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.
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Prediction of Activity for Antimalarial Nanoparticle Delivery Systems
Published: 01 August 2018 by MDPI in MOL2NET'18, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 4th ed. congress NANOBIOMAT-04: Nanotechnology & Biomaterials Sci. Congress, Jackson & Fargo, USA, 2018
Keywords: nanotechnology, machine learning