This question cannot be answered by just looking at min/max values. What is the distribution of data points? Ideally there would be (usually) a lot of inactive values, and a some actives offset by a few log steps (depending on the screen design, obviously). Also, consider what is known about, for example, the targeted receptor (if there is one) and its binding characteristics, the analysis of related screens (same cell lines and different compounds, or related cells and same compound set...), etc. You definitely should look beyond the pure mathematics of your single data set.

Some things worth considering:

1. express your IC50 values in M rather than mM as they seem to have a very wide range.
2. do you have a confidence interval for the IC50 values? If so this would be important. It depends on the assay but usually we think of IC50s in terms of log differences. So a drug with and IC50 of 10^-7M would be 'better' than a drug of -10^-6M. If the differences are half log or less than we don't consider the difference to be that dramatic.
3. the range of the data worth considering. Do the different drugs have values of say 5 logs or just a very small range?
4. How related are the chemical structures and how are you going to classify these? E.g. addition of a single carbon can change an IC50 significantly.

I don't know if this is sufficient to count as an answer but perhaps it helps a bit.

Does it make sense?