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Prediction of Activity for Antimalarial Nanoparticle Delivery Systems
1  Bachelor's Degree Nanotechnology - Universidad de Guadalajara


For the development of the project different activities were carried out, starting with the analysis of databases downloaded from ChEMBL. These databases collect information on thousands of drugs that are used to treat several diseases. In this case, we used bases related to Plasmodium which causes malaria in humans. Additionally, a compilation of information on multiple nanoparticles was analyzed. Finally, with help of Excel application and a statistical package named STATISTICA, we found a computational model that can help us to select more effective drug-nanoparticles pairs instead of wasting resources and time creating many samples.

Keywords: nanotechnology, machine learning