Relative. Thanks for reading…But wait a moment! Have you ever stopped to ask why relative potency (RP) assays are the most common potency assay? Perhaps there are cases where absolute potency (AP) would be better? Indeed, Quantics occasionally come across clients who continue to use AP for their assays. Are they incorrect? Potency is, put…
Population Pharmacokinetics (PopPK) is the gold standard method of understanding drug safety and efficacy, particularly as it provides a unique insight into the variation of drug behaviour from person to person. While not a novel methodology—Sheiner, Rosenberg and Marathe first demonstrated the analysis in 1977—techniques and approaches in PopPK have undergone continual improvement in the…
What are the most important properties of a new drug? Ultimately, we want to ensure that any new therapy treats what it is designed to treat—that it’s effective—and that the patient suffers as few negative consequences as possible while doing it—that it’s safe. These two criteria often boil down to what the drug does to…
In the first part of this series, we investigated the use of the coefficient of determination—R2—to measure goodness-of-fit. Specifically, we showed that it is an inadequate tool: a low R2 does not always mean a poor model fit; a high R2 does not always mean a good model fit; and it doesn’t even measure the…
One of the most important concepts in bioassay is that of replication. Test samples are regularly replicated 2 or 3 times. Multiple response measurements at each dose will, in general, result in a better estimate of the precision of our result. As with all biological experiments, however, there is often quite a lot of variability…
One of the most important metrics when analysing bioassay data is goodness-of-fit — how well does a dataset fit a chosen model? In development, this question can help determine which model is appropriate for a dataset, while new data will have to meet a goodness-of-fit criteria to ensure it is adequately represented by the chosen…
This is the third blog responding to the software discussions at the BEBPA US 2022 conference. Blog One: formulae can be found here and Blog Two: Algorithms used can be found here. The key driver for these sessions was the experience that many have had of different software and different versions of the same software…
This is the second mini blog responding to the software discussions at the BEBPA US 2022 conference. Blog One: Formulae can be found here. The key driver for these sessions was the experience that many have had of different software and different versions of the same software giving different results. This causes problems with RP…
Myself, and my colleague Brooke, attended the BEBPA US virtual meeting last week and reported back on the presentation and round table discussions on relative potency software, including some questions about the use of different types of statistical model. The key driver for these sessions was the experience that many have had of different software…
Choosing the right Parallel Line Analysis (PLA) software for your lab is not an easy task. Whilst there are several packages available, and most can perform an adequate standard job, at least for development, it can be a challenge to know what aspects to consider. This is an important consideration as choosing the right software…
This blog introduces the concept of multiplicity, why it is important and offers some techniques for dealing with the issue. When planning a clinical study, lots of thought is put into what to measure – i.e., which data needs to be collected, how it should be analysed. This leads to the definition of so-called endpoints….
At the recent BEBPA meeting, in response to the question: ‘If you have a zero dose control on your plate do you include it in your 4PL model?’ 78% responded either “no” or “don’t know” or “did not know I could”. Well you can! Just add them into the datapoints for the reference and/or the…
Accuracy and Precision are properties of an experiment which are often conflated — not least because they are often synonymous in everyday conversation. In science, however, they have separate, well-defined meanings. Of course, this also applies to bioassay, so we thought we’d take a look at the difference here. Accuracy describes how close, on average,…
This is the third blog in our trilogy on techniques for population adjustment in network meta-analysis (NMA). Here we will focus on an approach called Multi-Level Network Meta-Regression (ML-NMR), which improves on several aspects of the methods we described in our first two blogs – Matching Adjusted Indirect Comparison (MAIC), and Simulated Treatment Comparison (STC)….
It has been sometime since I have set foot in a lab, but the thought of seeing outliers in my data still sends a shiver down my spine – don’t you just internally (or externally) groan when you see them in your assay results? Do you mask them and pretend they are not there, or…
In this blog we will describe an alternative approach to indirect comparison – Simulated Treatment Comparison (STC) – and discuss the key aspects to consider when looking to use the technique. We will discuss the situations when we would recommend using the method instead of a Matching Adjusted Indirect Comparison (MAIC). HTA submissions often involve…
We have all experienced the frustration (and sometimes utter dejection!) of performing a bioassay to what you thought was near perfection only to come back, analyse the data, and find out your assay has failed goodness-of-fit. This can happen even when, visually, the data points look to be very close to the fitted model! What…
Designing and running a clinical trial for a medical device is expensive, and to avoid wasting money, time and risking the validity of the trial, it is important to get the design right. To provide a little more insight, we thought we would discuss some recurring errors that Quantics has observed in trial synopses and…
Interim analyses are common in medical device trials for a variety of reasons. Just having a look is fine, but if the outcome of the analysis could change the conduct of the trial, for example by early stopping for superiority, futility or safety, then there is a problem. If the analysis result does stop the…
When comparing trial outcomes using standard network meta-analysis (NMA), the assumption is that populations in different trials do not differ in any characteristics that may impact the treatment effect (see this blog for an introduction to the concept of NMA). If this assumption is not true, these study differences then need to be accounted for…