Physiologically-Based Pharmacokinetic Modeling of Atorvastatin Incorporating Delayed Gastric Emptying and Acid-to-Lactone Conversion

Effect of Gastric pH on the Pharmacokinetics of Atorvastatin and its Metabolites in Healthy Participants

BACKGROUND AND OBJECTIVE

Atorvastatin is dosed in its active acid form although it exists in equilibrium with its inactive lactone form in vivo. Although in vitro atorvastatin acid displays pH-dependent conversion to the lactone metabolite, pharmacokinetic (PK) data on the effect of elevated gastric pH on atorvastatin and major atorvastatin-related species are not currently available. In this dedicated study, we investigated the effect of food and acid-reducing agents on the PK of atorvastatin and its three major metabolites in humans.

METHODS

This was an open label, randomized, crossover study conducted in 17 healthy volunteers. Part 1 examined the PK of a 10-mg dose of atorvastatin co-administered with or without a 600-mg dose of sodium bicarbonate in fasted and fed states. Part 2 was a single assessment to examine the PK of a 10-mg dose of atorvastatin in the fasted state following a 5-day treatment course of 40-mg daily esomeprazole. Gastric pH was monitored during treatments using Heidelberg capsules. A linear mixed effects model was used to derive ratios for PK parameters of atorvastatin and metabolites between treatments.

RESULTS

Similar to previous food effect studies, food significantly decreased the maximum concentration (Cmax) and increased the time to Cmax (tmax) of atorvastatin, with minimal effect on total exposure of atorvastatin or metabolites. Neither sodium bicarbonate, in the fed or fasted state, nor treatment with esomeprazole had a clinically meaningful effect on the exposure of atorvastatin or its metabolites.

CONCLUSIONS

According to these results, atorvastatin PK does not appear to be sensitive to changes in gastric pH.

Rat PermQ: A permeability- and perfusion-based physiologically based pharmacokinetic model for improved prediction of drug concentration-time profiles in rat

A new rat permeability- and perfusion-limited physiologically based pharmacokinetic model, "rat PermQ," was developed with the goal of improving concentration-time (C-t) predictions of drugs. Similar to the previously published human PermQ, drugs can reversibly distribute between capillaries and interstitial fluid by fenestra or discontinuities in capillaries or by transcellular diffusion through endothelial cells. Drugs also can be partitioned into intracellular phospholipids and neutral lipids in the cytosol. For acidic drugs, active uptake transport and an empirical protein binding correction factor were considered. A shallow distribution compartment was added for basic drugs to account for early distribution. In vitro and in vivo experimental inputs were collected in-house or from the literature. C-t profiles were predicted for 7 drugs (2 acidic, 2 neutral, and 3 basic) with 3 models: Rodgers and Rowland (RR), a perfusion-limited membrane-based model, and rat PermQ. Results indicate the importance of consistent, species-specific in vitro inputs. In general, rat PermQ predicted C-t profiles at least as well as the other models. For acidic drugs, rat PermQ predictions improved with incorporation of uptake transport and the empirical protein binding factor. For neutral drugs, RR predicted digoxin C-t profiles better compared with rat PermQ, while midazolam predictions with rat PermQ were improved with the use of in-house in vitro experimental inputs. Rat PermQ predicted C-t profiles for all 3 bases better than RR and perfusion-limited membrane-based model, and addition of a shallow compartment greatly improved the predictions. Rat and human PermQ allowed several hypotheses to be simulated for putative uptake mechanisms for atenolol and glyburide. SIGNIFICANCE STATEMENT: A new physiologically based pharmacokinetic framework, rat PermQ, was developed. This model predicted plasma concentration-time profiles of the tested drugs as well as or better than published physiologically based pharmacokinetic models. PermQ allowed several hypotheses to be simulated for uptake mechanisms in rats and humans. The work highlights the importance of accurate in vitro parameters such as drug plasma protein binding and blood-to-plasma ratio. The model can aid in testing new hypotheses to explain poorly understood observations in distribution and elimination of drugs.

Multi-omics characterization of type 2 diabetes mellitus-induced gastroenteropathy in the db/db mouse model

Objective

Gastrointestinal dysfunction are often associated with type 2 diabetes mellitus (T2DM), a complicated metabolic illness. Contributing factors have been proposed, including genetic predisposition, gene environmental, and lifestyle interactions, but the pathophysiology remains unknown.

Methods

We aim to explore the possible causes behind gastrointestinal dysfunction caused by type 2 diabetes in this study. A comprehensive analysis of the gastric sinus metabolome, transcriptome, and proteome in db/db mice with gastrointestinal dysfunction was conducted.

Results

The model group of mice had considerably lower small intestine propulsion and gastric emptying rates, higher blood glucose levels, and were significantly obese compared to the control group. We identified 297 genes, 350 proteins, and 1,001 metabolites exhibiting significant differences between db/db and control mice (p < 0.05). Moreover, multi-omics analysis revealed that the genes, proteins, and metabolites in the T2DM-induced gastroenteropathy mice group were involved in arachidonic acid metabolism, glycerophospholipid metabolism and vitamin digestion and absorption. Specifically, Cbr3, Etnppl, and Apob were the major mRNAs associated with T2DM-induced gastrointestinal dysfunction, while Cyp2b10, Cyp2b19, Pgs1, Gpat3, Apoa4, and Tcn2 were the major proteins associated with T2DM-induced gastrointestinal injury, and 16(R)-HET, 5-HETE, LysoPC (22:0), and Pantothenic acid were the major metabolites associated with T2DM-induced gastrointestinal disorders.

Conclusion

The mechanism of action of diabetic gastroenteropathy may be related to vitamin digestion and absorption, glycerophospholipid metabolism, and arachidonic acid metabolism.

Mechanistic Account of Distinct Change in Organic Anion Transporting Polypeptide 1B (OATP1B) Substrate Pharmacokinetics during OATP1B-Mediated Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling

The role of transporters in drug clearance is widely acknowledged, directly and indirectly by facilitating tissue/enzyme exposure. Through the latter, transporters also affect volume of distribution. Drug-drug interactions (DDIs) involving organic anion transporting polypeptides (OATPs) 1B1/1B3 and SLCO1B1 pharmacogenetics lead to altered pharmacokinetics of OATP1B substrates; however, several factors may confound direct interpretation of pharmacokinetic parameters from these clinical studies using noncompartmental analysis (NCA). A review of clinical data herein indicates a single dose of OATP1B inhibitor rifampin almost never leads to increased substrate half-life but often a decrease and that most clinical OATP1B substrates are CYP3A4 substrates and/or undergo enterohepatic cycling (EHC). Using hypothetically simple OATP1B substrate physiologically based pharmacokinetic (PBPK) models, simulated effect of rifampin differed from specific OATP1B inhibition due to short rifampin half-life causing dissipation of OATP1B inhibition over time combined with CYP3A4 induction. Calculated using simulated tissue data, volume of distribution indeed decreased with OATP1B inhibition and was expectedly limited to the contribution of liver volume. However, an apparent and counterintuitive effect of rifampin on volume greater than that on clearance resulted for CYP3A4 substrates using NCA. The effect of OATP1B inhibition and rifampin on OATP1B substrate models incorporating EHC plus or minus renal clearance was distinct compared with simpler models. Using PBPK models incorporating reversible lactone metabolism for clinical OATP1B substrates atorvastatin and pitavastatin, DDIs reporting decreased half-life with rifampin were reproduced. These simulations provide an explanation for the distinct change in OATP1B substrate pharmacokinetics observed in clinical studies, including changes in volume of distribution and additional mechanisms. SIGNIFICANCE STATEMENT: Transporters are involved in drug clearance and volume of distribution, and distinct changes in OATP1B substrate pharmacokinetics are observed with OATP1B inhibitor rifampin. Using hypothetical and validated PBPK models and simulations, this study addresses the limitations of single-dose rifampin and complicated clinical OATP1B substrate disposition in evaluating the pharmacokinetic parameters of OATP1B substrates during rifampin drug-drug interactions (DDIs). These models account for change in volume of distribution and identify additional mechanisms underlying apparent pharmacokinetic changes in OATP1B DDIs.

Mechanistic Static Model based Prediction of Transporter Substrate Drug-Drug Interactions Utilizing Atorvastatin and Rifampicin

OBJECTIVE

An in vitro relative activity factor (RAF) technique combined with mechanistic static modeling was examined to predict drug-drug interaction (DDI) magnitude and analyze contributions of different clearance pathways in complex DDIs involving transporter substrates. Atorvastatin and rifampicin were used as a model substrate and inhibitor pair.

METHODS

In vitro studies were conducted with transfected HEK293 cells, hepatocytes and human liver microsomes. Prediction success was defined as predictions being within twofold of observations.

RESULTS

The RAF method successfully translated atorvastatin uptake from transfected cells to hepatocytes, demonstrating its ability to quantify transporter contributions to uptake. Successful translation of atorvastatin's in vivo intrinsic hepatic clearance (CLint,h,in vivo) from hepatocytes to liver was only achieved through consideration of albumin facilitated uptake or through application of empirical scaling factors to transporter-mediated clearances. Transporter protein expression differences between hepatocytes and liver did not affect CLint,h,in vivo predictions. By integrating cis and trans inhibition of OATP1B1/OATP1B3, atorvastatin-rifampicin (single dose) DDI magnitude could be accurately predicted (predictions within 0.77-1.0 fold of observations). Simulations indicated that concurrent inhibition of both OATP1B1 and OATP1B3 caused approximately 80% of atorvastatin exposure increases (AUCR) in the presence of rifampicin. Inhibiting biliary elimination, hepatic metabolism, OATP2B1, NTCP, and basolateral efflux are predicted to have minimal to no effect on AUCR.

CONCLUSIONS

This study demonstrates the effective application of a RAF-based translation method combined with mechanistic static modeling for transporter substrate DDI predictions and subsequent mechanistic interpretation.

PBPK Modeling of Azithromycin Systemic Exposure in a Roux-en-Y Gastric Bypass Surgery Patient Population

In this investigation, PBPK modeling using the Simcyp® Simulator was performed to evaluate whether Roux-en-Y gastric bypass (RYGB) surgery impacts the oral absorption and bioavailability of azithromycin. An RYGB surgery patient population was adapted from the published literature and verified using the same probe medications, atorvastatin and midazolam. Next, a PBPK model of azithromycin was constructed to simulate changes in systemic drug exposure after the administration of different oral formulations (tablet, suspension) to patients pre- and post-RYGB surgery using the developed and verified population model. Clinically observed changes in azithromycin systemic exposure post-surgery following oral administration (single-dose tablet formulation) were captured using PBPK modeling based on the comparison of model-predicted exposure metrics (Cmax, AUC) to published clinical data. Model simulations predicted a 30% reduction in steady-state AUC after surgery for three- and five-day multiple dose regimens of an azithromycin tablet formulation. The relative bioavailability of a suspension formulation was 1.5-fold higher than the tablet formulation after multiple dosing. The changes in systemic exposure observed after surgery were used to evaluate the clinical efficacy of azithromycin against two of the most common pathogens causing community acquired pneumonia based on the corresponding AUC24/MIC pharmacodynamic endpoint. The results suggest lower bioavailability of the tablet formulation post-surgery may impact clinical efficacy. Overall, the research demonstrates the potential of a PBPK modeling approach as a framework to optimize oral drug therapy in patients post-RYGB surgery.

Therapeutic Protein Drug Interactions: A White Paper From the International Consortium for Innovation and Quality in Pharmaceutical Development

Typically, therapeutic proteins (TPs) have a low risk for eliciting meaningful drug interactions (DIs). However, there are select instances where TP drug interactions (TP-DIs) of clinical concern can occur. This white paper discusses the various types of TP-DIs involving mechanisms such as changes in disease state, target-mediated drug disposition, neonatal Fc receptor (FcRn), or antidrug antibodies formation. The nature of TP drug interaction being investigated should determine whether the examination is conducted as a standalone TP-DI study in healthy participants, in patients, or assessed via population pharmacokinetic analysis. DIs involving antibody-drug conjugates are discussed briefly, but the primary focus here will be DIs involving cytokine modulation. Cytokine modulation can occur directly by certain TPs, or indirectly due to moderate to severe inflammation, infection, or injury. Disease states that have been shown to result in indirect disease-DIs that are clinically meaningful have been listed (i.e., typically a twofold change in the systemic exposure of a coadministered sensitive cytochrome P450 substrate drug). Type of disease and severity of inflammation should be the primary drivers for risk assessment for disease-DIs. While more clinical inflammatory marker data needs to be collected, the use of two or more clinical inflammatory markers (such as C-reactive protein, albumin, or interleukin 6) may help broadly categorize whether the predicted magnitude of inflammatory disease-DI risk is negligible, weak, or moderate to strong. Based on current knowledge, clinical DI studies are not necessary for all TPs, and should no longer be conducted in certain disease patient populations such as psoriasis, which do not have sufficient systemic inflammation to cause a meaningful indirect disease-DI.

QiShenYiQi pills, a Chinese patent medicine, increase bioavailability of atorvastatin by inhibiting Mrp2 expression in rats

CONTEXT

Atorvastatin (ATV) and QiShenYiQi pills (QSYQ), a Chinese patent medicine, are often co-prescribed to Chinese cardiovascular patients. The effects of QSYQ on the pharmacokinetics of ATV have not been studied.

OBJECTIVE

We investigated the influence of QSYQ on the pharmacokinetics of ATV and its metabolites upon oral or intravenous administration of ATV to rats.

MATERIALS AND METHODS

Sprague-Dawley rats (n = 5/group) were pre-treated with oral QSYQ (675 mg/kg) or vehicle control for 7 days and then orally administrated ATV (10 mg/kg) or intravenously administrated ATV (2 mg/kg). Serum concentrations of ATV and metabolites were determined by ultra-high performance liquid chromatography tandem mass spectrometry. Expression of metabolic enzymes and transporters in jejunum and ileum were measured by quantitative real-time PCR and Western blot.

RESULTS

QSYQ resulted in an increase of AUC_0-12 h of ATV from 226.67 ± 42.11 to 408.70 ± 161.75 ng/mL/h and of C_max of ATV from 101.46 ± 26.18 to 198.00 ± 51.69 ng/mL and in an increased of para-hydroxy atorvastatin from 9.07 ± 6.20 to 23.10 ± 8.70 ng/mL in rats administered ATV orally. No change was observed in rats treated intravenously. The expression of multidrug resistance-associated protein 2 mRNA and protein decreased in ileum, and the mRNA of P-glycoprotein decreased in jejunum, though no change in protein expression was found.

DISCUSSION AND CONCLUSIONS

QSYQ increased bioavailability of ATV administered orally through inhibiting the expression of Mrp2 in ileum. Clinicians should pay close attention to potential drug-drug interactions between ATV and QSYQ.

Population pharmacokinetic of paracetamol and atorvastatin with co-administration of semaglutide

Semaglutide is a glucagon-like-peptide-1 (GLP-1) analogue marketed for once-weekly subcutaneous administration for type 2 diabetes mellitus. Like other long-acting GLP-1 analogues, semaglutide reduces gastric emptying and, potentially, alters the rate of absorption of orally co-administered drugs. The objective of the current analysis was to evaluate the effects on the gastric emptying rate caused by semaglutide on pharmacokinetic model parameters of paracetamol and atorvastatin in healthy subjects. Non-linear mixed effect modeling was used to estimate population pharmacokinetic model parameters of paracetamol and atorvastatin after single doses with or without semaglutide. The absorption rate (ka) of paracetamol decreased by 53% when co-administered with semaglutide. For atorvastatin, ka and transit compartment rate (ktr) decreased by 72% and 91%, respectively. Thus, gastric emptying, measured as T50, i.e., drug disappearance from the absorption compartments, showed an additional 5-min delay for paracetamol and a 67-min delay for atorvastatin when co-administered with semaglutide. Semaglutide affected pharmacokinetic model parameters of paracetamol and atorvastatin, and minor quantitative differences in gastric emptying between placebo vs. semaglutide administration were observed. However, these effects of semaglutide were considered not to be of clinical relevance.

Enhancing Atorvastatin In Vivo Oral Bioavailability in the Presence of Inflammatory Bowel Disease and Irritable Bowel Syndrome Using Supercritical Fluid Technology Guided by wbPBPK Modeling in Rat and Human

Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are common disorders that can change the body's physiology and drugs pharmacokinetics. Solid dispersion (SD) preparation using supercritical fluid technology (SFT) has many advantages. Our study aimed to explore the effect of IBS and IBD on atorvastatin (ATV) pharmacokinetics, enhance ATV oral bioavailability (BCS II drug) using SFT, and analyze drug-disease-formulation interaction using a whole-body physiologically based pharmacokinetic (wbPBPK) model in rat and human. A novel ATV formulation was prepared using SFT and characterized in vitro and in vivo in healthy, IBS, and IBD rats. The resulting ATV plasma levels were analyzed using a combination of conventional and wbPBPK approaches. The novel formulation increased ATV solubility by 20-fold and resulted in a zero-order release of up to 95%. Both IBS and IBD increased ATV exposure after oral and intravenous administration by more than 30%. The novel SFT formulation increased ATV bioavailability by 28, 14, and 18% in control, IBD, and IBD rat groups and resulted in more consistent exposure as compared to raw ATV solution. Higher improvements in ATV bioavailability of more than 2-fold upon receiving the novel SFT formulation were predicted by the human wbPBPK model as compared to receiving the conventional tablets. Finally, the established wbPBPK model could describe ATV ADME in the presence of IBS and IBD after oral administration of raw ATV and using the novel SFT formula and can help scale the optimized ATV dosing regimens in the presence of IBS and IBD from rats to humans.

Atorvastatin population pharmacokinetics in a real-life setting: Influence of genetic polymorphisms and association with clinical response

The purpose of this study was to investigate the potential clinical relevance of estimating the apparent clearance (CL/F) of atorvastatin through population pharmacokinetic (PopPK) modeling with samples collected in a real-life setting in a cohort of ambulatory patients at risk of cardiovascular disease by using an opportunistic sampling strategy easily accessible in clinical routine. A total of 132 pharmacokinetic (PK) samples at a maximum of three visits were collected in the 70 included patients. The effects of demographic, genetic, and clinical covariates were also considered. With the collected data, we developed a two-compartment PopPK model that allowed estimating atorvastatin CL/F relatively precisely and considering the genotype of the patient for SLCO1B1 c.521T>C single-nucleotide polymorphism (SNP). Our results indicate that the estimation of the CL/F of atorvastatin through our PopPK model might help in identifying patients at risk of myalgia. Indeed, we showed that a patient presenting a CL/F lower than 414.67 L h-1 is at risk of suffering from muscle discomfort. We also observed that the CL/F was correlated with the efficacy outcomes, suggesting that a higher CL/F is associated with a better drug efficacy (i.e., a greater decrease in total and LDL-cholesterol levels). In conclusion, our study demonstrates that PopPK modeling can be useful in daily clinics to estimate a patient' atorvastatin clearance. Notifying the clinician with this information can help in identifying patients at risk of myalgia and gives indication about the potential responsiveness to atorvastatin therapy.

Lilly Absorption Modeling Platform: A Tool for Early Absorption Assessment

Oral drug absorption modeling has developed at a rapid pace in the 40 years or so since the first ideas for mathematical approaches to oral absorption were introduced. The success of compartmental approaches accelerated the uptake of absorption modeling, and over the last 20 years, work on absorption modeling has shifted almost exclusively to the compartmental framework. This report describes a new noncompartmental absorption modeling framework, the Lilly Absorption Modeling Platform (LAMP). LAMP connects a well-mixed stomach to a continuous tube model of the small intestine with plug flow. Within the continuous tube framework, the model includes intestinal mixing and a novel highly tunable precipitation model that can describe a combination of rapid nucleation and slow growth. The framework is designed to balance speed, consistency, and ease of use with a minimum of model complexity to capture the essential features of gastrointestinal (GI) physiology and critical elements of the oral absorption process. The model was validated based on predictions of the fraction absorbed and the maximum absorbable dose for a set of Eli Lilly and Company clinical compounds.

Current Evidence, Challenges, and Opportunities of Physiologically Based Pharmacokinetic Models of Atorvastatin for Decision Making

Atorvastatin (ATS) is the gold-standard treatment worldwide for the management of hypercholesterolemia and prevention of cardiovascular diseases associated with dyslipidemia. Physiologically based pharmacokinetic (PBPK) models have been positioned as a valuable tool for the characterization of complex pharmacokinetic (PK) processes and its extrapolation in special sub-groups of the population, leading to regulatory recognition. Several PBPK models of ATS have been published in the recent years, addressing different aspects of the PK properties of ATS. Therefore, the aims of this review are (i) to summarize the physicochemical and pharmacokinetic characteristics involved in the time-course of ATS, and (ii) to evaluate the major highlights and limitations of the PBPK models of ATS published so far. The PBPK models incorporate common elements related to the physicochemical aspects of ATS. However, there are important differences in relation to the analyte evaluated, the type and effect of transporters and metabolic enzymes, and the permeability value used. Additionally, this review identifies major processes (lactonization, P-gp contribution, ATS-Ca solubility, simultaneous management of multiple analytes, and experimental evidence in the target population), which would enhance the PBPK model prediction to serve as a valid tool for ATS dose optimization.

Sensitive, High-Throughput Liquid Chromatography-Tandem Mass Spectrometry Analysis of Atorvastatin and Its Pharmacologically Active Metabolites in Serum for Supporting Precision Pharmacotherapy

The antihyerlipidemic drug atorvastatin (ATR) is used worldwide as part of the strategy to prevent cardiovascular events. The high prevalence of patient nonadherence remains an important challenge which could be addressed efficiently by precision pharmacotherapy based on therapeutic drug monitoring (TDM). ATR is metabolized to pharmacologically active metabolites, and evidence shows that the sums of ATR acid and lactone form concentrations (ATR + ATRL), or of ATR and hydroxylated metabolites (ATR + MET) should be assayed. A method is presented for the analysis of these substances in serum. Method validation included the estimation of the quantitative relationship between the concentrations and the standard deviations (SD), which supports the optimal incorporation of TDM results into nonparametric pharmacokinetic models. The concentrations of the analytes were evaluated in human subjects receiving ATR. The method's performance improved by taking the sums of acid and lactone concentrations into account. The concentration-SD relationship was linear, and we recommend applying Theil's regression for estimating the assay error. All analytes could be detected by 2 h post dose in the samples of human subjects. The changes in metabolite/parent drug concentration ratios in time depended on the dose. The method is suitable for the TDM of ATR with a focus on precision pharmacotherapy.

Prediction of Cyclosporin-Mediated Drug Interaction Using Physiologically Based Pharmacokinetic Model Characterizing Interplay of Drug Transporters and Enzymes

Uptake transporter organic anion transporting polypeptides (OATPs), efflux transporters (P-gp, BCRP and MRP2) and cytochrome P450 enzymes (CYP450s) are widely expressed in the liver, intestine or kidney. They coordinately work to control drug disposition, termed as "interplay of transporters and enzymes". Cyclosporine A (CsA) is an inhibitor of OATPs, P-gp, MRP2, BCRP and CYP3As. Drug-drug interaction (DDI) of CsA with victim drugs occurs via disordering interplay of transporters and enzymes. We aimed to establish a whole-body physiologically-based pharmacokinetic (PBPK) model which predicts disposition of CsA and nine victim drugs including atorvastatin, cerivastatin, pravastatin, rosuvastatin, fluvastatin, simvastatin, lovastatin, repaglinide and bosentan, as well as drug-drug interactions (DDIs) of CsA with nine victim drugs to investigate the integrated effect of enzymes and transporters in liver, intestinal and kidney on drug disposition. Predictions were compared with observations. Most of the predictions were within 0.5-2.0 folds of observations. Atorvastatin was represented to investigate individual contributions of transporters and CYP3As to atorvastatin disposition and their integrated effect. The contributions to atorvastatin disposition were hepatic OATPs >> hepatic CYP3A > intestinal CYP3As ≈ efflux transporters (P-gp/BCRP/MRP2). The results got the conclusion that the developed PBPK model characterizing the interplay of enzymes and transporters was successfully applied to predict the pharmacokinetics of 10 OATP substrates and DDIs of CsA with 9 victim drugs.

The Necessity of Using Changes in Absorption Time to Implicate Intestinal Transporter Involvement in Oral Drug-Drug Interactions

INTRODUCTION

In drug discovery and development, it is of high interest to characterize the potential for intestinal drug-drug interactions to alter bioavailability of a victim drug. For drugs that are substrates of both intestinal transporters and enzymes, estimating the relative contribution of each process has proved challenging, especially since the susceptibility of drug to uptake or efflux transporters in vitro does not always translate to clinically significant in vivo involvement. Here we introduce a powerful methodology to implicate intestinal transporters in drug-drug interactions based on the theory that clinically relevant intestinal transporter interactions will result in altered rate of absorption of victim drugs.

METHODS AND MATERIALS

We present exemplary clinical drug-drug interaction studies that utilize well-characterized clinical substrates and perpetrators to demonstrate how mean absorption time (MAT) and time to maximum concentration (t_max) are expected to change (or remain unchanged) when either intestinal transporters or metabolic enzymes were/are altered. Apixaban was also selected to demonstrate the utility of the methodology, as the purported involvement of both intestinal enzymes and transporters has been suggested in its FDA package insert.

RESULTS AND DISCUSSION

Acute inhibition of gut efflux transporters resulted in decreased MAT and t_maxvalues, induction increased these values, while inhibition of intestinal metabolic enzymes did not result in altered MAT or t_max. Involvement of intestinal efflux transporters in apixaban disposition is unlikely.

CONCLUSION

Utilization of this simple but powerful methodology to implicate intestinal transporter involvement will have significant impact on how drug-drug interactions are interpreted.

Effects of Green Tea Extract on Atorvastatin Pharmacokinetics in Healthy Volunteers

BACKGROUND AND OBJECTIVES

Green tea catechins were recently reported to inhibit drug transporters such as organic anion-transporting polypeptides (OATPs) and metabolic enzymes, affecting the bioavailability of many drugs. This study aimed to evaluate the clinical significance of the effects of different doses of green tea extract on the pharmacokinetic parameters of atorvastatin and to rationalize the associated interaction mechanism.

METHODS

A randomized, double-blind, three-phase crossover study involving 12 healthy volunteers was performed. Participants received a single dose of atorvastatin 40 mg alone (control group), atorvastatin 40 mg plus a capsule containing 300 mg of dry green tea extract, or atorvastatin 40 mg plus a capsule containing 600 mg of dry green tea extract. Plasma samples taken from the volunteers were analyzed for atorvastatin using liquid chromatography-tandom mass spectrometry (LC/MS/MS).

RESULTS

Compared to atorvastatin alone, the administration of 300 mg or 600 mg of the green tea extract along with atorvastatin decreased the peak plasma concentration (C_max) of atorvastatin by 25% and 24%, respectively (P < 0.05), and the area under the plasma concentration-time curve (AUC_0-∞) of atorvastatin by 24% and 22%, respectively (P < 0.05). Additionally, administration of 300 mg or 600 mg of the green tea extract increased the apparent oral clearance (CL/F) of atorvastatin by 31% and 29%, respectively. The time to C_max (T_max) and the elimination half-life (t_1/2) of atorvastatin did not differ among the three phases. The effects of 600 mg of the green tea extract on the pharmacokinetic parameters of atorvastatin were not significantly different from the effects of 300 mg of the green tea extract.

CONCLUSION

Green tea extract decreases the absorption but not the elimination of atorvastatin, possibly by inhibiting OATP, albeit not in a dose-dependent manner. Coadministration of green tea extract with atorvastatin may necessitate the monitoring of the plasma concentration of atorvastatin in clinical practice.

A hybrid model to evaluate the impact of active uptake transport on hepatic distribution of atorvastatin in rats

1. Mathematical modeling remains a useful tool to study the impact of transporters on overall and intracellular drug disposition. The impact of organic anion transporter protein mediated uptake on atorvastatin systemic and intracellular pharmacokinetics, specifically distribution volume, was studied in rats with mathematical modeling and conducting in vivo pharmacokinetic studies for atorvastatin in presence and absence of rifampicin. A previously developed 5-compartment explicit membrane model for the liver was combined with a compartmental model to develop a semi-physiological hybrid model for atorvastatin disposition. 2. Rifampicin treatment resulted in a decrease in systemic clearance and steady-state distribution volume, and an increase in half-life of atorvastatin. The hybrid model predicted higher unbound intracellular liver atorvastatin concentrations than unbound plasma concentrations in both rifampicin treated and untreated groups, indicating involvement of uptake transporters. The intracellular unbound concentrations during the distributive phase were unaffected by rifampicin. The dependence of clearance on blood flow as well as hepatic uptake for atorvastatin (a moderate-to-high extraction ratio drug) can explain this lack of change in intracellular concentrations if there is incomplete inhibition of transport at the tested rifampicin dose. 3. The hybrid model successfully allowed the evaluation of effect of active uptake on intracellular and plasma atorvastatin disposition.

Prediction of pharmacokinetic drug-drug interactions causing atorvastatin-induced rhabdomyolysis using physiologically based pharmacokinetic modelling

Atorvastatin and its lactone form metabolite are reported to be associated with statin-induced myopathy (SIM) such as myalgia and life-threatening rhabdomyolysis. Though the statin-induced rhabdomyolysis is not common during statin therapy, its incidence will significantly increase due to pharmacokinetic drug-drug interactions (DDIs) with inhibitor drugs which inhibit atorvastatin's and its lactone's metabolism and hepatic uptake. Thus, the quantitative analysis of DDIs of atorvastatin and its lactone with cytochrome P450 3A4 (CYP3A4) and organic anion-transporting polypeptide (OATP) inhibitors is of great importance. This study aimed to predict pharmacokinetic DDIs possibly causing atorvastatin-induced rhabdomyolysis using Physiologically Based Pharmacokinetic (PBPK) Modelling. Firstly, we refined the PBPK models of atorvastatin and atorvastatin lactone for predicting the DDIs with CYP3A4 and OATP inhibitors. Thereafter, we predicted the exposure changes of atorvastatin and atorvastatin lactone originating from the case reports of atorvastatin-induced rhabdomyolysis using the refined models. The simulation results show that pharmacokinetic DDIs of atorvastatin and its lactone with fluconazole, palbociclib diltiazem and cyclosporine are significant. Consequently, clinicians should be aware of necessary dose adjustment of atorvastatin being used with these four inhibitor drugs.