For example, if you have a 25% false-positive rate and you’re not accounting for that, you’re effectively adding 25% more time to your process because you’re promoting strains that are not in fact improved. You could have had statistically significant data weeks or months before if you had run enough replicates the first time.
In this guide, learn how to conduct a power analysis to determine the correct number of replicates for your experiment and accelerate strain development.
What could you achieve with more bioreactor capacity?
You’re no longer limited by the bioreactor capacity in your lab.