Section11:Method Validation (In-Study)

From Assay Guidance Wiki

The in-study validation phase is about making sure that the assay continues to perform per pre-defined specifications in each study run. During production phase, when the assays are being used for screening the unknowns, it is important to run validation/QC samples in every run with at least 2 replicates at high, middle and low concentrations (just one or two columns of a 96-well plate). Compute the average % recovery of these samples to make sure that the average recovery is within a reasonable range of accuracy (say, 80% to 120%). This might be adequate for quality control and is a reasonable compromise for any loss in assay throughput. Various methods may be considered for setting criteria for accepting or rejecting a study run during production run (in-study validation). This is addressed in a subsequent section in this chapter.

Example of an Immunoassay Validation Experiment

Set up numerous aliquots of the standard and store frozen at –70°C. If the standard concentration is much higher than the first point on your curve, pre-dilute it so that a single, simple dilution can be made in order to set up the standard curve.

Dilute the standards serially to obtain an 8 point standard curve in the matrix appropriate for the samples that need to be measured. For example if measuring tissue culture samples then the standards should be diluted in the same tissue culture medium that the samples are in. For serum samples, the standards should be diluted in serum diluted with an optimized buffer to the same dilution that the samples will be diluted.

Set up a series of spiked samples, again in the matrix appropriate for the samples that will be measured. The spiked control samples should not be the same concentration as in the standard curve and should cover the detectable range that the samples are thought to cover.

Follow the immunoassay protocol established during the optimization experiments. Set up the plate with 3-4 replicates of the standard curve and 4 or more replicates of the spiked control samples.

Assay at least 3 plates over 3 different days for a complete validation.

Validation Plate Layout

St1	St1	St1	St1	SP1	SP1	SP1	SP1
St2	St2	St2	St2	SP2	SP2	SP2	SP2
St3	St3	St3	St3	SP3	SP3	SP3	SP3
St4	St4	St4	St4	SP4	SP4	SP4	SP4
St5	St5	St5	St5	SP5	SP5	SP5	SP5
St6	St6	St6	St6	SP6	SP6	SP6	SP6
St7	St7	St7	St7	SP7	SP7	SP7	SP7
St8	St8	St8	St8	SP8	SP8	SP8	SP8

Validation Results from an IL-10 Immunoassay

The %recovery and the standard error that takes into account of the relevant sources of variation are plotted below. If X is 30%, then the quantification limits are the lowest and highest concentrations where the %recovery are within 70% to 130%. So for this assay, the lower quantification limit is the lowest concentration tested in this validation study (6.2 pg/ml), and the upper quantification limit is 3265 pg/ml.

IL-10

Plate Uniformity & Variability Experiment

It is important to check whether there is any systematic data trend across rows or columns of the 96-well plate and whether there is any significant variability between plates. An experiment with three plates and four concentrations of the standard can be done using the plate-layout given below. In this layout, C1, C2, C3 and C4 denote the standard concentrations from lowest to highest. For the purpose of illustration, data from one of the plates and a plot of the data from this experiment are given below for a sandwich ELISA. A systematic trend across columns is evident from this plot. For determining the statistical significance of this trend and the plate to plate variability, further statistical analysis of the data can be done with the help of a statistician.