Applying experiment-design and support-vector-machines methods to new medicines preproduction

In the traditional process of new-medicines' preproduction, designing experiment schemes and analyzing data was usually manipulated artificially. It was too subjective. Aiming at these situations, a new-medicines' preproduction system was presented, which was based on experiment-design and support-vector-machines methods. First, experiment-design method was introduced in order to gain scientific and logical experiment schemes. Then, support-vector-machines (SVM) method was adopted to establish regress models for those experimental data, which is an analyzing and modeling tool suiting small sample data. These models were used for predicting the experiments' results and optimizing the schemes. In addition, an alternant optimizing method based on greedy search was introduced too. Finally, an example was given to validate that the whole set of methods was scientific and effective.