3.8. Summary
This chapter described statistical techniques used in drug discovery to facilitate model building. The techniques are useful for accelerating the pace of moving potential drugs through the development process. Procedures provided in this chapter deal with partitioning relevant data into training and test sets, selecting potential variables to be used to construct the model, building the model, and making predictions.
The model building process described in the chapter is illustrated by using a real drug discovery data set to predict the solubility of various chemical compounds. The SAS code is provided so that the interested reader can use these procedures on their own sets of data.
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