ELISA Intelligence System
A cognitive ELISA analytical platform integrating 4PL/5PL curve fitting, curve reliability scoring, sample validation, assay performance characterisation, sigma metrics, and clinical interpretation narrative.
Input & Computation
Standard Curve
| Conc. | OD Rep 1 | OD Rep 2 | OD Rep 3 | |
|---|---|---|---|---|
Samples
| Label | OD Rep 1 | OD Rep 2 | OD Rep 3 | Dil. | |
|---|---|---|---|---|---|
Plate Layout (optional)
Evidence & References
Engvall E & Perlmann P (1971)
Original ELISA paper. Enzyme-linked immunosorbent assay (ELISA). Quantitative assay of immunoglobulin G. Immunochemistry 8(9):871–874.
Findlay JWA & Dillard RF (2007)
Appropriate calibration curve fitting in ligand binding assays. AAPS J 9(2):E260–E267. Establishes 4PL as the standard model for immunoassays.
CLSI EP17-A2 (2012)
Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures. Defines LLOQ, ULOQ, LoD, and LoB for quantitative assays.
Boulanger B et al. (2003)
An analysis of the ELISA and immunoassay validation parameters. J Pharm Biomed Anal 32(4–5):753–765. Defines acceptance criteria for back-calculated standards (±15%).
Broto M et al. (2019)
New perspectives in immunoassay quality control. Anal Bioanal Chem 411:7503–7514. Sigma metrics application to ELISA assay monitoring.
Sittampalam GS et al. (2004)
Recommendations for the design, optimization, and qualification of cell-based assays used for the detection of neutralizing antibody responses elicited by biological therapeutics. J Immunol Methods 289:1–16.
ECIS v1.0 architecture: 4PL/5PL Levenberg-Marquardt fitting → back-calculation recovery (±15% = PASS, ±20% = FAIL) → sample quantification with dilution correction → LLOQ/ULOQ range checking → replicate CV assessment (Grubbs outlier detection) → sigma metrics integration → interpretive narrative generation.
PM Lab Suite
Clinical Laboratory Intelligence Platform
When to Use
- Evaluating ELISA assay reliability beyond R²
- Validating samples within or outside calibration range
- Characterising assay performance: LLOQ, ULOQ, dynamic range, signal-to-noise
- Applying sigma metrics to ELISA performance assessment
- Generating clinical interpretation narratives for biomarker data
- Teaching ELISA analytical concepts with viva preparation
Common Pitfalls
- Reporting concentrations from extrapolated OD values (outside LLOQ–ULOQ)
- Accepting R² ≥ 0.98 without checking standard back-calculation errors
- Ignoring hook effect at high concentrations
- Using CV% without clinical context of the biomarker
- Failing to correct for dilution factor in sample back-calculation