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Bioinformatics Vol. 19 Suppl. 1 2003
Pages i16-i25
© 2003 Oxford University Press

Methods for optimizing antiviral combination therapies

Niko Beerenwinkel 1,*, Thomas Lengauer 1, Martin Däumer 2, Rolf Kaiser 2, Hauke Walter 3, Klaus Korn 3, Daniel Hoffmann 4 and Joachim Selbig 5

1 Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany
2 Institute of Virology, University of Cologne, Fürst-Pückler-Str. 56, 50935 Köln, Germany
3 Institute of Clinical and Molecular Virology, German National Reference Center for Retroviruses, University of Erlangen–Nürnberg, Schloßgarten 4, 91054 Erlangen, Germany
4 Center of Advanced European Studies and Research, Friedensplatz 16, 53111 Bonn, Germany
5 Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany

Received on January 6, 2003 ; accepted on February 20, 2003

Motivation: Despite some progress with antiretroviral combination therapies, therapeutic success in the management of HIV-infected patients is limited. The evolution of drug-resistant genetic variants in response to therapy plays a key role in treatment failure and finding a new potent drug combination after therapy failure is considered challenging.

Results: To estimate the activity of a drug combination against a particular viral strain, we develop a scoring function whose independent variables describe a set of antiviral agents and viral DNA sequences coding for the molecular targets of the respective drugs. The construction of this activity score involves (1) predicting phenotypic drug resistance from genotypes for each drug individually, (2) probabilistic modeling of predicted resistance values and integration into a score for drug combinations, and (3) searching through the mutational neighborhood of the considered strain in order to estimate activity on nearby mutants. For a clinical data set, we determine the optimal search depth and show that the scoring scheme is predictive of therapeutic outcome. Properties of the activity score and applications are discussed.

Contact: beerenwinkel{at}mpi-sb.mpg.de

Keywords: HIV, antiretroviral therapy, drug resistance, SVM regression, therapy optimization, sequence space search.

* To whom correspondence should be addressed.


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