Quality, design, performance

Our broad menu of over 2,000 ELISA kits provides accurate and consistent results for all of your research needs. Each Invitrogen™ ELISA kit meets rigorous specifications and is manufactured with stringent quality controls to help ensure excellent quality and reproducibility.

Choose individual target-specific ELISA kits using the following selection guide.

Find ELISA kits by target

Our ELISA kits are thoroughly validated to help ensure they meet the high standards you have come to expect. Kits are tested for factors such as:

Data acquired from these validation tests are typically available in each kit’s manual—either in the kit packaging or on the product webpage. If you have any questions please contact Technical Support.

Intra-assay precision

Intra-assay validation shows the reproducibility between wells within an assay plate. Data resulting from intra-assay validation helps ensure that samples run in different wells of the plate will give comparable results. Below are an examples of data generated and reported for a representative intra-assay validation experiment. In this example, our VCAM-1 ELISA Kit, Human (Cat. No. KHT0601) was evaluated by testing 14 replicates each for three samples in the same assay. The resulting low %CV for each sample indicates good reproducibility within the assay. Samples with known Hu sVCAM-1 concentration were assayed in replicates of 14 to determine precision within an assay.

Parameters Sample 1 Sample 2 Sample 3
Mean (ng/mL) 1.23 4.33 18.59
SD 0.06 0.33 1.43
CV (%) 4.85 7.62 7.68

SD = standard deviation. CV = coefficient of variation.

Inter-assay precision

Inter-assay precision shows the reproducibility between assays done on different days. Inter-assay precision is typically <10%. This ensures the results obtained will be consistent over time and between kits. Below are examples of typical data generated and reported for inter-assay precision. In this example, our Aβ 42 Ultrasensitive ELISA Kit, Human (Cat. No. KHB3544) was used to test three samples, 36 times over multiple days. The results show CVs of less than a 10 %, thus demonstrating good reproducibility between assays.

Parameters Sample 1 Sample 2 Sample 3
Mean (ng/mL) 71.30 40.16 21.29
SD 5.24 3.96 1.13
CV (%) 7.36 9.85 5.32

SD = standard deviation. CV = coefficient of variation.


Linearity of dilution

Linearity is defined relative to the calculated amount of analyte based on the standard curve. The final calculated concentration for an analyte in a sample should be the same for any dilution that falls within the quantitative range of the assay. A well-developed immunoassay kit minimizes the potential effects of various sample matrices and other factors that may interfere. Linearity-of-dilution validation experiments provide information about the precision of results for samples tested at various dilution levels. Linearity of dilution is tested for each validated sample type and is considered to be good if results are 70–130% of the expected concentration for each dilution. Linearity is important for accurate measurement of analyte concentration across the assay’s dynamic range.

Linearity of dilution for a particular sample type is typically represented as shown in the table below. In this example, our c-Myc (total) ELISA Kit, Human (Cat. No. KHO2041) was evaluated using HeLa cell lysates. HeLa cell lysate was diluted in the kit’s diluent buffer across the dynamic range of the assay. The measured versus expected values show good assay linearity and no significant interference from sample matrices.

HeLa cells were grown in DMEM (Cat. No. P104-500) containing 10% fetal bovine serum at 37°C, lysed with Cell Extraction Buffer, and sonicated. This lysate was diluted in Standard Diluent Buffer over the range of the assay and measured for c-Myc (total). Linear regression analysis of assay results versus the expected concentration yielded a correlation coefficient of 0.99.

Cell lysate

Dilution Measured (pg/mL) Expected (pg/mL) % Expected
1/10 372.3 372.3 100
1/20 205.7 186.14 111
1/40 117.2
93.1 126
1/80 56.0 46.54 120
1/160 25.8 23.3 111
1/320 8.8 11.6 76


Parallelism provides confirmation that natural and recombinant samples are detected in the given ELISA in the same way. The data resulting from the parallelism validation ensures that the given analyte is recognized in a natural sample in a dose- dependent manner similar to the standard curve. 

Below are examples of data generated for parallelism during kit validation. Recombinant standard, rat serum, and rat plasma were serially diluted across the dynamic range of the assay and evaluated using our Growth Hormone ELISA Kit, Rat (Cat. No. KRC5311). The results indicate that the standard diluted in diluent buffer can be used to accurately quantitate sample concentrations in the tested matrices.


Random rat serum and plasma samples were serially diluted in the Standard Diluent Buffer. The optical density of each dilution was pltted against the Rt growth  hormone standard curve. Parellelism was demonstrated by the figure above and indicated that the satndard accurately reflects the Rt growth hormone content in natural samples.


Recovery is used to determine whether analyte detection is affected by differences in sample matrices. Matrices, such as serum and plasma, may have interfering factors that could affect the ability of the ELISA to accurately quantify an analyte.

Recovery is validated by spiking known amounts of analyte into different sample matrices. The assay is run, and recovery is determined. Generally, if average recovery is 80–120%, the sample matrices are considered to have minimal effect on the ability of the assay to accurately quantify the analyte. 

The table to the right is the typical format used for reporting recovery. In this example, our Adiponectin ELISA Kit, Human (Cat. No. KHP0041) was tested for recovery in 5 different plasma samples. 


Sample number Average recovery (%)
1 99.6
2 99.8
3 100.2
4 92.5
5 91.8


Sensitivity is defined as the lowest level of analyte that can be distinguished from background. This is often referred to as analytical sensitivity or limit of detection. Sensitivity is determined by adding 2 standard deviations to the mean O.D. obtained from replicates of the zero standard.

Below is the typical format used for reporting sensitivity. In this example, our Human Tau [pT181] Phospho-ELISA Kit (Cat. No. KHO0631) has a sensitivity of <10 pg/mL. This indicates that each kit lot tested demonstrated sensitivity below 10 pg/mL. 

  • The minimum detectable concentration of Hu Tau [pT181] is <10 pg/mL. This was determined by adding two standard deviations to the mean O.D. obtained when the zero standard was assayed 64 times.



Specificity testing is done to verify that the analyte of interest is detected without cross-reactivity with other closely related molecules. Cross-reactivity can lead to false positive results or inaccurate quantitation. To ensure that only the desired analyte is recognized, a panel of other substances is tested for cross-reactivity.

In this example, specificity of our Mouse IL-6 ELISA Kit (Cat. No. KMC0061) was tested by screening 20 different substances for cross-reactivity. The typical format used for reporting the results is shown below:

Buffered solutions of a panel of substances at 10,000 pg/mL were assayed with the Ms IL-6 kit. The following substances were tested and found to have no cross-reactivity: 
  • Mouse IL-1β, IL-2, IL-4, IL-10, IFN-γ, TNF-α
  • Rat IL-1β, IL-2, IL-4, IL-6, IFN-γ, TNF-α
  • Human IL-2, IL-4, IL-6, IL-10, IL-12, IFN-γ, TNF-α
  • Swine IL-8