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| The target. A micrograph of the human immunodeficiency virus. |
New data concerning HIV drug resistance were presented by Virco Group, a Mechelen (Belgium) biotechnology company, at the 5th International Congress on Drug Therapy in HIV Infection. The findings remove some ambiguity in the interpretation of resistance results from treated patients.
Viral mutation occurs readily during HIV replication such that mutants resistant to a particular drug therapy may quickly become the dominant strain. This fact is a significant cause of treatment failure. Therefore, to provide effective medical care, it is essential that a doctor monitor a patients virus for drug resistance. The question is, how does a physician know what actually signifies that drug resistance is taking place?
The phenotypic approach to this question involves actually measuring the amount of a particular drug required to decrease viral replication by 50%the IC50 value. A ratio is determined between this value and the IC50 for a nonmutated (wild-type) virus. To decide whether resistance is taking place, a nonresistance upper limit for the IC50 ratio must be designated. The usefulness of this method strongly depends on the pertinence of this cutoff value to what is actually happening in the body. Scientists at Virco have established the first drug-specific, biologically relevant drug resistance cutoff values. They accomplished this by determining, for 14 different HIV drugs, the average IC50 ratio for 1000 untreated patients and several thousand wild-type samples. The cutoff for each drug was set at two standard deviations above the corresponding average.
Until this announcement, cutoff values were typically based on the variability of a repetitive assay of a single nonmutated standard. The value obtained was used for all of the available drugs. According to Virco, this method is somewhat arbitrary because it does not reflect natural variation in the population and in drug response. Doctors caring for HIV patients will now be able to make more-informed treatment decisions.
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