Pharmacokinetic/Pharmacodynamic Modelling to Describe the Cholesterol Lowering Effect of Rosuvastatin in People Living with HIV

Perrine Courlet, Monia Guidi, Susana Alves Saldanha, Felix Stader, Anna Traytel, Matthias Cavassini, Marcel Stoeckle, Thierry Buclin, Catia Marzolini, Laurent A Decosterd, Chantal Csajka, and the Swiss HIV Cohort Study, Perrine Courlet, Monia Guidi, Susana Alves Saldanha, Felix Stader, Anna Traytel, Matthias Cavassini, Marcel Stoeckle, Thierry Buclin, Catia Marzolini, Laurent A Decosterd, Chantal Csajka, and the Swiss HIV Cohort Study

Abstract

Background: Rosuvastatin is a lipid-lowering agent widely prescribed in people living with HIV, which is actively transported into the liver, making it a potential victim of drug-drug interactions with antiretroviral agents.

Objectives: The aims of this study were to characterise the pharmacokinetic profile of rosuvastatin and to describe the relationship between rosuvastatin concentrations and non-high-density lipoprotein (HDL)-cholesterol levels in people living with HIV.

Methods: A population pharmacokinetic model (NONMEM) was developed to quantify the influence of demographics, clinical characteristics and comedications on rosuvastatin pharmacokinetics. This model was combined with an indirect effect model to describe non-HDL-cholesterol measurements.

Results: A two-compartment model with sequential zero- and first-order absorption best fitted the 154 rosuvastatin concentrations provided by 65 people living with HIV. None of the tested covariates significantly influenced rosuvastatin pharmacokinetics. A total of 403 non-HDL cholesterol values were available for pharmacokinetic-pharmacodynamic modelling. Baseline non-HDL cholesterol decreased by 14% and increased by 12% with etravirine and antiretroviral drugs with a known impact on the lipid profile (i.e. protease inhibitors, efavirenz, cobicistat), respectively. The baseline value was surprisingly 43% lower in people living with HIV aged 80 years compared with those aged 40 years. Simulations based on the covariate-free model predicted that, under standard rosuvastatin dosages of 5 mg and 20 mg once daily, 31% and 64% of people living with HIV would achieve non-HDL-cholesterol targets, respectively.

Conclusions: The high between-subject variability that characterises both rosuvastatin pharmacokinetic and pharmacodynamic profiles remained unexplained after the inclusion of usual covariates. Considering its limited potential for drug-drug interactions with antiretroviral agents and its potent lipid-lowering effect, rosuvastatin prescription appears safe and effective in people living with HIV with hypercholesterolaemia.

Clinical trial registration no: NCT03515772.

Conflict of interest statement

Perrine Courlet, Laurent A. Decosterd, Susana Alves Saldanha, Felix Stader, Anna Traytel, Matthias Cavassini, Thierry Buclin, Chantal Csajka and Monia Guidi have no conflict of interest to declare. Marcel Stoeckle got fee’s for advisory boards from Gilead, MSD, ViiV, Janssen-Cilag, Sandoz and Mepha, as well as grants for conferences from Gilead and MSD, yet unrelated to the present study. Catia Marzolini received a research grant from Gilead and speaker honoraria for her institution from MSD.

Figures

Fig. 1
Fig. 1
Compartmental model used to describe rosuvastatin pharmacokinetic (PK) and pharmacodynamic (PD) data. Cl apparent rosuvastatin clearance, Ct rosuvastatin plasma concentration predicted by the model, D1 duration of zero-order absorption, HDL high-density lipoprotein, IC50 rosuvastatin concentration that produced a 50% inhibition of non-HDL-cholesterol production, ka absorption rate constant, kin production rate of non-HDL-cholesterol, kout elimination rate of non-HDL-cholesterol, Q apparent inter-compartmental clearance, Vc apparent central volume of distribution, Vp apparent peripheral volume of distribution
Fig. 2
Fig. 2
Standardized observed rosuvastatin plasma concentration–time profiles. Rosuvastatin plasma concentrations were standardized for a daily dose of 10 mg once daily and are presented in log-scale. Concentrations in people living with HIV receiving boosted protease inhibitors are presented in pink triangles while concentrations observed in people living with HIV receiving antiretroviral drugs devoid of interaction potential are shown in white circles. Rosuvastatin plasma concentrations observed in people living with HIV enrolled in the pharmacokinetic study with rich sampling are joined with black lines
Fig. 3
Fig. 3
Prediction-corrected visual predictive check of the final pharmacokinetic/pharmacodynamic model. Open circles represent log transformed rosuvastatin plasma concentrations (left) and non-high-density lipoprotein (HDL) cholesterol values (right). The continuous line represents the median observed concentration and the dashed lines represent the observed 2.5% and 97.5% percentiles. Shaded areas represent the model-based 95% confidence interval for the median and the 2.5% and 97.5% percentiles
Fig. 4
Fig. 4
Rosuvastatin simulated plasma concentrations (n = 1000) after administration of a standard dose of 10 mg once daily, alone (grey) or with boosted protease inhibitors [PIs] (pink). Continuous lines represent the population median prediction and shaded areas represent the 95% prediction interval for rosuvastatin alone (grey) or with boosted PIs (pink)
Fig. 5
Fig. 5
Distribution of non-high-density lipoprotein (non-HDL)-cholesterol values, 24 h after administration of rosuvastatin dose at steady state, simulated in 1000 individuals using the base pharmacokinetic/pharmacodynamic model. The dashed line represents the non-HDL-cholesterol target according to European AIDS Clinical Society guidelines [23]

References

    1. de Gaetano DK, Cauda R, Iacoviello L. HIV infection, antiretroviral therapy and cardiovascular risk. Mediterr J Hematol Infect Dis. 2010;2(3):e2010034. doi: 10.4084/mjhid.2010.034.
    1. Uthman OA, Nduka C, Watson SI, Mills EJ, Kengne AP, Jaffar SS, et al. Statin use and all-cause mortality in people living with HIV: a systematic review and meta-analysis. BMC Infect Dis. 2018;18(1):258. doi: 10.1186/s12879-018-3162-1.
    1. Moreno A, Fortun J, Graus J, Rodriguez-Gandia MA, Quereda C, Perez-Elias MJ, et al. Severe rhabdomyolysis due to rosuvastatin in a liver transplant subject with human immunodeficiency virus and immunosuppressive therapy-related dyslipidemia. Liver Transpl. 2011;17(3):331–333. doi: 10.1002/lt.22225.
    1. de Kanter CT, Keuter M, van der Lee MJ, Koopmans PP, Burger DM. Rhabdomyolysis in an HIV-infected patient with impaired renal function concomitantly treated with rosuvastatin and lopinavir/ritonavir. Antiviral Ther. 2011;16(3):435–437. doi: 10.3851/IMP1747.
    1. Kitamura S, Maeda K, Wang Y, Sugiyama Y. Involvement of multiple transporters in the hepatobiliary transport of rosuvastatin. Drug Metab Dispos. 2008;36(10):2014–2023. doi: 10.1124/dmd.108.021410.
    1. Patilea-Vrana G, Unadkat JD. Transport vs. metabolism: what determines the pharmacokinetics and pharmacodynamics of drugs? Insights from the extended clearance model. Clin Pharmacol Ther. 2016;100(5):413–8.
    1. da Cunha J, Maselli LM, Stern AC, Spada C, Bydlowski SP. Impact of antiretroviral therapy on lipid metabolism of human immunodeficiency virus-infected patients: old and new drugs. World J Virol. 2015;4(2):56–77. doi: 10.5501/wjv.v4.i2.56.
    1. Courlet P, Livio F, Alves Saldanha S, Scherrer A, Battegay M, Cavassini M, et al. Real-life management of drug-drug interactions between antiretrovirals and statins. J Antimicrob Chemother. 2020.
    1. Samineni D, Desai PB, Sallans L, Fichtenbaum CJ. Steady-state pharmacokinetic interactions of darunavir/ritonavir with lipid-lowering agent rosuvastatin. J Clin Pharmacol. 2012;52(6):922–931. doi: 10.1177/0091270011407494.
    1. Courlet P, Stader F, Guidi M, Alves Saldanha S, Stoeckle M, Cavassini M, et al. Pharmacokinetic profiles of boosted darunavir, dolutegravir and lamivudine in aging people living with HIV. AIDS. 2020;34(1):103–108. doi: 10.1097/QAD.0000000000002372.
    1. Courlet P, Livio F, Guidi M, Cavassini M, Battegay M, Stoeckle M, et al. Polypharmacy, drug-drug interactions, and inappropriate drugs: new challenges in the aging population with HIV. Open Forum Infect Dis. 2019;6(12):ofz531.
    1. Tzeng TB, Schneck DW, Birmingham BK, Mitchell PD, Zhang H, Martin PD, et al. Population pharmacokinetics of rosuvastatin: implications of renal impairment, race, and dyslipidaemia. Curr Med Res Opin. 2008;24(9):2575–2585. doi: 10.1185/03007990802312807.
    1. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31–41. doi: 10.1159/000180580.
    1. van den Berg R, Noordam R, Kooijman S, Jansen SWM, Akintola AA, Slagboom PE, et al. Familial longevity is characterized by high circadian rhythmicity of serum cholesterol in healthy elderly individuals. Aging Cell. 2017;16(2):237–243. doi: 10.1111/acel.12547.
    1. Courlet P, Spaggiari D, Desfontaine V, Cavassini M, Alves Saldanha S, Buclin T, et al. UHPLC-MS/MS assay for simultaneous determination of amlodipine, metoprolol, pravastatin, rosuvastatin, atorvastatin with its active metabolites in human plasma, for population-scale drug-drug interactions studies in people living with HIV. J Chromatogr B Analyt Technol Biomed Life Sci. 2019;1125:121733. doi: 10.1016/j.jchromb.2019.121733.
    1. Mach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, et al. 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2019;.
    1. Keizer RJ, van Benten M, Beijnen JH, Schellens JH, Huitema AD. Pirana and PCluster: a modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs Biomed. 2011;101(1):72–79. doi: 10.1016/j.cmpb.2010.04.018.
    1. Lindbom L, Pihlgren P, Jonsson EN. PsN-Toolkit: a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 2005;79(3):241–257. doi: 10.1016/j.cmpb.2005.04.005.
    1. Busti AJ, Bain AM, Hall RG, 2nd, Bedimo RG, Leff RD, Meek C, et al. Effects of atazanavir/ritonavir or fosamprenavir/ritonavir on the pharmacokinetics of rosuvastatin. J Cardiovasc Pharmacol. 2008;51(6):605–610. doi: 10.1097/FJC.0b013e31817b5b5a.
    1. Custodio JM, West S, SenGupta D, Zari A, Humeniuk R, Ling KH, et al. Evaluation of the drug-drug interaction potential between cobicistat-boosted protease inhibitors and statins. [abstract O_04]. 18th International Workshop on Clinical Pharmacology of Antiviral Therapy; 14–16 June 2017; Chicago (IL).
    1. Overgaard RV, Ingwersen SH, Tornoe CW. Establishing good practices for exposure-response analysis of clinical endpoints in drug development. CPT Pharmacometrics Syst Pharmacol. 2015;4(10):565–575. doi: 10.1002/psp4.12015.
    1. Wahlby U, Thomson AH, Milligan PA, Karlsson MO. Models for time-varying covariates in population pharmacokinetic-pharmacodynamic analysis. Br J Clin Pharmacol. 2004;58(4):367–377. doi: 10.1111/j.1365-2125.2004.02170.x.
    1. European AIDS Clinical Society. Guidelines version 10.0. 2019. Available from: . [Accessed 1 Oct 2020].
    1. Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 2011;13(2):143–151. doi: 10.1208/s12248-011-9255-z.
    1. Macpherson M, Hamren B, Braamskamp MJ, Kastelein JJ, Lundstrom T, Martin PD. Population pharmacokinetics of rosuvastatin in pediatric patients with heterozygous familial hypercholesterolemia. Eur J Clin Pharmacol. 2016;72(1):19–27. doi: 10.1007/s00228-015-1946-4.
    1. Park W, Jang D, Han S, Yim D. Mixed-effects analysis of increased rosuvastatin absorption by coadministrered telmisartan. Transl Clin Pharmacol. 2016;24(1):55–62. doi: 10.12793/tcp.2016.24.1.55.
    1. Aoyama T, Omori T, Watabe S, Shioya A, Ueno T, Fukuda N, et al. Pharmacokinetic/pharmacodynamic modeling and simulation of rosuvastatin using an extension of the indirect response model by incorporating a circadian rhythm. Biol Pharm Bull. 2010;33(6):1082–1087. doi: 10.1248/bpb.33.1082.
    1. Pasanen MK, Fredrikson H, Neuvonen PJ, Niemi M. Different effects of SLCO1B1 polymorphism on the pharmacokinetics of atorvastatin and rosuvastatin. Clin Pharmacol Ther. 2007;82(6):726–733. doi: 10.1038/sj.clpt.6100220.
    1. Keskitalo JE, Zolk O, Fromm MF, Kurkinen KJ, Neuvonen PJ, Niemi M. ABCG2 polymorphism markedly affects the pharmacokinetics of atorvastatin and rosuvastatin. Clin Pharmacol Ther. 2009;86(2):197–203. doi: 10.1038/clpt.2009.79.
    1. Kiser JJ, Gerber JG, Predhomme JA, Wolfe P, Flynn DM, Hoody DW. Drug/drug interaction between lopinavir/ritonavir and rosuvastatin in healthy volunteers. J Acquir Immune Defic Syndr. 2008;47(5):570–578. doi: 10.1097/QAI.0b013e318160a542.
    1. Annaert P, Ye ZW, Stieger B, Augustijns P. Interaction of HIV protease inhibitors with OATP1B1, 1B3, and 2B1. Xenobiotica. 2010;40(3):163–176. doi: 10.3109/00498250903509375.
    1. Janssen-Cilag. Prezista summary of product characteristics. June 2012.
    1. Faltaos DW, Urien S, Carreau V, Chauvenet M, Hulot JS, Giral P, et al. Use of an indirect effect model to describe the LDL cholesterol-lowering effect by statins in hypercholesterolaemic patients. Fundam Clin Pharmacol. 2006;20(3):321–330. doi: 10.1111/j.1472-8206.2006.00404.x.
    1. Gatell JM, Assoumou L, Moyle G, Waters L, Johnson M, Domingo P, et al. Switching from a ritonavir-boosted protease inhibitor to a dolutegravir-based regimen for maintenance of HIV viral suppression in patients with high cardiovascular risk. AIDS. 2017;31(18):2503–2514. doi: 10.1097/QAD.0000000000001675.
    1. Taramasso L, Tatarelli P, Ricci E, Madeddu G, Menzaghi B, Squillace N, et al. Improvement of lipid profile after switching from efavirenz or ritonavir-boosted protease inhibitors to rilpivirine or once-daily integrase inhibitors: results from a large observational cohort study (SCOLTA) BMC Infect Dis. 2018;18(1):357. doi: 10.1186/s12879-018-3268-5.
    1. Casado JL, de Los SI, Del Palacio M, Garcia-Fraile L, Perez-Elias MJ, Sanz J, et al. Lipid-lowering effect and efficacy after switching to etravirine in HIV-infected patients with intolerance to suppressive HAART. HIV Clin Trials. 2013;14(1):1–9. doi: 10.1310/hct1401-1.
    1. Glass TR, Weber R, Vernazza PL, Rickenbach M, Furrer H, Bernasconi E, et al. Ecological study of the predictors of successful management of dyslipidemia in HIV-infected patients on ART: the Swiss HIV Cohort Study. HIV Clin Trials. 2007;8(2):77–85. doi: 10.1310/hct0802-77.
    1. El-Sadr WM, Mullin CM, Carr A, Gibert C, Rappoport C, Visnegarwala F, et al. Effects of HIV disease on lipid, glucose and insulin levels: results from a large antiretroviral-naive cohort. HIV Med. 2005;6(2):114–121. doi: 10.1111/j.1468-1293.2005.00273.x.
    1. May MT, Gompels M, Delpech V, Porter K, Orkin C, Kegg S, et al. Impact on life expectancy of HIV-1 positive individuals of CD4+ cell count and viral load response to antiretroviral therapy. AIDS. 2014;28(8):1193–1202. doi: 10.1097/QAD.0000000000000243.
    1. Aslangul E, Assoumou L, Bittar R, Valantin MA, Kalmykova O, Peytavin G, et al. Rosuvastatin versus pravastatin in dyslipidemic HIV-1-infected patients receiving protease inhibitors: a randomized trial. AIDS. 2010;24(1):77–83. doi: 10.1097/QAD.0b013e328331d2ab.
    1. Calza L, Manfredi R, Colangeli V, Pocaterra D, Pavoni M, Chiodo F. Rosuvastatin, pravastatin, and atorvastatin for the treatment of hypercholesterolaemia in HIV-infected patients receiving protease inhibitors. Curr HIV Res. 2008;6(6):572–578. doi: 10.2174/157016208786501481.

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