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What is the standard curve from ELISA kit testing?

ELISA kits are commercialized reagent sets based on the immunosorbent assays, including competitive ELISA, indirect ELISA, direct ELISA, sandwich ELISA, etc. It is a widely used technique for detecting and quantifying specific proteins or other molecules in biological samples. Nowadays, there are too many commercial products based on ELISA in life sciences, environment sciences, clinical sciences, agricultural sciences, etc.

What is a standard curve?

In order to get a quantitative test result in ELISA testing, a Standard Curve is always necessary. It is obtained from the testing of known or artificially prepared standard chemicals or proteins. For example, in the aflatoxin ELISA kit, there will be some standard solutions ranging from 0, 5, 10, 25, 50, 100 ng/L. During the real testing, these standard solutions will be used and a Standard Curve will be plotted using the mean absorbance (y-axis) against the standard concentration (x-axis). With certain curve regression model, the concentration of aflatoxin M1 in unknown samples can be calculated based on the absorbance (OD value).

What are the key factors for a stable standard curve?

To avoid operational errors, always run ELISA samples in duplicate or triplicate. This provides enough data for statistical validation. Calculate the average absorbance values for each set of duplicate standards and duplicate samples. Meanwhile, this is also helpful for eliminating the STRANGE value or OUT-OF-RANGE value.  Besides, running multiple duplicates is also good to check the standard deviations of the testing. This is helpful for evaluating the stability of the ELISA kit, as well the operation of the lab staff. Larger variance indicates greater inconsistency and error.  Remember to follow good laboratory practices, such as accurate pipetting, avoiding contamination, and maintaining stable incubation temperatures, to ensure reliable ELISA results.

How to do the standard curve calculation?

There are many different models for standard curve calculation, for examples, the Four-Parameter Logistic (4PL) Curve. It follows a sigmoidal (“S”-shaped) curve.  Particularly useful for characterizing bioassays because they are often linear across a specific range of concentration magnitudes.  Besides the 4PL curve, other regression models (such as linear, quadratic, or cubic) can be feasible based on the specific characteristics of your data. Normally we use curve-plotting software to determine the concentration of sample, such as CurveExpert, etc.