CMEonHIV.com is dedicated to providing online CME presentations (slides with voiceover) on HIV/AIDS for healthcare professionals given by local and international experts to keep you up-to-date on the ongoing developments in the field.
Conference
"HIV Drug Resistance: Current Status/Future Direction" Dr. Brendan Larder (biography) English - 2003-03-28 - 39 minutes
Summary : Resistance testing has become routine in HIV management, especially for patients who have undergone multiple rounds of drugs. Genotyping is done much more frequently than phenotyping, as there are reasonably priced commercial testing kits available on the market. The caveat of all resistance testing remains though, the interpretation. The rules of interpretation were very simple in the beginning, for example 184V/I equals 3TC resistance, 215Y/F equals AZT resistance and so on. Now however, the mutations for these drug resistances need to be deduced by computer programs because of their complex combinations. These rules/ algorithms have been found, however to be erroneous in predicting phenotype. In the past couple of years, systematic approaches have been developed to predict phenotypes based on complex mutational patterns. The “Virtual Phenotype” is one example, which requires a substantial genotype-phenotype database, and relies on analysis of pre-defined mutational clusters. The “Neural Networks” technique is another one, which is trained with large data sets, learning to connect complex data and identify patterns by being “fed” many examples. The networks can be used to relate resistance mutations to phenotype or clinical response. The HIV Resistance- Response Database Initiative (RDI) has been designed to “..improve the clinical management of HIV infection by developing and making freely accessible a large clinical database and bioinformatic techniques that define with increased precision and reliability the relationships between drug resistance and virologic response to treatment.” The RDI approach involves collecting genotype, clinical and outcome data from large numbers of patients, and using a large number of data analysis methodologies to relate resistance to clinical response. Neural Networks models have been incorporated here, to allow the system to predict viral load change, viral load trajectory (whether the VL goes up, stays the same or goes down), virologic failure, and most interestingly, to predict a patient’s response to various combination drug therapies based on his/ her genotype. The new RDI approach is thus looked upon to improve the accuracy of predicting outcome from genotype.
Learning objectives : The participant will be introduced to the systematic approaches now being used to predict phenotype and clinical response from a patient’s genotype, focusing on the Neural Networks and RDI techniques.
Bibliographic references : HIV resistance to antiretroviral drugs: mechanisms, genotypic and phenotypic resistance testing in clinical practice.
Blaise P, Clevenbergh P, Vaira D, Moutschen M, Dellamonica P.
CHU Liege, Belgium.
HIV resistance to antiretroviral agents is a major contributory cause of treatment failure. The dynamics of HIV replication, together with patient-, physician-, and drug-related factors, lead to emergence of HIV resistant strains in most of the patients. Phenotypic assays look for an increase in the antiretroviral drug (ARV) concentration that inhibits 50% of the growth of the tested HIV strain (IC50), comparatively with a reference strain cultivated in parallel. Genotypic tests detect resistance mutations in the reverse transcriptase and protease genes by comparing the gene sequences of a resistant virus to those of a wild-type strain that has previously been described. The efficacy of each ARV class and each individual ARV is threatened by specific mutations and resistance mechanisms. In retrospective studies of genotypic or phenotypic resistance testing, baseline resistance tests results were correlated with virological outcomes. There is some evidence from prospective studies that resistance testing may have some benefits when used to choose salvage regimens. However, problems in the areas of test interpretation, patient compliance, availability of active drugs, and technical test performance limit the usefulness of resistance testing in clinical practice. This article reviews the mechanisms underlying HIV resistance, the principles of phenotypic and genotypic tests, and the use of these tests in clinical practice.
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