Analyze chemical response data with flexible concentration inputs. Find midpoint activity using interpolation and modeling. Create clean reports, graphs, and exports for laboratory review.
This form uses a 3-column layout on large screens, 2 columns on smaller screens, and 1 column on mobile screens.
This sample set represents a typical rising dose-response experiment. It can be pasted directly into the calculator form.
| Concentration (uM) | Observed Response (%) |
|---|---|
| 0.10 | 4 |
| 0.30 | 15 |
| 1.00 | 38 |
| 3.00 | 64 |
| 10.00 | 86 |
| 30.00 | 97 |
Stimulatory mode: Effect % = ((Response - Bottom) / (Top - Bottom)) × 100
Inhibitory mode: Effect % = ((Top - Response) / (Top - Bottom)) × 100
When the measured effect crosses 50%, the calculator estimates EC50 between two neighboring points. If both concentrations are positive, log-linear interpolation is used for better dose-response behavior.
Effect % = 100 × (C^h / (EC50^h + C^h))
Here, C is concentration and h is the Hill slope. The calculator estimates h by linear regression after transforming the dose-response curve.
pEC50 = -log10(EC50 in molar units)
EC50 is the concentration that produces half of the maximal modeled effect. It is widely used to compare compound potency in chemistry, pharmacology, and bioassay work.
It first normalizes the response range, then looks for the 50% effect region in measured data. It also estimates a Hill model and reports both interpolation and model-based results when possible.
pEC50 is the negative base-10 logarithm of EC50 after converting concentration into molar units. Larger pEC50 values indicate stronger potency because less material is needed to reach half-maximal effect.
No. Log-spaced concentrations are common for dose-response work because they define the transition region more clearly. The calculator sorts the data automatically before interpolation and plotting.
Yes. Choose inhibitory mode when response decreases as concentration rises. The calculator reverses the normalization so 50% effect still represents the midpoint between top and bottom responses.
Interpolation uses only the local region around 50% effect. The model uses multiple eligible points to estimate a full curve. Sparse data, noise, or poor top and bottom settings can cause differences.
The interpolation result may be unavailable because no measured pair brackets 50%. In that case, the calculator can still estimate a model-based EC50 if enough valid transformed points remain.
They let you lock normalization to control values instead of observed extremes. This is helpful when your experiment does not fully reach the assay floor or ceiling within the tested range.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.