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Principal Investigator: ROBERT William SHAFER
Organization: STANFORD UNIVERSITY
Fiscal Year: 2024
Award: $713,086
Funding agency: National Institute of Allergy and Infectious Diseases
PROJECT SUMMARY
HIV drug resistance (HIVDR) is a threat to the success of antiretroviral (ARV) therapy (ART) and a major
barrier to the elimination of AIDS as a public health problem. Persons with HIV who develop virological failure
(VF) during ART are at high risk of developing HIVDR and transmitting a drug-resistant virus to others while
persons primarily infected with a drug-resistant virus are at high risk of developing VF and a further increase
in HIVDR. Comprehensive, accurate, and publicly available HIVDR data are essential for population-based
monitoring of acquired and transmitted HIVDR, for the management of HIV-infected patients, and for
identifying overall drug-development needs. A public database that curates, annotates, synthesizes, and
disseminates data from HIVDR studies will make it possible to identify and characterize the HIVDR mutations
most relevant to surveillance, clinical management, and drug development, and will expedite research into
the mechanisms of HIVDR and the predictors of response to the newest ARV regimens.
The Stanford HIV Drug Resistance Database (HIVDB) provides a unique conceptual framework for
addressing data-intensive questions about the main molecular targets of HIV therapy: reverse transcriptase,
protease, integrase, and capsid. HIVDB’s sequence analysis programs have also become integrated into the
workflows of many research laboratories worldwide. Accomplishing the Aims of this proposal will assist
researchers engaged in HIVDR surveillance, ART clinical trials, and ARV development by enabling them to
identify gaps in the published literature, incorporate contributions from HIVDB into novel analyses, and
discover new knowledge.
Our first Aim will involve expanding HIVDB as a resource that provides the scientific foundations of the clinical
and epidemiological significance of HIVDR mutations and that address gaps in HIVDR knowledge including
the correlates of resistance to recently approved ARVs, established ARVs used for new indications, and the
long-acting ARVs that will be used for prevention and treatment. We will implement strategies to increase
data sharing to help ensure the long-term sustainability of this project.
Our second Aim will involve extending the logic of HIVDB’s genotypic resistance test interpretation program
to predict the virological response to ARV combinations and common ART regimens. We will demonstrate
and promote the use of our sequence analysis software for the analysis of other pathogenic viruses for which
antiviral therapy is available.
Our third Aim will involve converting HIVDB into a fully open source and transferable project. Accomplishing
this aim will support researchers using HIVDB to advance their research by enabling them to seamlessly
integrate HIVDR data into their research. Accomplishing this aim will also foster the long-term sustainability
of the HIVDB project.
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