Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping. Objective: The evaluation as a potential treatment support tool of computational models that predict response to thera...

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Bibliographic Details
Main Authors: Andrew Revell, Paul Khabo, Lotty Ledwaba, Sean Emery, Dechao Wang, Robin Wood, Carl Morrow, Hugo Tempelman, Raph L. Hamers, Peter Reiss, Ard van Sighem, Anton Pozniak, Julio Montaner, H. Clifford Lane, Brendan Larder
Format: Article
Language:English
Published: AOSIS 2016-06-01
Series:Southern African Journal of HIV Medicine
Subjects:
HIV therapy
mathematical modelling
treatment
genotype
Online Access:https://sajhivmed.org.za/index.php/hivmed/article/view/450

Internet

https://sajhivmed.org.za/index.php/hivmed/article/view/450

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