Influence of Drug–Drug Interactions on the Pharmacokinetics of Atorvastatin and Its Major Active Metabolite ortho-OH-Atorvastatin in Aging People Living with HIV

People living with HIV (PLWH) live longer and experience age-related physiological changes and comorbidities, notably cardiovascular diseases. Polypharmacy is frequent in elderly PLWH, leading to an increased risk for drug–drug interactions (DDIs), which may harm this vulnerable population. Antiretroviral drugs (ARVs) are among the therapeutic agents with the highest potential for DDIs. Protease inhibitors (PIs) and non-nucleoside reverse transcriptase inhibitors (NNRTIs) can indeed inhibit and/or induce cytochrome P450 (CYP) isoforms [1] as well as drug transporters [2].

Atorvastatin is a widely prescribed lipid-lowering agent that undergoes extensive first-pass metabolism [3]. It is predominantly metabolized by CYP3A4 into two active metabolites: the major ortho-hydroxy atorvastatin (o-OH-atorvastatin) and the minor para-hydroxy atorvastatin (p-OH-atorvastatin). Both atorvastatin and its active metabolites can undergo lactonization and thus exist in equilibrium with their respective inactive lactone forms. A study has suggested that most of the acid metabolites present in human plasma results from an interconversion of lactone metabolites [4]. It has been reported that about 70% of the HMG-CoA reductase inhibition is attributable to o-OH-atorvastatin and p-OH-atorvastatin, while the lactone forms are inactive [3]. Nevertheless, the latter may be incriminated for statin-induced myotoxicity [5, 6].

Importantly, the organic anion transporting polypeptide (OATP1B1/1B3) facilitates the entry of atorvastatin in the liver (i.e. the site of action) [7]. PIs inhibit OATP1B1 in addition to CYP3A4 and are therefore expected to substantially increase atorvastatin exposure, both by inhibiting the entry of the statin in the liver and by further inhibiting its biotransformation. According to the summary of product characteristics, atorvastatin exposure could increase by three- to fourfold in the presence of ritonavir-boosted darunavir [8]. This interaction can lead to serious adverse effects, such as rhabdomyolysis [9]. The current recommendations indicate to initiate atorvastatin at a low dosage in the presence of boosted darunavir and not to exceed a daily dose of 20 mg. However, formal DDI studies have not been performed, particularly in the elderly, leading to a lack of knowledge on the magnitude of DDIs.

To date, several studies have evaluated the factors influencing atorvastatin pharmacokinetics (PK). The effect of age is controversial, with some authors reporting an age-related increase in atorvastatin exposure [10‐12], while others did not find any significant influence [13, 14]. One non-compartmental PK study showed an effect of sex (11% decrease in area under the curve [AUC] in women) on atorvastatin disposition [11]. Moreover, population PK studies indicate a body weight-related decrease in atorvastatin clearance [13], an influence of liver enzymes (aspartate aminotransferase [AST] and lactate dehydrogenase) on atorvastatin disposition [14, 15], and an effect of polymorphisms in the intestinal breast cancer resistance protein (BCRP) on atorvastatin bioavailability [16]. However, to our knowledge, no study investigated the effect of ARVs on atorvastatin disposition in a real-life setting.

The aims of this observational study were to develop a population PK model for atorvastatin and its major active metabolite in aging PLWH, and to quantify the effect of ARVs and other covariates on their disposition.

Our study provides a description of the population PK profile of atorvastatin and o-OH-atorvastatin, and quantifies the magnitude of DDIs with ARVs in real-life situations. Although parameter estimates widely differ between published population PK analyses, the reported PK parameters estimated in the present study were generally in fair concordance with overall reported values [13, 14].

The present model revealed large interindividual variability in atorvastatin PK, notably during the absorption phase, known to be affected by multiple factors. First, food has been reported to decrease atorvastatin peak concentration (C_max) and increase time to C_max (T_max) [3]. Although all full PK samples were obtained under standardized conditions, this parameter was not controlled for samples collected during the follow-up visits. Since, atorvastatin is exposed to intestinal CYP3A4 during the absorption phase, CYP3A4 inhibitors and inducers may further contribute to the observed important variability in this parameter. In our PK model, this has been captured by integrating the effect of boosted regimens (all CYP3A4 inhibitors) on the absorption parameter FR_ator-oOH. Finally, several transporters are involved in the disposition of atorvastatin and its metabolites. Genetic polymorphisms can affect the intrinsic activity and/or expression of transporters and the observed variability in atorvastatin absorption could therefore be explained by the genetic background [10, 31]. Shitara et al. showed that OATP could play a significant role in atorvastatin absorption [32]. In addition, ABCG2 and SLCOB polymorphisms have been shown to affect atorvastatin C_max, with no effect on elimination half-life [33‐35], supporting an effect of transporter genotypes on atorvastatin mainly during the absorption phase. However, the lack of genotyping data in our study prevented the estimation of such an effect. In our model, due to the complexity of the absorption phase, k_a was fixed to the value obtained during the analysis, using atorvastatin rich PK data to obtain a reasonable value of T_max. Predicted T_max values ranged from 0.5 to 3.7 h, with a median of 1.3 h, in accordance with the manufacturer’s data [36]. Studies also reported T_max values varying from 0.5 to 2 h [37‐41]. In addition, the k_a value of 2.59 h⁻¹ is in the range of values reported in published population PK models, varying from 0.2 to 3.5 h⁻¹.

The present study also identified large between-subject variability in atorvastatin clearance and central volume of distribution. Although non-compartmental analyses showed an effect of age on atorvastatin disposition [10, 11], the majority of previously published population PK analyses did not report any significant influence [13, 14, 16], while one of the studies found an effect in men only [12]. In our study, this association did not reach statistical significance, although visual inspection of the plots evaluating the effect of age on atorvastatin clearance suggested a slight decrease in clearance for PLWH older than 60 years of age. This absence of age effect could result from the narrow interquartile range of age (58–71 years) in our population.

This model allowed for the evaluation of the impact of DDIs that are encountered in clinical practice. The dual inhibition of cytochromes and transporters is expected to substantially increase atorvastatin exposure [42]. Inhibition of the hepatic uptake transporter OATP1B1 is expected to reduce the entry of atorvastatin in the liver, whereas inhibition of hepatic BCRP and P-gp decreases the hepatobiliary excretion of atorvastatin. A previously published study demonstrated that inhibition of hepatic transporters of atorvastatin might yield to DDIs with the same magnitude as enzyme inhibition [38], with potential occurrence of atorvastatin toxicity. Indeed, adverse effects such as rhabdomyolysis appeared to be at least partially related to atorvastatin plasma concentrations [43, 44], and several cases of rhabdomyolysis have been reported with the simultaneous administration of moderate or strong CYP3A4 inhibitors [45‐48]. Studies suggested that myotoxicity may be related to either atorvastatin lactone or hydroxylated metabolites, or both [6, 39]. However, regardless of the actual incriminated species, its formation critically depends on the disposition and the circulating concentrations of the parent statin, which keeps a determinant interest. No atorvastatin target plasma trough concentrations have been clearly established to avoid toxicity, but caution is needed when co-prescribing enzyme and transporter inhibitors with atorvastatin.

The magnitude of DDIs with atorvastatin differs between boosted regimens. Atorvastatin AUC was shown to be increased by 822% when coadministered with ritonavir-boosted atazanavir, while atorvastatin AUC increased by 200–300% and 700–800% when coadministered with ritonavir-boosted darunavir or ritonavir-boosted tipranavir, respectively [37]. Differences in the magnitude of DDIs have been attributed to differences in the ability of PIs to inhibit OATP1B1 [49]. In our study, the lack of data prevented us from differentiating the effect of different boosted regimens on atorvastatin and o-OH-atorvastatin exposure. Model-based simulations revealed a 2.8-fold increase in AUC_ator when coadministered with boosted regimens that were mostly boosted darunavir. This result is in good agreement with the manufacturer’s data reporting a three- to fourfold increase in atorvastatin AUC when coadministered with ritonavir-boosted darunavir. In addition, another study showed that atorvastatin AUC increased by 290% in cases of coadministration of cobicistat-boosted darunavir [50]. To our knowledge, no study has reported the effect of boosted regimens on the active moiety, which is modulated by the decrease in o-OH-atorvastatin exposure. Our results demonstrated that PLWH receiving concomitantly boosted regimens and atorvastatin at a daily dose of 10 mg obtained an atorvastatin exposure 29% lower than PLWH receiving atorvastatin alone at a daily dose of 40 mg. This result is slightly different, with manufacturer’s data reporting a difference of 15% [8]. Conversely, AUC_ator and AUC_{active moiety} were 44 and 31% lower, respectively, in PLWH receiving CYP3A4 inducers compared with PLWH receiving ARVs not involved in DDIs with atorvastatin. This is in perfect agreement with studies reporting a moderate magnitude of DDIs between atorvastatin and NNRTIs [51, 52]. Finally, the inducing effect of NNRTIs on CYP3A4 partly compensates for the magnitude of DDIs with boosted ARVs. Of interest, when coadministered together, the inhibitory effect of boosted regimens was shown to be stronger than the concurrent inducing effect of NNRTIs, as evidenced by the fact that AUC_ator and AUC_{active moiety} increased by 61 and 21%, respectively.

This study has some limitations. First, the small sample size prevented us from differentiating the effect of different boosted regimens. However, atorvastatin PK data in PLWH are limited in the literature and this work aims to expand the current knowledge on DDIs in a real-life setting. In addition, the effect of boosted ARVs on the magnitude of DDIs could have been slightly attenuated as among the 80 concentrations obtained in PLWH treated with boosted regimens, 12 (15%) were also influenced by CYP3A4 inducers.

The present study showed an important between-subject variability in atorvastatin PK that remained largely unexplained after the inclusion of covariates. Since atorvastatin exposure doubles in the presence of boosted ARV drugs, the initial dosage might be reduced by half, and titrated based on clinical risk factors and targets.