SANZ CARRERAS, FERRAN

Departament de Ciències Experimentals i de la Salut
Informática Biomédica

+34 933160540
[email protected]
Dr. Aiguader, 88 08003 Barcelona


Personal profile in our Scientific Output Portal (PPC)  

Biography note

Ferran Sanz is chemical engineer by the Institut Quimic de Sarrià (Barcelona) and BSc and PhD by the Universitat Autònoma de Barcelona. He is Professor of Biostatistics and Biomedical Informatics at the Universitat Pompeu Fabra (UPF, Barcelona) and Director of the IMIM-UPF joint Research Programme on Biomedical Informatics (GRIB). He is also visiting professor at Naples, Düsseldorf and Vienna Universities.

Author of more than 100 articles in ISI-indexed journals. Mentor of 18 PhD thesis. Coordinator of eight EU-funded initiatives, as well as a STOA report for the European Parliament. Currently academic coordinator of the IMI (Innovative Medicines Initiative) project on the in silico prediction of drug toxicity eTOX. Partner in many other EU-funded projects, like the ongoing IMI projectOpenPHACTS and EMIF.

Ferran Sanz is member of the Scientific Committee of the European Innovative Medicines Initiative (IMI) and academic coordinator of the Spanish Technology Platform on Innovative Medicines (PTEMI). Coordinator of the Biomedical Informatics Node of the Spanish Institute of Bioinformatics (INB). Scientific Director of Bioinformatics Barcelona (BIB). Vice-rector for Scientific Policy of the UPF from January 2004 to March 2009, currently delegate of the rector for strategic projects in the biomedical field. President of the European Federation for Medicinal Chemistry (EFMC) from January 2003 to December 2005

Research lines

Computational approaches in drug discovery and development with a particular focus on the prediction of potential adverse drug reactions.

Integrative knowledge management and exploitation in biomedicine, including multi-level and multi-scale modelling and simulation.

Docencia

Research lines

Computational approaches in drug discovery and development with a particular focus on the prediction of potential adverse drug reactions.

Integrative knowledge management and exploitation in biomedicine, including multi-level and multi-scale modelling and simulation.