An update to the HIV-TRePS system: the development of new computational models that do not require a genotype to predict HIV treatment outcomes | Zendy

Andrew Revell | Zendy; D. Wang | Zendy; Robin Wood | Zendy; Carl Morrow | Zendy; H. Tempelman | Zendy; Raph L Hamers | Zendy; Gerardo AlvarezUria | Zendy; Adrian StreinuCercel | Zendy; Luminiţa Ene | Zendy; Annemarie M. J. Wensing | Zendy; Peter Reiss | Zendy; A.I. van Sighem | Zendy; Mark Nelson | Zendy; Sean Emery | Zendy; Julio Montaner | Zendy; H. Clifford Lane | Zendy; B. A. Larder | Zendy; Ard van Sighem | Zendy; Richard Harrigan | Zendy; Tobias Rinke de Wit | Zendy; Kim Sigaloff | Zendy; Brian K. Agan | Zendy; Vincent C. Marconi | Zendy; Scott A. Wegner | Zendy; Wataru Sugiura | Zendy; Maurizio Zazzi | Zendy; José M. Gatell | Zendy; Elisa de Lazzari | Zendy; Brian Gazzard | Zendy; Anton Pozniak | Zendy; Sundhiya Mandalia | Zendy; Lidia Ruíz | Zendy; B. Clotet | Zendy; Schlomo Staszewski | Zendy; Carlo Torti | Zendy; C. Lane | Zendy; Julia A. Metcalf | Zendy; María Jesús PérezElías | Zendy; Andrew Carr | Zendy; R. P. Norris | Zendy; Kathleen Hesse | Zendy; Emanuel Vlahakis | Zendy; Roos E. Barth | Zendy; Gordana Dragović | Zendy; D. James Cooper | Zendy; John D. Baxter | Zendy; Laura Monno | Zendy; Gastón Picchio | Zendy; Marie-Pierre deBethune | Zendy

Open Access

An update to the HIV-TRePS system: the development of new computational models that do not require a genotype to predict HIV treatment outcomes

Author(s) -

Andrew Revell,

D. Wang,

Robin Wood,

Carl Morrow,

H. Tempelman,

Raph L Hamers,

Gerardo AlvarezUria,

Adrian StreinuCercel,

Luminiţa Ene,

Annemarie M. J. Wensing,

Peter Reiss,

A.I. van Sighem,

Mark Nelson,

Sean Emery,

Julio Montaner,

H. Clifford Lane,

B. A. Larder,

Ard van Sighem,

Richard Harrigan,

Tobias Rinke de Wit,

Kim Sigaloff,

Brian K. Agan,

Vincent C. Marconi,

Scott A. Wegner,

Wataru Sugiura,

Maurizio Zazzi,

José M. Gatell,

Elisa de Lazzari,

Brian Gazzard,

Anton Pozniak,

Sundhiya Mandalia,

Lidia Ruíz,

B. Clotet,

Schlomo Staszewski,

Carlo Torti,

C. Lane,

Julia A. Metcalf,

María Jesús PérezElías,

Andrew Carr,

R. P. Norris,

Kathleen Hesse,

Emanuel Vlahakis,

Roos E. Barth,

Gordana Dragović,

D. James Cooper,

John D. Baxter,

Laura Monno,

Gastón Picchio,

Marie-Pierre deBethune

Publication year - 2013

Publication title -

journal of antimicrobial chemotherapy

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.124

H-Index - 194

eISSN - 1460-2091

pISSN - 0305-7453

DOI - 10.1093/jac/dkt447

Subject(s) - human immunodeficiency virus (hiv) , genotyping , antiretroviral therapy , genotype , selection (genetic algorithm) , medicine , drug development , lentivirus , intensive care medicine , viral load , computational biology , biology , computer science , virology , viral disease , drug , machine learning , pharmacology , genetics , gene

The optimal individualized selection of antiretroviral drugs in resource-limited settings is challenging because of the limited availability of drugs and genotyping. Here we describe the development of the latest computational models to predict the response to combination antiretroviral therapy without a genotype, for potential use in such settings.

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