Dosisresponsanalyses

Dosisresponsanalyses refers to the quantitative assessment of how varying doses of a substance produce changes in a biological response. Used across pharmacology, toxicology, environmental health, and epidemiology, these analyses help characterize potency, efficacy, safety margins, and risk. Endpoints can be continuous (e.g., biomarker levels, weight change) or binary (e.g., incidence of an adverse effect).

Common models include the Hill equation for sigmoidal dose–response curves, logistic and probit models for binary outcomes, and linear or nonlinear models for continuous endpoints. The four- or five-parameter logistic models are frequently used; the Hill slope describes curve steepness. Nonlinear mixed effects can account for between-subject variability.

In risk assessment, benchmark-dose (BMD) modeling estimates a dose associated with a predefined response level (e.g., 10% increase) and yields a BMD with a lower confidence limit (BMDL) for uncertainty management. Traditional approaches include the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL), but BMD is increasingly preferred.

Practical steps include data inspection, selecting candidate models, fitting them, checking goodness-of-fit, and comparing models by information criteria or likelihood-ratio tests. Outputs include estimated potency, LOAEL/NOAEL when available, the BMD and BMDL, and confidence intervals. Assumptions, data range coverage, potential confounding, and choice of endpoint influence results.

Software tools such as R packages (drm, drc), PROAST, and BMDS are commonly used. Transparent reporting of model choice, data handling, and uncertainty is essential for interpretability.