# HIV viral suppression among women in Malawi before and after switch from efavirenz to dolutegravir: contextualizing viral outcomes with robust resistance and objective adherence measures > **NIH NIH R21** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $157,500 ## Abstract ABSTRACT There are nearly 15 million persons living with HIV on antiretroviral (ARV) treatment in sub-Saharan Africa (SSA). Despite success in scale-up of therapy, many barriers remain to achieving optimal ARV treatment outcomes, including limited access to viral load (VL) monitoring, increasing rates of transmitted and acquired drug resistance, and drug toxicities resulting in treatment discontinuation. In response to these challenges, the World Health Organization recently revised its recommended first-line ARV regimen, retaining the nucleoside reverse- transcriptase (NRTI) backbone but replacing efavirenz (EFV), a non-nucleoside reverse-transcriptase inhibitor (NNRTI), with the more potent, better-tolerated, and more genetically robust integrase strand transfer inhibitor (INSTI) dolutegravir (DTG). Reacting to this change, countries across SSA, including Malawi, are switching all persons currently on an EFV-based regimen to a DTG-based regimen. With limited availability of VL and even more scarce resistance testing, this will be a “blind switch”, without information regarding viral suppression (VL<1000 copies/ml) or drug resistance. Such a strategy may compromise long-term public health benefits of DTG, risking DTG failure or resistance in the setting of poor adherence or inadvertent DTG monotherapy (i.e., no residual NRTI-backbone activity). An ongoing prospective cohort study of ~1400 women in Malawi, ~1000 of whom will be enrolled while on EFV, provides a unique and timely opportunity to evaluate the ARV outcomes, including viral suppression and resistance, before and after switching from EFV to DTG. Therefore, we propose a sub-study to evaluate these outcomes, using existing stored specimens collected from the cohort study. Aim 1 will measure rates of viral suppression before and after switch from EFV to DTG, conducting VL tests on stored blood specimens collected immediately prior to DTG switch and specimens collected approximately 6 months (+/-3 months) after switch to DTG (n=1000). Aim 2 will describe the frequency and patterns of ARV resistance among persons with viral failure at time of switch or 6 months after starting DTG (~10%, n=100) using next generation sequencing on stored blood specimens, with novel techniques to identify and quantify majority and minority variants for NRTI and INSTI resistance. Finally, among women with viral failure on either EFV or DTG- based regimens (~10%, n=100), Aim 3 will evaluate adherence using lamivudine drug concentrations in hair, the NRTI common to both regimens. This will be the first prospective study of HIV outcomes in a real-world EFV-to- DTG switch paradigm contextualized by novel deep sequencing and objective drug exposure (i.e., adherence) data. By embedding our sub-study into an almost completely enrolled cohort study, we will be able to access available stored specimens, quickly conduct analyses, and more expeditiously evaluate public health implications of blindly switching from EFV to ... ## Key facts - **NIH application ID:** 10263158 - **Project number:** 5R21AI152848-02 - **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL - **Principal Investigator:** MINA CHRISTINE HOSSEINIPOUR - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $157,500 - **Award type:** 5 - **Project period:** 2020-09-14 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10263158 ## Citation > US National Institutes of Health, RePORTER application 10263158, HIV viral suppression among women in Malawi before and after switch from efavirenz to dolutegravir: contextualizing viral outcomes with robust resistance and objective adherence measures (5R21AI152848-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10263158. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*