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Conference Report

Arevir: A Secure Platform for Designing Personalized Antiretroviral Therapies Against HIV

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45310

Roomp,  Kirsten
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44105

Beerenwinkel,  Niko
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45492

Sing,  Tobias
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44197

Büch,  Joachim
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44907

Lengauer,  Thomas
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Citation

Roomp, K., Beerenwinkel, N., Sing, T., Schülter, E., Büch, J., Sierra-Aragon, S., et al. (2006). Arevir: A Secure Platform for Designing Personalized Antiretroviral Therapies Against HIV. In Lecture Notes in Bioinformatics (pp. 185-194).


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-2221-0
Abstract
Despite the availability of antiretroviral combination therapies, success in drug treatment of HIV-infected patients is limited. One reason for therapy failure is the development of drug-resistant genetic variants. In principle, the viral genomic sequence provides resistance information and could thus guide the selection of an optimal drug combination. In practice however, the benefit of this procedure is impaired by (1) the difficulty in inferring the clinically relevant information from the genotype of the virus and (2) the restricted availability of this information. We have developed a secure platform for collaborative research aimed at optimizing anti-HIV therapies, called Arevir. A relational database schema was designed and implemented together with a web-based user interface. Our system provides a basis for monitoring patients, decision-support, and computational analyses. Thus, it merges clinical, diagnostic and bioinformatics efforts to exploit genomic and patient therapy data in clinical practice.