Stanford University HIV Drug Resistance Database - A curated public database designed to represent, store, and analyze the divergent forms of data underlying HIV drug resistance.

Background and Rationale

Last updated on 9/99
 

Database Background

  • Recent clinical trials have shown that HIV-1 replication can be dramatically curtailed, if not completely arrested, with potent, rationally designed drug combinations.
  • The benefits of combination therapy, however, are greatly diminished in patients who have received previous anti-HIV therapy.
  • Although 15 drugs have been approved by the United States FDA (6 nucleoside analog RT inhibitors, 6 protease inhibitors, and 3 nonnucleoside analog RT inhibitors), there is considerable cross-resistance within each class of inhibitors.
  • Several new anti-HIV drugs may be approved by the FDA within the next few years, but preliminary data suggests that many of the current drug-resistant HIV-1 isolates will also be resistant to these new drugs.
  • Despite the availability of many anti-HIV drugs, it has become increasingly difficult to effectively treat patients who fail an initial combination therapy regimen or who are infected primarily with drug resistant strains.

Rationale

  • Therefore, it is urgent to study whether patients developing drug-resistant HIV-1 isolates during treatment with one anti-HIV regimen can have a prolonged response to treatments with different anti-HIV drugs or drug combinations.

  • HIV-1 RT and protease sequences of clinical HIV-1 strains reflect experiments of nature, which if collected and interpreted appropriately can provide insight into HIV-1 drug resistance.
  • However, only a small proportion of HIV-1 RT and protease sequences are publicly available and there is no standard mechanism for relating these sequences to other forms of data (e.g. drug treatment history, in vitro drug susceptibility, and clinical outcome).
  • A database linking HIV-1 RT and protease sequence data, drug treatment histories, drug susceptibility, and clinical parameters will allow researchers to assess the extent of clinical cross-resistance among current and experimental anti-HIV drugs. At the same time, drug regimens that do retain long-term effectiveness against particular drug-resistant HIV-1 isolates may be identified.