Author: Matthew Stephenson

Bioassays can be expensive, both in terms of time and money. It is, therefore, sensible to consider bioassay optimisation: ways to design assays which minimise resource use while maximising throughput. This derives from the principle of lean manufacturing: processes which reduce waste while simultaneously increasing productivity and maintaining effective procedures. What is optimisation in bioassay?…

In parts 1 & 2 of our series on the confidence interval, we have covered some of the basic statistical concepts – means, standard deviations, and distributions – and how they can be used to describe the results obtained from a bioassay. Then, we described how we can investigate the distribution of our sample-based estimates…

A common discussion we at Quantics have with our clients surrounds the issue of pseudo-replicates. It’s an area of tension between scientist and statistician – pseudo-replicates reduce the cost of an assay, but also its statistical validity, meaning that a compromise solution is often required. One such solution is averaging pseudo-replicates, which comes with its…

In part 1 of our series covering the confidence interval, we examined some of the basic statistical concepts associated with a bioassay. In particular, we saw that a property of interest – we considered (and will continue to consider!) the EC50 of a test lot – follows a distribution defined by a mean (\(\mu\)) and…

A crucial acknowledgement of the scientific method is that no measurement will ever be perfect: results will always have associated variability, no matter how sophisticated the methodology used. Bioassay is no exception, so it is not surprising that one of the most common areas we address at Quantics is how to account for this uncertainty….