Perrine Courlet1, Monia Guidi1,2, Susana Alves Saldanha1, Deolinda Alves3, Matthias Cavassini3, Thierry Buclin1, Catia Marzolini4, Laurent A. Decosterd1, Chantal Csajka1,2 and the Swiss HIV Cohort Study.
1Service of Clinical Pharmacology, University Hospital Center, University of Lausanne, Lausanne, Switzerland 2School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland 3Division of Infectious Diseases, University Hospital Center, University of Lausanne 4Departments of Medicine and Clinical Research, University Hospital of Basel and University of Basel, Switzerland
Objectives:
Antiretroviral treatments (ARTs) have transformed HIV infection from a deadly disease to a chronic condition. People living with HIV (PLWH) are aging, experience age-related physiological changes and comorbidities, such as cardiovascular diseases. Atorvastatin is a widely prescribed lipid-lowering agent, predominantly metabolized by cytochrome (CYP) 3A4 into two major active metabolites: ortho-hydroxy (o-OH-atorvastatin) and para-hydroxy atorvastatin (p-OH-atorvastatin) (1, 2). The organic anion transporter protein (OATP1B1/1B3) regulates the entry of atorvastatin in the liver (3). Protease inhibitors are expected to substantially increase atorvastatin exposure by inhibition of its entry in the liver and its further biostransformation, potentially leading to serious side effects such as rhabdomyolysis. The aims of this study were to describe the pharmacokinetic profile of atorvastatin and o-OH-atorvastatin, to identify influencing factors and to evaluate drug-drug interactions (DDIs) with ARTs.
Methods:
Atorvastatin pharmacokinetic assessment involved rich (clinicaltrials.gov, NCT03515772) and sparse sampling studies (SHCS #815). The population pharmacokinetic analysis was performed using NONMEM®, with full PK profiles (87 atorvastatin concentrations) collected in eight PLWH, and then adding 79 atorvastatin concentrations from 55 PLWH. After removal of unreliable o-OH-atorvastatin concentrations (37% of metabolite data), 110 metabolite concentrations were available for model development. Plasma concentrations were converted into their molar equivalents. A stepwise procedure with sequential addition of the metabolite was used to find the model that adequately fit the data. For identifiability issues, the volume of distribution of atorvastatin and its metabolite were assumed to be equal. The correlation between parent drug and metabolite concentration measurements was tested using the L2 function. The influence of age, body weight and comedications on o-OH-atorvastatin formation rate was quantified.
Results:
A two-compartment model with first-order absorption and elimination best described atorvastatin pharmacokinetics, although variability was very high, notably during the absorption phase. During the analysis of rich pharmacokinetic data, absorption rate constant was estimated at 3.06 h-1 with high between-subject variability (BSV, 778%) and was fixed to this value for subsequent model development. o-OH-atorvastatin concentrations were described by adding one compartment and by assuming linear metabolism from atorvastatin. When combining all data, atorvastatin apparent clearance was 232 Lh-1 with a BSV of 105%. Atorvastatin apparent central volume of distribution was 3300 L (BSV 100%), apparent peripheral volume of distribution 830 L, and intercompartmental clearance 116 L/h. o-OH-atorvastatin metabolic rate constant (k23) was 0.265 h-1 with a BSV of 76%, and apparent clearance of the metabolite 1430 L.h-1. K23 was reduced by 56% in PLWH treated with CYP3A4 inhibitors (i.e. boosted protease inhibitors and boosted integrase inhibitors) and explained 15% of the variability on k23. Conversely, the presence of a CYP3A4 inducer (i.e efavirenz) increased k23 by 22% but this association did not reached statistical significance due to the lack of data (8% of atorvastatin concentrations). Finally, age was associated with a non-significant decrease of 8% of k23 for a 70-year patient compared to a 50-year patient. The narrow age interquartile range (58-71 years) might have compromised our power to detect an effect of age.
Conclusions:
The present study showed an important inter-individual variability in atorvastatin pharmacokinetics of which a large proportion remained unexplained after inclusion of covariates. The influence of protease inhibitors on atorvastatin clearance highlights the importance of a personalized dosage adjustment in PLWH treated with boosted ARTs. This pharmacokinetic model allows the establishment of dosages recommendations, thereby providing the most efficient and safest patient’s care.
References:
[1] Kearney AS, Crawford LF, Mehta SC, Radebaugh GW. The interconversion kinetics, equilibrium, and solubilities of the lactone and hydroxyacid forms of the HMG-CoA reductase inhibitor, CI-981. Pharm Res. 1993;10(10):1461-5.
[2] Lennernas H. Clinical pharmacokinetics of atorvastatin. Clinical pharmacokinetics. 2003;42(13):1141-60.
[3] Wu X, Whitfield LR, Stewart BH. Atorvastatin transport in the Caco-2 cell model: contributions of P-glycoprotein and the proton-monocarboxylic acid co-transporter. Pharm Res. 2000;17(2):209-15.
Reference: PAGE 28 (2019) Abstr 8963 [www.page-meeting.org/?abstract=8963]
Poster: Drug/Disease Modelling - Infection