Assessing Sirolimus and Antiretroviral Interactions in People with HIV on Chronic ART: A Population Pharmacokinetic Approach in Non-Transplant Recipients
Authors: Tummala Hari Prabhath , Kuo-Esser Laurence , Marzan Florence , Huang Liusheng , Hsue Priscilla , Deeks Steven , Henrich Timothy , Aweeka Francesca , Deitchman Amelia 
Published: February 2025

Objectives: Sirolimus, due to its high intra- and inter-individual pharmacokinetic (PK) variability and narrow therapeutic index, necessitates therapeutic drug monitoring (TDM). The goal of this research was to utilize trough-based TDM data to characterize and investigate PK interactions between sirolimus and frequently employed antiretrovirals (ARVs; namely, tenofovir-TFV, emtricitabine-FTC, efavirenz-EFV, dolutegravir-DTG) from the AIDS Clinical Trials Group Study A5337. Prior studies from our group indicated potential interaction of EFV and DTG based on sirolimus dose-corrected trough-based geometric mean ratio analyses (Kuo-Esser L, ASCPT 2024).Methods: This PK investigation leverages sirolimus trough level data obtained from a 20-week, single-arm study in people with HIV (PWH) stably managed on antiretroviral therapy. We used non-linear mixed effects modeling to evaluate PK interactions between sirolimus and ARVs (NONMEM v7.4). For parameter estimation, the first-order conditional estimation method was utilized, while a 2-compartment model served as the structural model, incorporating first-order absorption and elimination. Parameters that could not be reliably estimated were fixed to literature values or informative priors. Between-subject variability was assessed via an exponential model, while the residual variability (RV) was examined through additive, proportional, and combined error models. The potential impact of ARVs and body weight (BW) on sirolimus PK was assessed as covariate effects. The model’s validity was confirmed through visual and numerical predictive checks.Results: The dataset comprised 298 trough concentrations from 29 patients. The RV model was optimally characterized by an additive error model. The base structural model yielded an objective function value (OFV) of 1149.16, with an estimated clearance (CL) of 9.63 L/hr and an estimated central volume of distribution of 92.4 L. The absorption rate constant (Ka) was fixed at 2.1 (1/h), based on literature values and estimated priors. ARVs were introduced as covariates on CL in an exponential form as dichotomous predictors. Among these, EFV resulted in a decrease in OFV (1136.45), while other drugs and BW did not significantly impact the OFV. Diagnostic and goodness of fit plots (CWRES vs PRED, |IWRES| vs PRED, CWRES vs TIME, DV vs IPRED) corroborated the adequacy of the model.Conclusion: The population PK model effectively characterized the PK of sirolimus in PWH on chronic ART, facilitating prediction of sirolimus exposure in the context of ARVs. The findings revealed that while the ARVs (TFV, FTC, DTG) did not significantly influence sirolimus PK, EFV was associated with an increased sirolimus CL, consequently leading to reduced sirolimus concentrations. This model will be used to simulate a formal drug interaction clinical trial to predict if these changes may result in clinically relevant changes in sirolimus exposure warranting closer monitoring in PWH on EFV.Citations: Golubović B et al. Exploring Sirolimus Pharmacokinetic Variability Using Data Available from the Routine Clinical Care of Renal Transplant Patients - Population Pharmacokinetic Approach. J Med Biochem. 2019 May 11;38(3):323-331.Kuo-Esser L, et al. Efavirenz and Dolutegravir May Alter Sirolimus Metabolism in People Living with HIV. ASCPT 2024.