If I understand correctly, you need to fit Logistic-2P, because the asymptote is known.
In that case, you need to normalize your data, such that Y is between 0 and 1. In your case, I guess that you should divided your Y by 100.
After that, the Logistic-2P will be available:
![peng_liu_1-1715568564067.png peng_liu_1-1715568564067.png](https://community.jmp.com/t5/image/serverpage/image-id/64133i7A278C9A2059FC3A/image-size/medium?v=v2&px=400)
Scaling your data should not impact the other two parameter estimates, i.e. the remaining two estimates are same. Unless you want to do some kind of prediction of Y given "cp", then your need to scale back after prediction using the fitted model.