Hi Melissa,

As far as I understand, inter-variability assesses the assay-to-assay reproducibility (measuring the same samples on different days, for example), whereas intra-variability looks at the variation of sample values within a single assay run.

A lot of companies who provide ELISAs will give validation data and show how they calculate inter-assay variability. For example, they might measure several samples within one lab on different days and calculate the Coefficient of variance (%CV) between the assay values (the average of the triplicate sample, for example). The lower the %CV, the less intervariability.

Intra-variability is assessed by looking at the replicate values (usually triplicate) within each sample assayed. You could look at the Standard deviation (SD) or Standard Error of the Mean (SEM) which will give you an idea of how close the replicate values are to each other.

Hi Melissa,

As far as I understand, inter-variability assesses the assay-to-assay reproducibility (measuring the same samples on different days, for example), whereas intra-variability looks at the variation of sample values within a single assay run.

A lot of companies who provide ELISAs will give validation data and show how they calculate inter-assay variability. For example, they might measure several samples within one lab on different days and calculate the Coefficient of variance (%CV) between the assay values (the average of the triplicate sample, for example). The lower the %CV, the less intervariability.

Intra-variability is assessed by looking at the replicate values (usually triplicate) within each sample assayed. You could look at the Standard deviation (SD) or Standard Error of the Mean (SEM) which will give you an idea of how close the replicate values are to each other.

In both cases, and in my opinion, the best way to calculate the variability between assays and duplicates/triplicates is CV=(SD/mean)*100. The lower CV the better, It should be less than 20%. Good luck

Victor- I think some people use