A concept we’ve discussed several times over the years is that of homogeneity of variance. We highlight it so regularly as it’s among the most critical properties that relative potency data must have before valid statistical inference can take place, and often requires careful consideration to realise. We’ve previously covered one common way to ensure that homogeneity of variance is ensured: response transformations. Here, we’re going to take a look at an alternative method for restoring homogeneity of variance: response weighting. What is Homogeneity of Variance, and Why does it Matter? T ..read more

In previous blogs, we’ve examined the statistics behind Non-Compartmental PK/PD analysis. The existence of the Non-Compartmental Analysis (NCA) implies the existence of compartmental analysis, and, indeed, it is among the most commonly used methodologies for PK/PD statistics. Rather than extract results from data alone as in an NCA, a compartmental analysis involves fitting a model of the movement of a drug through the body to the collected data. This is done by dividing the body into theoretical “compartments” which the drug can flow into and out from.  A compartmental analysis can use ..read more

In our blog introducing bioequivalence, we described how studies establishing bioequivalence can be a way to avoid expensive clinical trials without compromising on the safety or efficacy of a drug product. In particular, this applies for generic versions of already approved drugs, or for different dosage routes for those drugs. In these cases, bioequivalence studies can replace a traditional clinical trial in approving the product under an Abbreviated New Drug Application (ANDA), dramatically decreasing the cost of bringing a drug product to market. The FDA issue guidances for a large varie ..read more

The post Blah appeared first on Quantics Biostatistics ..read more

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 using the standard error and the central limit theorem. Here, we’re going to use the ideas we’ve discussed previously to, at last, fully define the confidence interval, describe the process of constructing one, and investigate it’s meaning. The Ingredients Let’s retu ..read more

Validation of statistical software is required for use in regulatory work. Many auditors expect to see the traditional IQ, OQ, PQ approach applied to the base system (SAS, R, etc). This approach, however, was never mandated by the FDA – or anyone else – and was never really suited to software validation because it ignores the inevitability of undetectable bugs in the code. The new CSA guidelines from the FDA, released in September 20221, seek to re-focus validation effort on those issues of the greatest importance, and go some way to expose the fallacy of the traditional approach. Much has be ..read more

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 own set of pros and cons. We want to examine when pseudo-replication might prove problematic and take an empirical look at why averaging your pseudo-replicates may be a good idea. True Replicates vs Pseudo-replicates In bioassays ..read more

The United States Pharmacopeia (USP) guidance on biological assay validation, General Chapter <1033>, will soon be updated. In the leadup to the publication of the new guidance, Quantics co-founder Dr Ann Yellowlees has presented on the changes at the recent BEBPA conferences in both the US and Europe. Here, we summarise some of the most important changes in the new version of USP <1033>, highlighted by Ann, and discuss what they mean for those looking to undergo an assay validation in future. Setting assay acceptance criteria based on the probability of an Out-Of-Specification r ..read more

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 () and a standard deviation (). Note again that we shall assume all EC50s are measured on the log scale, as in part 1. Whenever we measure the EC50, the result is drawn from this distribution – we are more likely to observe EC50s close to , with the likelihood of observing a value ..read more

… The post Subscribe to the Quantics Blog appeared first on Quantics Biostatistics ..read more