We previously discussed the purpose of system suitability tests and sample suitability tests and gave some examples of each. However, we did not explain how to actually set the limits for these tests: suitability criteria. In this blog we will discuss this and go through a couple of examples of how to set suitability criteria…
Suitability tests for bioassay are often confusing. In this blog, we discuss the two types of suitability tests: System suitability tests and Sample suitability tests. The blog is deliberately simplistic in approach to aid basic understanding. In practice, the use of the various System and Sample suitability criteria may be more complex. We’ll focus mainly…
LD50 assays and challenge assays both measure the time to an event, often death, for each animal. However the standard statistical approach to the analysis of the data treats the endpoint as binary – alive / dead – at a given point in time. This is inefficient use of the data. Here, we will recommend…
It often happens that the precision required from a relative potency (RP) bioassay cannot be achieved using a single plate. In this situation the usual approach is to repeat the assay two or more times1. Each run of the assay will give a separate relative potency result. These are then combined to give a single…
We can waste about 40% of multi-well plates to avoid biasing the relative potency (RP) due to the “edge effect”. Quantics recently used a Latin square design to support a batch release assay designed to eliminate variation across the whole assay plate. This design allowed row and column effects to be identified and correctly accounted…
Our clients sometimes tell us that they don’t want to use response transformations since it feels like an unwarranted manipulation of the data. However, there is little point in avoiding a transformation just to get results that may be wrong. In this blog we explain when you should consider transforming the response, and how to…
Many of our readers will be familiar with our paper “Parallelism in Practice” (PDA Journal of Pharmaceutical Science and Technology, 2015) and how we examined the common methods used for evaluation of parallelism for bioassay. Here, we explain why the usual way of thinking about parallelism doesn’t always make sense when dealing with biosimilars; we…
Following the EurPh recommendations mixes up system and sample suitability and can lead to undesirable results. We recommend some alternative approaches to the problem.
We have previously discussed the 4 parameter logistic (4PL) model. Sometimes you may see slightly different versions of the 4PL equation – these are all mathematically equivalent. However, one thing to watch out for is that the meanings of the four parameters can vary between these versions. If you’re fitting a 4PL and getting parameter…
Our recent paper, Estimation of Relative Potency from Bioassay Data that Include Values below the Limit of Quantitation (Francis Bursa, Kelly J. Fleetwood, Karie J. Hirst and Ann Yellowlees), discusses values below the limit of quantitation (“LOQs” – sometimes called “non-reportables”) which are a common issue with bioassay data, and specifically how to deal with…
Previously, we discussed the definition of relative potency and how it relates to biological similarity, and therefore the need for parallelism between reference and test dose–response curves. In order to test for parallelism and calculate a relative potency, the assay data must be mathematically modelled. From a modelling perspective there are two fundamentally different types…
Relative potency (RP) refers to the dose of a test sample required to produce the same response in an assay as a dose of a reference sample. Since we (usually) know the potency of the reference sample, this gives us a measure of the potency of the test sample by comparing it to that reference….