HIV drug resistance data are critical for HIV drug resistance surveillance, antiretroviral drug design, and the management of persons infected with drug-resistant HIV. Three fundamental types of correlations form the basis of drug resistance knowledge: (1) Correlations between genotypic data with the treatments of persons from whom sequenced HIV-1 isolates have been obtained (genotype-treatment);(2) Correlations between genotype and in vitro drug susceptibility (genotype-phenotype);and (3) Correlations between genotype and the clinical response to a new treatment regimen (genotype-outcome). Accordingly our three plans are as follows: (1) To use phylogenetically-based statistical analysis of correlations between mutations in the targets of HIV therapy (genotype) and antiretroviral treatment to distinguish between drug- and non-drug- related HIV-1 evolution, to identify temporal and geographic patterns in the prevalence of drug resistance, and to identify the spread of viruses with particular patterns of drug-resistance mutations. (2) To use patterns of mutations in the targets of antiretroviral therapy, antiretroviral treatment data, and in vitro drug susceptibility results to help prioritize the clinical development of experimental antiretroviral compounds. (3) To us correlations between genotype-phenotype and genotype-clinical outcome to identify the treatment regimens most likely to be effective in persons with acquired or transmitted drug resistance. In order to accomplish these aims, we will expand the online publicly available Stanford HIV RT and Protease Sequence Database to represent, store, and analyze the diverse forms of data underlying drug resistance knowledge. Standardized protocols for exchanging data with the broad community of researchers studying HIV-1 drug resistance will be refined and validated. Improved methods for representing published drug resistance data, performing temporal queries and knowledge discovery, and for analyzing genotypic resistance data in a phylogenetic context will be implemented. This proposal is also the start of a three-way collaboration between Stanford University, the University College of London (UCL), and Oxford University. UCL is on the forefront of research into the problem of transmitted drug resistance and Oxford University is on the forefront of research on virus evolution and population genetics.
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