The 4-parameter logistic curve fit is the most common approach. It models a symmetric sigmoidal dose-response correlationship. The 5-parameter logistic fit function adds an asymmetry parameter, which can be useful to account for ceiling or floor-effects. The 3-parameter model is a reduced 4-parameter model, where one of the asymptotes has to be set to a fixed value or to the mean of a control line, which allows the system to deal with truncated data.
PLA 3.0 allows you to carry out the regression for each standard/sample combination in your bioassay separately or at once.
Use this approach for all typical bioassays, such as
- binding assays (for example ELISA),
- enzyme activity assays (for example spectrophotometric, fluorometric or radiometric assay),
- cell based assays (for example cell proliferation, cytotoxicity or cell death assay) or
- cell and gene therapy assays.