LAUSR

The fight against a Human Immunodeficiency Virus (HIV) pandemic is progressively advancing towards the ambitious 90-90-90 goal: to diagnose HIV infection in 90% of infected subjects, provide treatment to 90% of those and, finally, achieving viral suppression in 90% of treated patients. On this path towards eradication, strong epidemiologic surveillance mechanisms have warned of an increase in HIV resistance to the common antiretroviral treatments (ART), which affects more than 10% of the infected population in lowand middleincome countries (LMICs) [1]. Updated guidelines recommend changing one of the three drugs that usually conform ART, for Dolutegravir (DTG) [2]. However, DTG efficacy may also be at stake when a patient’s virus is already resistant to the ART drug backbone, and represents a possible source of future resistant DTG that undermines efficacy of integrase inhibitors drugs. Clinically, HIV resistance is managed differently in LMICs compared to high-income countries. In LMICs, ARTs are designed according to a public health approach that is not guided by viral genetic information but by patient clinical course. Conversely, in richer countries, a Sanger-based genetic test is performed on every patient’s viral genome, inferring drug resistance from genotypic information and taking advantage of the large genotypic to phenotypic knowledge base [3]. Unfortunately, despite ART resistance being specific to LMICs, the cost of standard HIV drug resistance testing (DRT) is too high for LMICs to adopt [4]. Thus, there is an urgent need to build cost-effective DRT alternatives that overcome high cost, long turnaround times, HIV genetic diversity, supply chain discontinuity and sample type heterogeneity. Two main alternatives exist. Next Generation Sequencing-based approaches for high throughput HIV DRT pipelines can benefit from the extremely low cost per nucleobase and cloud-based data analysis [5]. However, their potential in generating affordable clinical grade DRT results and almost real-time epidemiological information relies on