Why Cayman Assay Kits | Cayman Chemical
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​​Why Cayman Assay Kits?

2017-08-24

Cayman offers hundreds of immunoassay, cell-based assay, and enzyme activity assay kits in a variety of formats to monitor biomarkers, assess cellular health, and measure enzyme activity/inhibition. We have an exceptional understanding of assay development, validation, and performance, and value the importance of integrity in scientific research. Our key advantage is that the scientists who directly develop our products are also readily available to provide technical support or custom assay design and optimization. Each of our assay kits undergoes rigorous quality testing to certify high precision and accuracy to deliver the sensitivity and specificity needed to detect biologically significant analyte levels. Our attention to these details ensures you will obtain reproducible results, from day to day and batch to ​batch. Because the success of your work is integral to ours, Cayman’s mission is to help make research possible by supplying assay kits that produce results you can trust.

When selecting a kit among manufacturers, researchers often face the challenge of “apples-to-oranges” comparison of sample compatibility, sensitivity, etc. Below, we have defined how Cayman kits compare to other manufacturers, using common industry terms to describe the performance of an assay.

Sensitivity Defined

Because not all assay companies define their sensitivity similarly, we point out the intended definitions of the particular points of quantitation on the typical standard curves generated by Cayman’s competitive assay, sandwich ELISA, and activity/inhibitor screening assay kits.

Competitive ELISA Standard Curve Quantitation

  • Cayman’s Sensitivity – is defined as the 80% B/B0* point on the curve. 80% binding is the minimum level where reliable, reproducible data can be obtained and represents the minimal functional sensitivity outside of the range of statistical bias.

versus

  • Competitor Sensitivity – is typically defined by the Lower Limit of Detection (LLOD), which is usually considered the mean zero plus two standard deviations (S.D.). While this is the lowest level of analyte detected by the kit, this range is typically not reliable nor reproducible and may reside at a concentration below the linear range of assay. This value typically lies below an assay’s functional sensitivity range.

Cayman provides researchers with both the 80% B/B0 value and the LLOD along with the assay’s high-low range and 50% B/B0 mid-point (the direct center of the most reliable portion of the curve) to further qualify the ELISA’s robustness.

*%B/B0 - (%Bound/Maximum Bound): ratio of the absorbance of a particular sample or standard well to that of the maximum binding (B0) well.

Sample Competitive ELISA Standard Curve

Sample Competitive ELISA Standard Curve 2017AUG.jpg

*Please note above data is example data only and do​es not represent a specific kit.


ASSAY RANGE: The range between the highest standard and the lowest standard.

SENSITIVITY: The lowest level of reliable quantification. For competitive ELISAs, this is defined as the 80% B/B0. 80% binding is the minimum level where reliable, reproducible data can be obtained.

MID-POINT: The middle point (50% B/B0) of the standard curve.

LOWER LIMIT OF DETECTION: The smallest measure that can be detected with reasonable certainty for a given analytical procedure. The LLOD is defined as a point two standard deviations greater than the mean zero value.


Immunometric (Sandwich) ELISA Standard Curve Quantitation

  • Cayman’s Sensitivity – is defined as the Lower Limit of Quantification (LLOQ). LLOQ is the minimum level where reliable, reproducible data can be obtained. It is demarcated by a set goal for bias and precision: the lowest standard concentration in which optical density (O.D.) of the sample minus (1.64 x S.D.) is higher than the blank value of O.D. plus (1.64 x S.D.).

versus

  • Competitor Sensitivity – many immunoassay suppliers define the sensitivity of their assays with the LLOD, the lowest level of analyte detected by the assay. Typically, LLOQ will be found at a higher concentration than LLOD, but how much higher is dependent on the LLOQ-defined specifications for bias and imprecision.

Cayman provides researchers with both the LLOQ value and the LLOD along with the assay’s high-low range to further qualify the ELISA’s sensitivity.

Sample Sandwich ELISA Standard Curve

Sample Sandwich ELISA Standard Curve 2017AUG.jpg

*Please note​​ above data is example data only and does not represent a specific kit.


ASSAY RANGE: The range between the highest standard and the lowest standard.

SENSITIVITY (LLOQ): The lowest level of reliable quantitation is defined as the lower limit of quantification (LLOQ). LLOQ is the lowest standard concentration in which O.D. - (1.64 x S.D.) is higher than the blank value of O.D. + (1.64 x S.D.).

LOWER LIMIT OF DETECTION: The smallest measure that can be detected with reasonable certainty for a given analytical procedure. The LLOD is defined as a point two standard deviations greater than the mean zero value.


Inhibition Curve ​Quantitation

With activity or inhibitor screening assays, the mid-point (IC50) value is reported. This is defined as 50% of the maximum inhibitory concentration, or stated plainly, the concentration of an inhibitor that elicits a 50% reduction in response (signal) or binding. The solvent (vehicle or “Veh.”, as noted on the below graph) in which the inhibitor of interest is dissolved represents 0% inhibition.

Sample Inhibition Curve

Sample Inhibition Curve 2017AUG.jpg

*Please note above data is example data only and does not represent a specific kit.

Additional M​​easure of Robustness

Cayman includes a Z-factor analysis (Z′) with inhibition assays as an indicator of assay performance. An assay with a Z′ factor >0.5 is indicative of excellent assay performance.

The Z-factor is defined in terms of four parameters: the means (µ) and standard deviations (σ) of both the positive (p) and negative (n) controls (µp, σp and µn, σn) using the equation:

Additional Measure of Robustness Equation 2017AUG.jpg

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