Rifampin- and Silymarin-Mediated Pharmacokinetic Interactions of Exogenous and Endogenous Substrates in a Transgenic OATP1B Mouse Model.

Organic anion-transporting polypeptides (OATP) 1B1 and OATP1B3, encoded by the SLCO gene family of the solute carrier superfamily, are involved in the disposition of many exogenous and endogenous compounds. Preclinical rodent models help assess risks of pharmacokinetic interactions, but interspecies differences in transporter orthologs and expression limit direct clinical translation. An OATP1B transgenic mouse model comprising a rodent Slco1a/1b gene cluster knockout and human SLCO1B1 and SLCO1B3 gene insertions provides a potential physiologically relevant preclinical tool to predict pharmacokinetic interactions. Pharmacokinetics of exogenous probe substrates, pitavastatin and pravastatin, and endogenous OATP1B biomarkers, coproporphyrin-I and coproporphyrin-III, were determined in the presence and absence of known OATP/Oatp inhibitors, rifampin or silymarin (an extract of milk thistle [Silybum marianum]), in wild-type FVB mice and humanized OATP1B mice. Rifampin increased exposure of pitavastatin (4.6- and 2.8-fold), pravastatin (3.6- and 2.2-fold), and coproporphyrin-III (1.6- and 2.1-fold) in FVB and OATP1B mice, respectively, but increased coproporphyrin-I AUC0-24h only (1.8-fold) in the OATP1B mice. Silymarin did not significantly affect substrate AUC, likely because the silymarin flavonolignan concentrations were at or below their reported IC50 values for the relevant OATPs/Oatps. Silymarin increased the Cmax of pitavastatin 2.7-fold and pravastatin 1.9-fold in the OATP1B mice. The data of the OATP1B mice were similar to those of the pitavastatin and pravastatin clinical data; however, the FVB mice data more closely recapitulated pitavastatin clinical data than the data of the OATP1B mice, suggesting that the OATP1B mice are a reasonable, though costly, preclinical strain for predicting pharmacokinetic interactions when doses are optimized to achieve clinically relevant plasma concentrations.

Evodiamine decreased the systemic exposure of pravastatin in non-alcoholic steatohepatitis rats due to the up-regulation of hepatic OATPs.

CONTEXT: Patients with non-alcoholic steatohepatitis (NASH) may have a simultaneous intake of pravastatin and evodiamine-containing herbs. OBJECTIVE: The effect of evodiamine on the pharmacokinetics of pravastatin and its potential mechanisms were investigated in NASH rats. MATERIALS AND METHODS: The NASH model was conducted with feeding a methionine choline-deficient (MCD) diet for 8 weeks. Sprague-Dawley rats were randomised equally (n = 6) into NASH group, evodiamine group (10 mg/kg), pravastatin group (10 mg/kg), and evodiamine (10 mg/kg) + pravastatin (10 mg/kg) group. Normal control rats were fed a standard diet. Effects of evodiamine on the pharmacokinetics, distribution, and uptake of pravastatin were investigated. RESULTS: Evodiamine decreased Cmax (159.43 ± 26.63 vs. 125.61 ± 22.17 µg/L), AUC0-t (18.17 ± 2.52 vs. 14.91 ± 2.03 mg/min/L) and AUC0-∞ (22.99 ± 2.62 vs. 19.50 ± 2.31 mg/min/L) of orally administered pravastatin in NASH rats, but had no significant effect in normal rats. Evodiamine enhanced the uptake (from 154.85 ± 23.17 to 198.48 ± 26.31 pmol/mg protein) and distribution (from 736.61 ± 108.07 to 911.89 ± 124.64 ng/g tissue) of pravastatin in NASH rat liver. The expression of Oatp1a1, Oatp1a4, and Oatp1b2 was up-regulated 1.48-, 1.38-, and 1.51-fold by evodiamine. Evodiamine decreased the levels of IL-1ß, IL-6, and TNF-α by 27.82%, 24.76%, and 29.72% in NASH rats, respectively. DISCUSSION AND CONCLUSIONS: Evodiamine decreased the systemic exposure of pravastatin by up-regulating the expression of OATPs. These results provide a reference for further validation of this interaction in humans.

Prediction of drug-drug interaction potential mediated by transporters between dasatinib and metformin, pravastatin, and rosuvastatin using physiologically based pharmacokinetic modeling.

PURPOSE: Recent in vitro studies demonstrated that dasatinib inhibits organic cation transporter 2 (OCT2), multidrug and toxin extrusion proteins (MATEs), and organic anion transporting polypeptide 1B1/1B3 (OATP1B1/1B3). We developed a physiologically based pharmacokinetic (PBPK) model to assess drug-drug interaction (DDI) potential between dasatinib and known substrates for these transporters in a virtual population. METHODS: The dasatinib PBPK model was constructed using Simcyp® Simulator by combining its physicochemical properties, in vitro data, in silico predictions, and pharmacokinetic (PK) results from clinical studies. Model validation against three independent clinical trials not used for model development included dasatinib DDI studies with ketoconazole, rifampin, and simvastatin. The validated model was used to simulate DDIs of dasatinib and known substrates for OCT2 and MATEs (metformin) and OATP1B1/1B3 (pravastatin and rosuvastatin). RESULTS: Simulations of metformin PK in the presence and absence of dasatinib, using inhibitor constant (Ki) values measured in vitro, produced estimated geometric mean ratios (GMRs) of the maximum observed concentration (Cmax) and area under the concentration-time curve (AUC) of 1.05 and 1.06, respectively. Sensitivity analysis showed metformin exposure increased < 30% in both AUC and Cmax when dasatinib Ki was reduced by tenfold for OCT2 and MATEs simultaneously, and < 40% with a 20-fold Ki reduction. The estimated GMRs of Cmax and AUC for pravastatin and rosuvastatin with co-administration of dasatinib were unity (1.00). CONCLUSIONS: This PBPK model accurately described the observed PK profiles of dasatinib. The validated PBPK model predicts low risk of clinically significant DDIs between dasatinib and metformin, pravastatin, or rosuvastatin.

Assessment of the Effect of Filgotinib on the Pharmacokinetics of Atorvastatin, Pravastatin, and Rosuvastatin in Healthy Adult Participants.

Filgotinib, an oral Janus kinase-1 preferential inhibitor, is approved in Europe and Japan for adults with rheumatoid arthritis. Patients with rheumatoid arthritis are at higher risk of cardiovascular morbidity/mortality; thus, it is important to understand potential drug-drug interactions of filgotinib with lipid-lowering agents. This open-label, randomized, 2-way crossover study evaluated the pharmacokinetics of atorvastatin, pravastatin, and rosuvastatin with and without filgotinib coadministration. Healthy participants (N = 27) received single doses of atorvastatin (40 mg) and of a pravastatin (40 mg)/rosuvastatin (10 mg) cocktail-alone or with filgotinib (200 mg once daily for 11 days)-on 2 different occasions with washout in between. Serial pharmacokinetic blood samples were collected, and safety was assessed. Pharmacokinetic parameters were evaluated using 90% confidence intervals (CI) of the geometric least-squares mean (GLSM) ratio of the test treatment (statin coadministration with filgotinib) vs statin alone, with prespecified lack-of-interaction bounds of 0.70 to 1.43. Coadministration of filgotinib did not affect atorvastatin area under the plasma concentration-time curve extrapolated to infinity (AUCinf ; [GLSM ratios (90% CI): 0.91 (0.84-0.99)]), but maximum concentration [Cmax ] was slightly lower [0.82 (0.69-0.99)]. The exposure of 2-hydroxy-atorvastatin was unaffected (GLSM ratios [90% CI], 0.98 [0.81-1.19] for Cmax ; 1.11 [1.02-1.22] for AUCinf ). Pravastatin AUCinf was also unaffected (GLSM ratios, 1.22 [1.05-1.41], but Cmax was slightly higher 1.25 [1.01-1.54]). Rosuvastatin exposure was moderately higher with filgotinib coadministration-GLSM ratios (90% CI), 1.68 (1.43-1.97) for Cmax ; 1.42 (1.30-1.57) for AUCinf -but this was not considered clinically relevant. These results indicate that filgotinib has no clinically meaningful effect on exposure of atorvastatin, pravastatin, or rosuvastatin.

Improving the Translation of Organic Anion Transporting Polypeptide Substrates using HEK293 Cell Data in the Presence and Absence of Human Plasma via Physiologically Based Pharmacokinetic Modeling.

Accurately predicting the pharmacokinetics of compounds that are transporter substrates has been notoriously challenging using traditional in vitro systems and physiologically based pharmacokinetic (PBPK) modeling. The objective of this study was to use PBPK modeling to understand the translational accuracy of data generated with human embryonic kidney 293 (HEK293) cells overexpressing the hepatic uptake transporters organic anion transporting polypeptide (OATP) 1B1/3 with and without plasma while accounting for transporter expression. Models of four OATP substrates, two with low protein binding (pravastatin and rosuvastatin) and two with high protein binding (repaglinide and pitavastatin) were explored, and the OATP in vitro data generated in plasma incubations were used for a plasma model, and in buffer incubations for a buffer model. The pharmacokinetic parameters and concentration-time profiles of pravastatin and rosuvastatin were similar and well predicted (within 2-fold of observed values) using the plasma and buffer models without needing an empirical scaling factor, whereas the dispositions of the highly protein bound repaglinide and pitavastatin were more accurately simulated with the plasma models than the buffer models. This work suggests that data from HEK293 overexpressing transporter cells corrected for transporter expression represent a valid approach to improve bottom-up PBPK modeling for highly protein bound OATP substrates with plasma incubations and low protein binding OATP substrates with or without plasma incubations. SIGNIFICANCE STATEMENT: This work demonstrates the bottom-up approach of using in vitro data directly without employing empirical scaling factors to predict the intravenous pharmacokinetic (PK) profiles reasonably well for four organic anion transporting polypeptide (OATP) substrates. Based on these results, using HEK293 overexpressing cells, examining the impact of plasma for highly bound compounds, and incorporating transporter quantitation for the lot in which the in vitro data were generated represents a valid approach to achieve more accurate prospective PK predictions for OATP substrates.

A randomized pilot clinical trial of pravastatin versus placebo in pregnant patients at high risk of preeclampsia.

BACKGROUND: Preeclampsia remains a major cause of maternal and neonatal morbidity and mortality. Biologic plausibility, compelling preliminary data, and a pilot clinical trial support the safety and utility of pravastatin for the prevention of preeclampsia. OBJECTIVE: We previously reported the results of a phase I clinical trial using a low dose (10 mg) of pravastatin in high-risk pregnant women. Here, we report a follow-up, randomized trial of 20 mg pravastatin versus placebo among pregnant women with previous preeclampsia who required delivery before 34+6 weeks' gestation with the objective of evaluating the safety and pharmacokinetic parameters of pravastatin. STUDY DESIGN: This was a pilot, multicenter, blinded, placebo-controlled, randomized trial of women with singleton, nonanomalous pregnancies at high risk for preeclampsia. Women between 12+0 and 16+6 weeks of gestation were assigned to receive a daily pravastatin dose of 20 mg or placebo orally until delivery. In addition, steady-state pravastatin pharmacokinetic studies were conducted in the second and third trimesters of pregnancy and at 4 to 6 months postpartum. Primary outcomes included maternal-fetal safety and pharmacokinetic parameters of pravastatin during pregnancy. Secondary outcomes included maternal and umbilical cord blood chemistries and maternal and neonatal outcomes, including rates of preeclampsia and preterm delivery, gestational age at delivery, and birthweight. RESULTS: Of note, 10 women assigned to receive pravastatin and 10 assigned to receive the placebo completed the trial. No significant differences were observed between the 2 groups in the rates of adverse or serious adverse events, congenital anomalies, or maternal and umbilical cord blood chemistries. Headache followed by heartburn and musculoskeletal pain were the most common side effects. We report the pravastatin pharmacokinetic parameters including pravastatin area under the curve (total drug exposure over a dosing interval), apparent oral clearance, half-life, and others during pregnancy and compare it with those values measured during the postpartum period. In the majority of the umbilical cord and maternal samples at the time of delivery, pravastatin concentrations were below the limit of quantification of the assay. The pregnancy and neonatal outcomes were more favorable in the pravastatin group. All newborns passed their brainstem auditory evoked response potential or similar hearing screening tests. The average maximum concentration and area under the curve values were more than 2-fold higher following a daily 20 mg dose compared with a 10 mg daily pravastatin dose, but the apparent oral clearance, half-life, and time to reach maximum concentration were similar, which is consistent with the previously reported linear, dose-independent pharmacokinetics of pravastatin in nonpregnant subjects. CONCLUSION: This study confirmed the overall safety and favorable pregnancy outcomes for pravastatin in women at high risk for preeclampsia. This favorable risk-benefit analysis justifies a larger clinical trial to evaluate the efficacy of pravastatin for the prevention of preeclampsia. Until then, pravastatin use during pregnancy remains investigational.

Evaluation of Pharmacokinetic Drug Interactions of the Direct-Acting Antiviral Agents Elbasvir and Grazoprevir with Pitavastatin, Rosuvastatin, Pravastatin, and Atorvastatin in Healthy Adults.

BACKGROUND: Many people infected with hepatitis C virus have comorbidities, including hypercholesterolemia, that are treated with statins. In this study, we evaluated the drug-drug interaction potential of the hepatitis C virus inhibitors elbasvir (EBR) and grazoprevir (GZR) with statins. Pitavastatin, rosuvastatin, pravastatin, and atorvastatin are substrates of organic anion-transporting polypeptide 1B, whereas rosuvastatin and atorvastatin are also breast cancer resistance protein substrates. METHODS: Three open-label, phase I clinical trials in healthy adults were conducted with multiple daily doses of oral GZR or EBR/GZR and single oral doses of statins. Trial 1: GZR 200 mg plus pitavastatin 10 mg. Trial 2: Part 1, GZR 200 mg plus rosuvastatin 10 mg, then EBR 50 mg/GZR 200 mg plus rosuvastatin 10 mg; Part 2, EBR 50 mg/GZR 200 mg plus pravastatin 40 mg. Trial 3: EBR 50 mg/GZR 200 mg plus atorvastatin 10 mg. RESULTS: Neither GZR nor EBR pharmacokinetics were meaningfully affected by statins. Coadministration of EBR/GZR did not result in clinically relevant changes in the exposure of pitavastatin or pravastatin. However, EBR/GZR increased exposure to rosuvastatin (126%) and atorvastatin (94%). Coadministration of statins plus GZR or EBR/GZR was generally well tolerated. CONCLUSIONS: Although statins do not appreciably affect EBR or GZR pharmacokinetics, EBR/GZR can impact the pharmacokinetics of certain statins, likely via inhibition of breast cancer resistance protein but not organic anion-transporting polypeptide 1B. Coadministration of EBR/GZR with pitavastatin or pravastatin does not require adjustment of either dose of statin, whereas the dose of rosuvastatin and atorvastatin should be decreased when coadministered with EBR/GZR.

UPLC-MS/MS method for the simultaneous quantification of pravastatin, fexofenadine, rosuvastatin, and methotrexate in a hepatic uptake model and its application to the possible drug-drug interaction study of triptolide.

A rapid and specific UPLC-MS/MS method with a total run time of 3.5 min was developed for the determination of pravastatin, fexofenadine, rosuvastatin, and methotrexate in rat primary hepatocytes. After protein precipitation with 70% acetonitrile (containing 30% H2 O), these four analytes were separated under gradient conditions with a mobile phase consisting of 0.03% acetic acid (v/v) and methanol at a flow rate of 0.50 mL/min. The linearity, recovery, matrix effect, accuracy, precision, and stability of the method were well validated. We evaluated drug-drug interactions based on these four compounds in freshly suspended hepatocytes. The hepatic uptake of pravastatin, fexofenadine, rosuvastatin, and methotrexate at 4°C was significantly lower than that at 37°C, and the hepatocytes were saturable with increased substrate concentration and culture time, suggesting that the rat primary hepatocyte model was successfully established. Triptolide showed a significant inhibitory effect on the hepatic uptake of these four compounds. In conclusion, this method was successfully employed for the quantification of pravastatin, fexofenadine, rosuvastatin, and methotrexate and was used to verify the rat primary hepatocyte model for Oatp1, Oatp2, Oatp4, and Oat2 transporter studies. Then, we applied this model to explore the effect of triptolide on these four transporters.

Functional Consequences of Pravastatin Isomerization on OATP1B1-Mediated Transport.

Pravastatin acid (PVA) can be isomerized to its inactive metabolite 3'α-iso-pravastatin acid (3αPVA) under acidic pH conditions. Previous studies reported interindividual differences in circulating concentrations of PVA and 3αPVA. This study investigated the functional consequences of PVA isomerization on OATP1B1-mediated transport. We characterized 3αPVA inhibition of OATP1B1-mediated PVA uptake into human embryonic kidney 293 cells expressing the four different OATP1B1 proteins (*1a, *1b, *5, and *15). 3αPVA inhibited OATP1B1-mediated PVA uptake in all four OATP1B1 gene products but with lower IC50/Ki values for OATP1B1*5 and *15 than for the reference proteins (*1a and *1b). PVA and 3αPVA were transported by all four OATP1B1 proteins. Kinetic experiments revealed that maximal transport rates (Vmax values) for OATP1B1 variants *5 and *15 were lower than for *1a and *1b for both substrates. Apparent affinities for 3αPVA transport were similar for all four variants. However, the apparent affinity of OATP1B1*5 for 3αPVA was higher (lower Km value) than for PVA. These data confirm that PVA conversion to 3αPVA can have functional consequences on PVA uptake and impacts OATP1B1 variants more than the reference protein, thus highlighting another source variation that must be taken into consideration when optimizing the PVA dose-exposure relationship for patients. SIGNIFICANCE STATEMENT: 3'α-iso-pravastatin acid inhibits pravastatin uptake for all OATP1B1 protein types; however, the IC50 values were significantly lower in OATP1B1*5 and *15 transfected cells. This suggests that a lower concentration of 3'α-iso-pravastatin is needed to disrupt OATP1B1-mediated pravastatin uptake, secondary to decreased cell surface expression of functional OATP1B1 in variant-expressing cells. These data will refine previous pharmacokinetic models that are utilized to characterize pravastatin interindividual variability with an ultimate goal of maximizing efficacy at the lowest possible risk for toxicity.

Predicted values for human total clearance of a variety of typical compounds with differently humanized-liver mouse plasma data.

Prediction of human pharmacokinetics is important in the preclinical stage. Values for total clearance of compounds from plasma should be one of the most important pharmacokinetic parameters for predictions. Although several physiological and empirical methods including single-species allometry for prediction of values for human clearance of compounds using humanized-liver mice have been reported, further improvement of prediction accuracies would be still expected. To optimize these approaches, we proposed methods for unbound intrinsic clearance in virtually 100% humanized-liver mouse by incorporating unbound plasma fractions of compounds in differently humanized-liver mice. Comparisons of prediction accuracies of values for human clearance of 15 model compounds were performed among our current physiological and previously reported models and single-species allometry using humanized-liver mice. Incorporation of the actual unbound plasma fractions of compounds and correction of residual mice hepatocyte in humanized-liver mice showed comparable prediction accuracy to that by single-species allometry. After exclusion of 3 compounds with large species differences in values of clearance and unbound plasma fractions between mice and humans out of 15 compounds, prediction accuracies were improved in the methods investigated. The previously and present reported physiological methods could show the good prediction accuracy of values for clearance of drugs from plasma.

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.

Thanks to highly active antiretroviral treatments, HIV infection is now considered as a chronic condition. Consequently, people living with HIV (PLWH) live longer and encounter more age-related chronic co-morbidities, notably cardiovascular diseases, leading to polypharmacy. As the management of drug-drug interactions (DDIs) constitutes a key aspect of the care of PLWH, the magnitude of pharmacokinetic DDIs between cardiovascular and anti-HIV drugs needs to be more thoroughly characterized. To that endeavour, an UHPLC-MS/MS bioanalytical method has been developed for the simultaneous determination in human plasma of amlodipine, metoprolol, pravastatin, rosuvastatin, atorvastatin and its active metabolites. Plasma samples were subjected to protein precipitation with methanol, followed by evaporation at room temperature under nitrogen of the supernatant, allowing to attain measurable plasma concentrations down to sub-nanogram per milliliter levels. Stable isotope-labelled analytes were used as internal standards. The five drugs and two metabolites were analyzed using a 6-min liquid chromatographic run coupled to electrospray triple quadrupole mass spectrometry detection. The method was validated over the clinically relevant concentrations ranging from 0.3 to 480 ng/mL for amlodipine, atorvastatin and p-OH-atorvastatin, and 0.4 to 480 ng/mL for pravastatin, 0.5 to 480 ng/mL for rosuvastatin and o-OH-atorvastatin, and 3 to 4800 ng/mL for metoprolol. Validation performances such as trueness (95.4-110.8%), repeatability (1.5-13.4%) and intermediate precision (3.6-14.5%) were in agreement with current international recommendations. Accuracy profiles (total error approach) were lying within the limits of ±30% accepted in bioanalysis. This rapid and robust UHPLC-MS/MS assay allows the simultaneous quantification in plasma of the major currently used cardiovascular drugs and offers an efficient analytical tool for clinical pharmacokinetics as well as DDIs studies.

Organic Anion Transporter Polypeptide 1B1 Polymorphism Modulates the Extent of Drug-Drug Interaction and Associated Biomarker Levels in Healthy Volunteers.

Understanding transporter-mediated drug-drug interactions is an integral part of risk assessment in drug development. Recent studies support the use of hexadecanedioate (HDA), tetradecanedioate (TDA), coproporphyrin (CP)-I, and CP-III as clinical biomarkers for evaluating organic anion-transporting polypeptide (OATP)1B1 (SLCO1B1) inhibition. The current study investigated the effect of OATP1B1 genotype c.521T>C (OATP1B1-Val174Ala) on the extent of interaction between cyclosporin A (CsA) and pravastatin, and associated endogenous biomarkers of the transporter (HDA, TDA, CP-I, and CP-III), in 20 healthy volunteers. The results show that the levels of each clinical biomarker and pravastatin were significantly increased in plasma samples of the volunteers following administration of pravastatin plus CsA compared with pravastatin plus placebo. The overall fold change in the area under the concentration-time curve (AUC) and maximum plasma concentration (Cmax ) was similar among the four biomarkers (1.8-2.5-fold, paired t-test P value < 0.05) in individuals who were homozygotes or heterozygotes of the major allele, c.521T. However, the fold change in AUC and Cmax for HDA and TDA was significantly abolished in the subjects who were c.521-CC, whereas the respective fold change in AUC and Cmax for pravastatin and CP-I and CP-III were slightly weaker in individuals who were c.521-CC compared with c.521-TT/TC genotypes. In addition, this study provides the first evidence that SLCO1B1 c.521T>C genotype is significantly associated with CP-I but not CP-III levels. Overall, these results suggest that OATP1B1 genotype can modulate the effects of CsA on biomarker levels; the extent of modulation differs among the biomarkers.

Effects of Uremic Serum Residue on OATP1B1- and OATP1B3-Mediated Pravastatin Uptake in OATP-Expressing HEK293 Cells and Human Hepatocytes.

Patients with end-stage renal disease have increased plasma concentrations of statins, which is a risk factor for rhabdomyolysis, as well as elevated levels of uremic toxins (UTs). We investigated the effects of uremic serum residue and UTs on organic anion-transporting peptide (OATP1B1)- and OATP1B3-mediated pravastatin uptake. We evaluated the effects of normal serum residue with four UTs (hippuric acid, 3-carboxy-4-methyl-5-propyl-2-furan propionate, indole-3-acetic acid, and 3-indoxyl sulfate) and uremic serum residue on pravastatin uptake by OATP1B1- or OATP1B3-expressing HEK293 cells. Furthermore, we assessed the contribution of each transporter using cryopreserved human hepatocytes. Uremic serum residue and UTs significantly inhibited OATP1B1-mediated pravastatin uptake. Uremic serum residue accelerated OATP1B3-mediated pravastatin uptake, while UTs had no effect. There was no difference in pravastatin uptake between uremic- and normal serum residue-treated hepatocytes. The results suggest that the effects of uremic serum on pravastatin hepatic uptake may be considered negligible in end-stage renal disease patients.

Interaction of statins with phospholipid bilayers studied by solid-state NMR spectroscopy.

Statins are drugs that specifically inhibit the enzyme HMG-CoA reductase and thereby reduce the concentration of low-density lipoprotein cholesterol, which represents a well-established risk factor for the development of atherosclerosis. The results of several clinical trials have shown that there are important intermolecular differences responsible for the broader pharmacologic actions of statins, even beyond HMG-CoA reductase inhibition. According to one hypothesis, the biological effects exerted by these compounds depend on their localization in the cellular membrane. The aim of the current work was to study the interactions of different statins with phospholipid membranes and to investigate their influence on the membrane structure and dynamics using various solid-state NMR techniques. Using 1H NOESY MAS NMR, it was shown that atorvastatin, cerivastatin, fluvastatin, rosuvastatin, and some percentage of pravastatin intercalate the lipid-water interface of POPC membranes to different degrees. Based on cross-relaxation rates, the different average distribution of the individual statins in the bilayer was determined quantitatively. Investigation of the influence of the investigated statins on membrane structure revealed that lovastatin had the least effect on lipid packing and chain order, pravastatin significantly lowered lipid chain order, while the other statins slightly decreased lipid chain order parameters mostly in the middle segments of the phospholipid chains.

Assessment of OATP transporter-mediated drug-drug interaction using physiologically-based pharmacokinetic (PBPK) modeling - a case example.

GDC-0810 was under development as an oral anti-cancer drug for the treatment of estrogen receptor-positive breast cancer as a single agent or in combination. In vitro data indicated that GDC-0810 is a potent inhibitor of OATP1B1/1B3. To assess clinical risk, a PBPK model was developed to predict the transporter drug-drug interaction (tDDI) between GDC-0810 and pravastatin in human. The PBPK model was constructed in Simcyp® by integrating in vitro and in vivo data for GDC-0810. The prediction of human pharmacokinetics (PK) was verified using GDC-0810 phase I clinical PK data. The Simcyp transporter DDI model was verified using known OATP1B1/1B3 inhibitors (rifampicin, cyclosporine and gemfibrozil) and substrate (pravastatin), prior to using the model to predict GDC-0810 tDDI. The effect of GDC-0810 on pravastatin PK was then predicted based on the proposed clinical scenarios. Sensitivity analysis was conducted on the parameters with uncertainty. The developed PBPK model described the PK profile of GDC-0810 reasonably well. In the tDDI verification, the model reasonably predicted pravastatin tDDI caused by rifampicin and gemfibrozil OATP1B1/3 inhibition but under-predicted tDDI caused by cyclosporine. The effect of GDC-0810 on pravastatin PK was predicted to be low to moderate (pravastatin Cmax ratios 1.01-2.05 and AUC ratio 1.04-2.23). The observed tDDI (Cmax ratio 1.20 and AUC ratio 1.41) was within the range of the predicted values. This work demonstrates an approach using a PBPK model to prospectively assess tDDI caused by a new chemical entity as an OATP1B1/3 uptake transporter inhibitor to assess clinical risk and to support development strategy.

Effect of OATP1B1/1B3 Inhibitor GDC-0810 on the Pharmacokinetics of Pravastatin and Coproporphyrin I/III in Healthy Female Subjects.

Developed as an oral anticancer drug to treat estrogen receptor-positive breast cancer, GDC-0810 was shown to be a potent inhibitor of organic anion-transporting polypeptide 1B1 and 1B3 (OATP1B1/1B3) from an in vitro assay. A clinical study was conducted to assess the drug-drug interaction potential between GDC-0810 and pravastatin, which is a relatively selective and sensitive OATP1B1/1B3 substrate. Fifteen healthy female subjects of non-childbearing potential were enrolled in the study. On day 1 in period 1, a single 10-mg dose of pravastatin was administered to all subjects. Following a 4-day washout period, 600 mg of GDC-0810 was administered once daily on days 5 through 8 in period 2 to achieve steady-state concentrations. On day 7, a single dose of 10-mg pravastatin was coadministered with the 600-mg GDC-0810 dose. Concentrations of pravastatin (periods 1 and 2) and GDC-0810 (period 2 only) were quantified in blood samples and subsequently used to calculate the pharmacokinetics (PK) parameters. The pravastatin mean maximal concentration and area under the curve values were approximately 20% and 41% higher, respectively, following pravastatin coadministration with GDC-0810 compared to pravastatin alone. Based on the magnitude of change in this drug-drug interaction study, dose adjustments for pravastatin (and other OATP1B1/1B3 substrates) were not considered necessary when administered with GDC-0810. Retrospectively, the endogenous biomarkers of OATP1B1/1B3, coproporphyrin I and III, were also measured and showed changes comparable to those of pravastatin, indicating their utility in detecting weak inhibition of OATP1B1/1B3 in the clinical setting.

Prediction of the Pharmacokinetics of Pravastatin as an OATP Substrate Using Plateable Human Hepatocytes With Human Plasma Data and PBPK Modeling.

Plateable human hepatocytes with human plasma were utilized to generate the uptake transporter kinetic data for pravastatin, an organic anion-transporting polypeptide (OATP) transporter substrate. The active hepatic uptake of pravastatin was determined with a Jmax value of 134.4 pmol/min/million cells and Km of 76.77 µM in plateable human hepatocytes with human plasma. The physiologically-based pharmacokinetic (PBPK) model with incorporation of these in vitro kinetic data successfully simulated the i.v. pharmacokinetic profile of pravastatin without applying scaling factor (the mean predicted area under the curve (AUC) is within 1.5-fold of the observed). Furthermore, the PBPK model also adequately described the oral plasma concentration-time profiles of pravastatin at different dose levels. The current investigation demonstrates an approach allowing us to build upon the translation of in vitro OATP uptake transporter data to in vivo, with a hope of utilizing the in vitro data for the prospective human pharmacokinetic (PK) prediction.

Effect of inhalation exposure to toluene on the activity of organic anion transporting polypeptide (Oatp) using pravastatin as a probe drug in rats.

1. Toluene, used as a pure substance or in solvent mixtures, is the cause of occupational exposures of large numbers of workers in the world. The organic anion transporting polypeptides (OATP: human; Oatp: rodents) are drug carriers which have been frequently associated to drug-drug interactions. The objective of this study was to evaluate the influence of inhalation exposure to toluene in Oatp in vivo activity using pravastatin as a probe drug in rats. 2. Male Wistar rats ((n = 6 per sampling time) were exposed to 85 mg/m3 toluene by inhalation or air in a nose only exposure system for 6 h/d, 5 d/week during 4 weeks, in order to simulate the occupational exposure to toluene at level slightly above the occupational exposure limit proposed by the American Conference of Governmental Industrial Hygienists (ACGIH). After 4 weeks of exposure, animals received a single dose of 20 mg/kg pravastatin orally. 3. Areas under concentration × time curves extrapolated to infinite (AUC0-∞) were calculated by Gauss Laguerre quadrature. Non-exposed animals showed AUC0-∞ of 726.0 (261.8) ng h/mL for pravastatin and rats exposed to toluene 85 mg/m3 showed AUC0-∞ of 681.8 (80.1) ng h/mL [data presented as mean (standard error of the mean)]. No significant difference was observed in pravastatin kinetic disposition between groups in terms of 95% confidence interval for the difference between means. 4. Toluene exposure by inhalation did not change the in vivo activity of Oatp evaluated by pravastatin kinetic disposition in rats.

Explaining Ethnic Variability of Transporter Substrate Pharmacokinetics in Healthy Asian and Caucasian Subjects with Allele Frequencies of OATP1B1 and BCRP: A Mechanistic Modeling Analysis.

BACKGROUND: Ethnic variability in the pharmacokinetics of organic anion transporting polypeptide (OATP) 1B1 substrates has been observed, but its basis is unclear. A previous study hypothesizes that, without applying an intrinsic ethnic variability in transporter activity, allele frequencies of transporters cannot explain observed ethnic variability in pharmacokinetics. However, this hypothesis contradicts the data collected from compounds that are OATP1B1 substrates but not breast cancer resistance protein (BCRP) substrates. OBJECTIVE: The objective of this study is to evaluate a hypothesis that is physiologically reasonable and more consistent with clinical observations. METHODS: We evaluated if allele frequencies of two transporters (OATP1B1 and BCRP) are key contributors to ethnic variability. In this hypothesis, the same genotype leads to the same activity independent of ethnicity, in contrast to the previous hypothesis of intrinsic ethnic variability in OATP1B1 activity. As a validation, we perform mechanistic pharmacokinetic modeling for SLCO1B1 (encoding OATP1B1) and ABCG2 (encoding BCRP) genotyped pharmacokinetic data from 18 clinical studies with healthy Caucasian and/or Asian subjects. RESULTS: Simulations based on the current hypothesis reasonably describe SLCO1B1 and ABCG2 genotyped pharmacokinetic time course data for five transporter substrates (atorvastatin, pitavastatin, pravastatin, repaglinide, and rosuvastatin) in Caucasian and Asian populations. CONCLUSION: This hypothesis covers the observations that can (e.g., ethnic differences in rosuvastatin pharmacokinetics) or cannot (e.g., lack of differences for pitavastatin pharmacokinetics) be explained by the previous hypothesis. It helps to characterize sources of ethnic variability and provides a foundation for predicting ethnic variability in transporter substrate pharmacokinetics.