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Personalized HIV Therapy to Control Drug Resistance

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

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons98170

Pfeifer,  Nico
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Citation

Lengauer, T., Pfeifer, N., & Kaiser, R. (2014). Personalized HIV Therapy to Control Drug Resistance. Drug Discovery Today: Technologies, 11, 57-64. doi:10.1016/j.ddtec.2014.02.004.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0024-8FDD-0
Abstract
The therapy of HIV patients is characterized by both the high genomic diversity of the virus population harbored by the patient and a substantial volume of therapy options. The virus population is unique for each patient and time point. The large number of therapy options makes it difficult to select an optimal or near optimal therapy, especially with therapy-experienced patients. In the past decade, computer-based support for therapy selection, which assesses the level of viral resistance against drugs has become a mainstay for HIV patients. We discuss the properties of available systems and the perspectives of the field.