The activities of research and development are aimed at creating the knowledge necessary and sufficient to produce, market and sell innovative medicines. Therefore the objective of the Informatics and Knowledge Management at NIBR (IK@N ) team is to provide the right knowledge to the right people at the right time, enabling them to make the right decisions by:

• Establishing new technologies and approaches in data, information and knowledge management.
• Developing novel approaches in scientific computing in support of the drug discovery process.
• Integrating relevant information from internal and external sources in support of NIBR's new research strategy and the drug discovery process.

In order to provide comprehensive, reliable data and information, set in context, with "one-touch" access – in short, to turn data into knowledge via in silico science – we are focusing our activities on these strategic themes:

• Consistent data, information and knowledge management.
• Information integrating for seamless and easy navigation.
• Modeling and simulation of biomolecular processes as well as data mining, analysis and visualization.
• Enabling knowledge sharing among disseminated teams using e-collaboration tools.
• Licensing and provision of external scientific, medical and technical literature to Novartis worldwide.
• Providing support for a reliable computing environment

About 200 employees work for IK@N on all the different NIBR sites. Manuel Peitsch is the head of IK@N.

Rozanov M, Plikat U, Chappey C, Kochergin A, Tatusova T. (2004) A web-based genotyping resource for viral sequences. Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W654-9.
 

Hiroyuki Takashima, Norio Mimura, Tadayasu Ohkubo, Takuya Yoshida, Haruhiko Tamaoki, and Yuji Kobayashi (2004) Distributed Computing and NMR Constraint-Based High-Resolution Structure Determination: Applied for Bioactive Peptide Endothelin-1 To Determine C-Terminal Folding. J. Am. Chem. Soc 126:4504-4505.
 

Peitsch MC, Morris GE, Basse-Welker J, Cartwright G, Juterbock D, Marti KO, Lorban S, Odell G and Vachon T (2004) Informatics and Knowledge Management at the Novartis Institutes for BioMedical Research. SCIP-online 46:1-4.
 

Schwede T, Guex N, Kopp J and Peitsch MC (2003) SWISS MODEL - an automated protein homology-modeling server. Nucleic Acids Research 31: 3381-3385. PMID: 12824332
 

Peitsch MC, Schwede T, Diemand A and Guex N (2003) Protein homology modelling. in: The Encyclopaedia of the Human Genome, DN. Cooper and A. Lockyer. eds., Nature publishing Group.
 

Kelly, Bergmann, et al. (2003). Progressive age-related impairment of cognitive behaviour in APP 23 transgenic mice. Neurobiology of Aging, Experimental and Clinical Research 24: 365-
 

Anthony E. Klon, Meir Glick, Mathis Thoma, Pierre Acklin, and John W. Davies (2003, in press). Improving the Enrichment of High-Throughput Docking Results Using Machine Learning. Journal of Medicinal Chemistry.
 

P. Ertl (2003), Cheminformatics Analysis of Organic Substituents: Identification of the Most Common Substituents, Calculation of Substituent Properties, and Automatic Identification of Drug-like Bioisosteric Groups. J. Chem. Inf. Comput. Sci. 43, 374-380.
 

P. Ertl and P. Selzer (2003).Web-based calculation of molecular properties, in Handbook of Cheminformatics, Ed. by J. Gasteiger, Wiley-VCH, Weinheim, 1336 - 1348.