The object of this thesis concerns the development of a system to predict drugs side effects, starting from molecule chemical structure. This is a particularly important problem in the development of new drugs. The molecules can be examined with computational methods before being tested in clinical trials, in order to avoid unnecessary additional costs and risks to the participants health. To collect the data needed for the study, I made use of the SIDER and PubChem public databases. The first contains information on the drugs on the market and the related adverse reactions recorded. The information is extracted from public documents and package inserts. Pubchem, on the other hand, is an open chemical database of the National Institutes of Health (NIH). This has become a key resource of chemical information for scientists, students and the general public. Finally, the developed program uses Machine Learning techniques, and, in particular, exploits the Multilayer Perceptron Artificial Neural Network.
Graduation thesis written in italian
I dedicate this study to Wally - Luigi - who, at the time of writing this thesis, is in serious health conditions. And to his family, Emma, Edoardo and Eleonora. They have always shown so much strength, typical of few people.