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Tools / Statistical analysis / Dose-Response 4PL
Statistical analysis

Dose-Response 4PL

4PL dose-response fitting with R (webR) in your browser: IC50 / EC50, Hill slope, R², residuals and curve quality checks.

Fit a dose–response curve and estimate EC50

Data

16 points

Sample: R datasets::DNase, run 1 (ELISA; Davidian & Giltinan, 1995)

Options

Results

The fit appears here once there are at least five positive doses.

The R engine loads when you start entering data (downloaded once)

Guide and FAQ

Running ELISA or ligand-binding standard curves for QC or CRO work? Check residuals and curve fit here first; for membrane spot assays, see the in-browser Dot Blot analyzer.

Plate-reader ODs are back-calculated in the ELISA standard-curve tool.

What Is a 4PL Dose-Response Fit?

A four-parameter logistic curve is commonly used when a response changes sigmoidally across concentration or dose. It estimates the lower plateau, upper plateau, midpoint, and Hill slope from the observed data.

Y = Bottom + (Top - Bottom) / (1 + 10((logDose - logIC50) × HillSlope))

When to Use It

  • Drug response: estimate IC50 from viability or inhibition curves.
  • Receptor or reporter assays: estimate EC50 from increasing signal curves.
  • ELISA and standard curves: fit sigmoid calibration data before interpolation.

Computed by R in Your Browser

The fit is computed by R (webR) in your browser with nls and SSfpl, and comes with code you can rerun in desktop R. Input, fitting, charts and CSV export stay in the browser; the data are not sent to a server.

Fit Quality Checklist

  • Cover at least 1.5 to 2 log10 units of dose range whenever possible.
  • Include points near both plateaus and around the transition region.
  • Inspect residuals and warnings before reporting IC50 or EC50.
  • A high R² does not replace biological or assay-specific judgement.

Version history

Version history for all tools is listed in the Chronicle.

View tool updates