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HIV Drug Resistance Database, also known as Stanford HIV RT and Protease Sequence Database, is a database at Stanford University that tracks 93 common mutations of HIV.It has been recompiled in 2008 listing 93 common mutations, after its initial mutation compilation in 2007 of 80 mutations.
HIV-1 is the most common and most pathogenic strain of the virus. As of 2022, approximately 1.3 million such infections occur annually. [4] [5] Scientists divide HIV-1 into a major group (group M) and two or more minor groups, namely groups N, O and possibly a group P.
The Stanford HIV RT and Protease Sequence Database (also called the “HIV Drug Resistance Database”) was formed in 1998 with HIV reverse transcriptase and protease sequences from persons with well-characterized antiretroviral treatment histories, and is publicly available to query resistance mutations and genotype-treatment, genotype ...
HIV drug resistance poses an issue because it reduces the possible HIV medications a person can take due to cross resistance. In cross resistance, an entire class of medication is considered ineffective in lowering a patient's HIV viral load because all the drugs in a given class share the same mechanism of action. [7]
The genome and proteins of HIV (human immunodeficiency virus) have been the subject of extensive research since the discovery of the virus in 1983. [1] [2] "In the search for the causative agent, it was initially believed that the virus was a form of the Human T-cell leukemia virus (HTLV), which was known at the time to affect the human immune system and cause certain leukemias.
HIV Resistance Response Database Initiative (RDI) was formed in 2002 to use artificial intelligence (AI) to predict how patients will respond to HIV drugs using data from more 250,000 patients from around 50 countries around the world. The RDI used its models to power its HIV Treatment Response Prediction System (HIV-TRePS).
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