What is the difference between ED50 at inflection point and ED50 at 50%, and how to predict both using 'drc' R-library package? I need to predict ED50 at the inflection point and ED50 at 50%. I am not sure the ED50 (intercept) value calculated by the R library 'drc' is ED50 at the inflection point and ED50 at 50%. Can someone explain what is the difference between both, and how to calculate the other parameter since one of them is predicted by the 'drc' package as default?
I tried to understand the concept from the previous posts in this forum (post1, post2) in vain. Please help.
library(tidyverse)
library(drc)

toxdata<- ryegrass
model<- drm(rootl~conc, data=ryegrass, fct=LL.4(names = c("Slope", "Lower Limit", "Upper Limit", "ED50")))
#you don't need the 'names = ' argument but it's useful to label the b, c, d, and e parameters until you're familiar with
plot(model, type="all")
summary(model)
......................................................
  Model fitted: Log-logistic (ED50 as parameter) (4 parms)
 
  Parameter estimates:

                          Estimate Std. Error t-value   p-value    
  Slope:(Intercept)        2.98222    0.46506  6.4125 2.960e-06 ***
  Lower Limit:(Intercept)  0.48141    0.21219  2.2688   0.03451 *  
  Upper Limit:(Intercept)  7.79296    0.18857 41.3272 < 2.2e-16 ***
  ED50:(Intercept)         3.05795    0.18573 16.4644 4.268e-13 ***
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

  Residual standard error:

   0.5196256 (20 degrees of freedom)
......................................................

ED(model, 50, interval="delta")

......................................................

Estimated effective doses

       Estimate Std. Error   Lower   Upper
e:1:50  3.05795    0.18573 2.67053 3.44538


 A: I can reverse engineer the computation of ED50 in the case of the drc package.
With the code below I recreated the plot from the drc package using the nls function to fit the 4 parameter log-logistic model that the drc package uses. It seems like the package uses as ED50 value the concentration where the estimated effect is 50% of the entire curve.

library(tidyverse)
library(drc)

### DRM stuff

toxdata<- ryegrass
model<- drm(rootl~conc, data=ryegrass, fct=LL.4(names = c("Slope", "Intercept", "ED50")))
plot(model, type="all")
summary(model)

### reverse engineering with nls

### fit the 4 parameter log-logistic model  
mod = nls(rootl ~ c + (d-c)/(1+exp(b*(conc-e))), start = list(b = -1, c = 8, d = 0, e = 1), data = toxdata)

b=coef(mod)[1]  # slope
c=coef(mod)[2]  # lower limit
d=coef(mod)[3]  # upper limit
e=coef(mod)[4]  # 50% level and also inflection point, ED50

### plot data along with fitted model
plot(toxdata$conc,toxdata$rootl, log = "", pch = 20, cex = 0.7)
cs =seq(0,40,0.1)
y = c + (d-c)/(1+exp(b*(cs-e)))
lines(cs,y)

c50 = 3.05795
y50 = c + (d-c)/(1+exp(b*(c50-e)))
points(c50,y50, pch = 21, col = 1, bg = 2)
lines(c(-10,40),c(1,1)*(d+c)/2, lty = 2)


I haven't used ED50 a lot and I had to search for it. According to Wikipedia it is the dose at which a certain effect is appearing in 50% of the population.
An open question is 'what effect' are we talking about. That might relate to the 'inflection point' and the '50%' as definitions of an effect.
In the example above, if we would give a dose with a concentration of 3.05795 then the estimated distribution of the effect in the rye plants would be a normal distribution with a mean rootl around 4.360447 which is the 50% level of the curve. So at a concentration of 3.05795 the median effect will be 4.360447 which is an effect at 50% of the dose-response curve.
Whether you can get the inflection point via drc I am not sure, but it seems to me that in the four parameter logistic function the 50% value and the inflection point are the same because the function is symmetric.

Related to your comment how to get ED90 and your first link (Logistic Regression and Inflection Point). In those cases the modelled variable is a probability for some predifined effect (binomial regression), instead of a numerical response. The use of ED values relate directly to the values of the curve which goes from 0 to 1. Values like ED90 make probably more sense in those cases.
In the case of modelling a numerical value, people also seem to use the term EC50, the 50% effective concentration. The dose where thee effect is at 50% (on average). Possibly that is what you meant by ED50 at 50%.
