Applications of "Dose Response" Outside of Biostatistics? I was reading about a class of models called "Dose Response Models" (https://cran.r-project.org/web/packages/drda/vignettes/drda.pdf) - in the traditional sense, these are typically used to model the statistical impact and magnitude of some treatment administered on groups of patients.
By doing a quick search on the internet, (naturally) most of the results involving applications of "Dose Response Models" generally concern themselves with estimating the impact of different drug therapies in clinical trials. However, I had the following question:

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*Mathematically, is there anything preventing "Dose Response Models" to be used outside the  their typical use cases in the domain of biostatistics and clinical trials? For instance, could a bank use "Dose Response Methodology" to estimate the long-term impact of setting different interest rates on bankruptcy of their borrowers - or is there something inherently preventing these models from being used outside of their typical use cases in clinical trials?

A major class of what you might consider "dose-response models" has roots going back to the mid 19th-century.
The 4-parameter logistic curve described in the package you cite for dose-response analysis is equivalent to the first curve described as "logistic", a term coined by P.-F. Verhulst in an 1844 presentation published as "Recherches mathématiques sur la loi d'accroissement de la population," NOUVEAUX MÉMOIRES DE L'ACADÉMIE ROYALE DES SCIENCES ET BELLES-LETTRES DE BRUXELLES, vol. 18. As the title indicates, he was examining theories of population growth.
On page 8, just before he introduces the term, he shows an equation for a 4-parameter logistic curve: effectively, one each for the lower and upper asymptotes, one for the x-axis value at the midpoint between them, and one for the steepness (although his parameterization was different).
So methods for fitting such "dose-response" curves are applicable to any "logistic" growth or decay phenomenon.
