Drybench Assay.
ELISA standard curve: interpolate unknown samples
Fit ELISA standards with a linear or four-parameter curve, read unknowns back with their dilution, and see which fall outside the standards.
Fit your standards, read each unknown back from its mean response, multiply by its pre-assay dilution, and see which samples fall outside the standards: those are flagged, never extrapolated. The curve is linear or a four-parameter logistic, the one your kit's protocol specifies; the app does not choose.
Open Standard curve in the appIn the app, choose Standard curve in the Analysis menu, paste your readings, and pick the kit or protocol.
Worked example: a rising four-parameter curve
Nine synthetic standards from 0.01 to 100 concentration units with a fixed noise vector, and five unknowns, two of them beyond the standards. Fitted when this page is built by the same engine the app uses, and checked against SciPy on the published fixture.
Four-parameter logistic; tested standard range 0.01 to 100 ng/mL.
| Sample | Mean response | Interpolated (ng/mL) | Original sample (ng/mL) | Status |
|---|---|---|---|---|
| unknown-0 | 0.4 | 0.3874 | 0.3874 | Interpolated |
| unknown-1 | 1.1 | 1.574 | 3.148 | Interpolated |
| unknown-2 | 1.8 | 4.69 | 46.9 | Interpolated |
| out-of-range-0 | 0.07504 | – | – | Below tested range |
| out-of-range-1 | 2.388 | – | – | Above tested range |
ELISA: the result is in the units of the kit's own standard. Immunoassay standard curves are often sigmoidal; choose the model the kit's protocol specifies. The working range is the kit's, from its manual; none is assumed here, and unknowns outside the standards are not extrapolated.
Method
- Standard-curve interpolation. NIST/SEMATECH e-Handbook §2.3.6.6, inverse calibration; Cox et al., Assay Guidance Manual, Immunoassay Methods (2019), calibration and recovery. Linear least squares or the existing 4PL; mean responses per concentration; bounded interpolation. From A5 the 5PL and inverse-prediction intervals are their own methods (five-pl-calibration, calibration-inverse-prediction).Checked against exact rational least squares (linear, 7 cases) and SciPy 1.13.1 (4PL, 2 cases); out-of-range unknowns flagged (10 October 2026). R not run on the 4PL cases.
- Four-parameter logistic fit. Hill AV. J Physiol 1910;40:iv-vii (the logistic form); Ritz C, Baty F, Streibig JC, Gerhard D. Dose-response analysis using R. PLoS ONE 2015;10:e0146021 (the LL.4 parameterisation the fixtures map to).Version 2 unweighted estimates and intervals are checked against the compatible R fixtures. Historical relative-loss and reporting-policy fixtures are archival, not validation of IRLS or the permutation gate.
- Bounded Levenberg-Marquardt with an analytic Jacobian and deterministic starts. Levenberg K. Q Appl Math 1944;2:164-168; Marquardt DW. J Soc Indust Appl Math 1963;11:431-441 (original papers).Version 2 unweighted estimates and intervals are checked against the compatible R fixtures. Historical relative-loss and reporting-policy fixtures are archival, not validation of IRLS or the permutation gate.
Limits
- For research and education only, and not medical advice: a C50 estimated here describes this assay under these conditions and is not a binding constant.