Abstract Over 38 million people across the world live with HIV. Although antiretroviral therapy (ART) has suppressed HIV plasma viremia, the persistent inflammation in people living with HIV (PLWH) places them at two-fold greater risk of developing metabolic diseases, including cardiovascular disease (CVD). CVD is biochemically associated with predictive inflammatory metabolic biomarkers, such as apolipoprotein A1 (ApoA1), saturated fatty acids (SAFAs), and ceramides. In numerous HIV clinical cohort studies, the excess CVD risk has been documented. Systemic inflammation is an important factor in the pathogenesis of CVD. However, traditional CVD risk assessments do not include direct cardiometabolic measurements of inflammation, nor are unique aspects of inflammatory processes in PLWH considered. While the biochemical factors leading to inflammation and CVD are multifactorial, antiretrovirals (ARVs) are a unique factor. ARV exposure induces changes in the functional cellular transcriptomic and metabolomic profiles and increases inflammatory cytokines; these changes promote CVD in PLWH. Therefore, the net influence on the cardiometabolic risk must be clarified to provide more targeted CVD risk factor modification among PLWH. To address this knowledge gap, we will conduct the Multiomics and Antiretroviral Drug Exposure for assessing Metabolic Effects (MADE-FOR-ME) study using stored specimens from the Multicenter AIDS Cohort Study/Women Interagency HIV Study Combined Cohort Study (MWCCS) to quantify ARV exposure and CVD inflammatory biomarkers. With these specimens, we will quantify ARV exposure and perform experimental multiomics analyses to understand the molecular mechanisms underlying the development of CVD. We will apply principal component analyses, Bayesian estimation methods, and mediation analyses to understand the molecular mechanisms underlying the development of CVD, particularly among different demographic groups living with HIV. We will make exposure-response relationships among different populations such that we can stratify the risk and have population-specific biomarkers and/or understand the limitations from more established biomarkers of interest. These are uniquely 21st century clinical problems that require 21st century methodologies. Our project will likewise contribute to the fields of drug development, computational biology, and systems physiology. By expanding into these areas, we will synergistically impact and transform research studying HIV-associated comorbidities. We anticipate discovering unique and potential drug targets and biomarkers to utilize for more precise monitoring of HIV- associated CVD. With this committed multidisciplinary team, we will identify the effects of ARV exposure on metabolic homeostasis and on inflammatory profiles and pioneer a new era of personalized medicine in HIV/AIDS research with antiretroviral pharmacometabolomics.