1.6 Calculation of results

There are several types of curve-fitting methods for computerized calculation. The two most often used are linear and non-linear algorithms. The choice depends on the shape of the measuring range for the particular assay. Most assays do not have a linear measuring range, thus the selection of algorithm should be non-linear. The Cubic Spline Regression analysis is a non-linear algorithm that is recommended by Mercodia.

The Spline method is a piecewise third order polynomial, which has knots at every calibrator concentration. The whole function and its first and second derivates are continuous.

There are two kinds of Spline fitting methods:

1. Smoothed Spline

If available, Smoothed Spline is the best method. It selects the degree of smoothing so that it reaches the optimal for a continuous function. An outlying calibrator value within the calibrator curve will not have an effect on the curve fitting.

2. Interpolation Spline

The curve fitting in Interpolation Spline method will draw the calibrator curves exactly through all calibrator responses. Since the calibrators may have outlying values this method would not yield a well-behaved continuous function. This is the recommended method for manual calculation.

Four-parameter log-logistic (4PL) is another non-linear algorithm. This is the second best choice after Smoothed Spline, although it does not compensate for outlying values.

If a curve-fitting program is not available, manual calculation can be done most accurately using Excel. When using manual calculation the absorbance values obtained for the calibrators are plotted against the concentration. Mercodia provides Excel evaluation sheets upon request, which uses the Interpolation Spline method.

When calculating results, the Blank/Calibrator 0 should be seen as a negative control and not be included in the calibration curve.

Back to Mercodia ELISA Technology