Effects of grapefruit juice and SLCO1B1 388A>G polymorphism on the pharmacokinetics of pitavastatin

Physiologically based pharmacokinetic (PBPK) modeling of pitavastatin in relation to SLCO1B1 genetic polymorphism

Pitavastatin, a potent 3-hydroxymethylglutaryl coenzyme A reductase inhibitor, is indicated for the treatment of hypercholesterolemia and mixed dyslipidemia. Hepatic uptake of pitavastatin is predominantly occupied by the organic anion transporting polypeptide 1B1 (OATP1B1) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is a polymorphic gene that encodes OATP1B1. SLCO1B1 genetic polymorphism significantly alters the pharmacokinetics of pitavastatin. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict pitavastatin pharmacokinetics according to SLCO1B1 genetic polymorphism. PK-Sim® version 10.0 was used to establish the whole-body PBPK model of pitavastatin. Our pharmacogenomic data and a total of 27 clinical pharmacokinetic data with different dose administration and demographic properties were used to develop and validate the model, respectively. Physicochemical properties and disposition characteristics of pitavastatin were acquired from previously reported data or optimized to capture the plasma concentration-time profiles in different SLCO1B1 diplotypes. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and profiles to the observed data. Predicted plasma concentration-time profiles were visually similar to the observed profiles in the non-genotyped populations and different SLCO1B1 diplotypes. All fold error values for AUC and Cmax were included in the two fold range of observed values. Thus, the PBPK model of pitavastatin in different SLCO1B1 diplotypes was properly established. The present study can be useful to individualize the dose administration strategy of pitavastatin in individuals with various ages, races, and SLCO1B1 diplotypes.

HDI Highlighter, The First Intelligent Tool to Screen the Literature on Herb-Drug Interactions

Herbal food supplements are commonly used and can be an important part of patient self-care. Like all other bio-active and therapeutic products, they have a benefit/risk balance. These products are not without adverse effects and potentially interact with other therapies. Educating patients and providing information for health professionals about the risk of herb-drug interactions is key. One of the purposes of the biomedical literature is to inform prescribers. Scientific literature accessible on databases such as PubMed is dense and careful reading is time consuming. We propose a reading aid tool named "HDI highlighter" to help readers to find key information in clinical studies and case reports describing herb-drug interactions. It uses natural language processing algorithms (artificial intelligence) with a pharmaceutical focus. Semantic relation extraction for herb-drug interactions from the biomedical literature are overexpressed using keywords. We have tested it to review 120 published articles over the last 10 years. In these articles, we have shown that case reports often involved long-term or semi-long-term treatments such as cancer or human immunodeficiency virus therapies, antiepileptic drugs, or central nervous system drugs. Similarly, these classes of drugs are more extensively targeted by clinical studies. Herb-drug interactions described in case reports are identified in medicinal, recreational, and alimentary uses. They also usually lack a rigorous description of the herb(s) involved. Typically, clinical studies provide a complete description of protocols and dosages, with a few exceptions explained by patients' needs. Clinical studies on herbs are nevertheless conducted on a limited number of patients. All these limitations make the interpretation of herb-drug interactions complicated, but the HDI highlighter provides a quick overview of the herb-drug interaction literature.

Effects of SLCO1B1 and SLCO1B3 Genetic Polymorphisms on Valsartan Pharmacokinetics in Healthy Korean Volunteers

Purpose: This study aimed to examine OATP1B1 (SLCO1B1) and OATP1B3 (SLCO1B3) on the pharmacokinetics of valsartan. Twenty-five subjects were genotyped for 16 single-nucleotide polymorphisms of the SLCO1B1 and SLCO1B3 genes. Methods: After a single dose of 160 mg of valsartan was orally administered to healthy male volunteers, drug concentrations were assayed up to 48 h. The 25 subjects were genotyped for 16 single-nucleotide polymorphisms (SNPs) of the SLCO1B1 and SLCO1B3 genes. Subjects were classified into groups according to their SLCO1B1*1B haplotype; 23 subjects were carriers of SLCO1B1*1B and two subjects were included in the reference group with SLCO1B1*1A/*1A. Alternations of the splicing factor-binding site pattern caused by the given mutation were evaluated with the Human Splicing Finder (HSF) 3.1. Results: The subjects who carried SLCO1B1*1B showed a 2.3-fold higher clearance than those without the *1B haplotype. Mean C_max and AUC_inf were reduced by 45% and 54%, respectively, in the SLCO1B1*1B genotype group compared to the reference group with the *1A/*1A genotype (p < 0.01). The carriers of the rs4149153 T allele of SLCO1B3 had a 27% lower mean C_max and a 1.5-fold higher Vd compared to homozygotic CC carriers (p < 0.05). In a combined analysis of SLCO1B1 and SLCO1B3, subjects not carrying SLCO1B1 *1B and carrying SLCO1B3 rs4149153 T allele showed a 1.6-fold higher clearance than those with the other genotypes, whereas mean C_max and AUC_last were reduced by 35% and 42%, respectively (p < 0.05), in the subjects. HSF 3.1 analysis showed that rs4149153 could cause alterations of the acceptor splice site (TAAATACTAAAGAC to TAAATATTAAAGAC) with scoring change (from 72.57 to 71.92, difference = −0.9). Conclusion: It was found that plasma exposure to valsartan is significantly decreased in SLCO1B1*1B carriers and carriers of the rs4149153 T allele of SLCO1B3, possibly as a result of increased hepatic uptake.

Herb-Drug Interactions: Worlds Intersect with the Patient at the Center

This review examines three bodies of literature related to herb-drug interactions: case reports, clinical studies, evaluations found in six drug interaction checking resources. The aim of the study is to examine the congruity of resources and to assess the degree to which case reports signal for further study. A qualitative review of case reports seeks to determine needs and perspectives of case report authors. Methods: Systematic search of Medline identified clinical studies and case reports of interacting herb-drug combinations. Interacting herb-drug pairs were searched in six drug interaction resources. Case reports were analyzed qualitatively for completeness and to identify underlying themes. Results: Ninety-nine case-report documents detailed 107 cases. Sixty-five clinical studies evaluated 93 mechanisms of interaction relevant to herbs reported in case studies, involving 30 different herbal products; 52.7% of these investigations offered evidence supporting reported reactions. Cohen's kappa found no agreement between any interaction checker and case report corpus. Case reports often lacked full information. Need for further information, attitudes about herbs and herb use, and strategies to reduce risk from interaction were three primary themes in the case report corpus. Conclusions: Reliable herb-drug information is needed, including open and respectful discussion with patients.

Multi-factorial pharmacokinetic interactions: unraveling complexities in precision drug therapy

Introduction: Precision drug therapy requires accounting for pertinent factors in pharmacokinetic (PK) inter-individual variability (i.e., pharmacogenetics, diseases, polypharmacy, and natural product use) that can cause sub-therapeutic or adverse effects. Although each of these individual factors can alter victim drug PK, multi-factorial interactions can cause additive, synergistic, or opposing effects. Determining the magnitude and direction of these complex multi-factorial effects requires understanding the rate-limiting redundant and/or sequential PK processes for each drug.Areas covered: Perturbations in drug-metabolizing enzymes and/or transporters are integral to single- and multi-factorial PK interactions. Examples of single factor PK interactions presented include gene-drug (pharmacogenetic), disease-drug, drug-drug, and natural product-drug interactions. Examples of multi-factorial PK interactions presented include drug-gene-drug, natural product-gene-drug, gene-gene-drug, disease-natural product-drug, and disease-gene-drug interactions. Clear interpretation of multi-factorial interactions can be complicated by study design, complexity in victim drug PK, and incomplete mechanistic understanding of victim drug PK.Expert opinion: Incorporation of complex multi-factorial PK interactions into precision drug therapy requires advances in clinical decision tools, intentional PK study designs, drug-metabolizing enzyme and transporter fractional contribution determinations, systems and computational approaches (e.g., physiologically-based pharmacokinetic modeling), and PK phenotyping of progressive diseases.

Interindividual and interethnic variability in drug disposition: polymorphisms in organic anion transporting polypeptide 1B1 (OATP1B1; SLCO1B1)

OATP1B1 (SLCO1B1) is predominantly expressed at the basolateral membrane of hepatocytes and is critically important for the hepatic uptake and clearance of numerous drug substrates and endogenous compounds. In general, the organic anion transporting polypeptides (OATP; SLCO) represent a superfamily of uptake transporters that mediate the sodium-independent transport of a diverse range of amphipathic organic compounds including bile salts, steroid conjugates, thyroid hormones, anionic peptides, numerous drugs and other xenobiotic substances. OATP1B1 is highly polymorphic and a number of relevant and ethnically dependent polymorphisms have been identified and functionally characterized. In particular, the SLCO1B1 521T>C and 388A>G polymorphisms are commonly occurring variants in ethnically diverse populations and numerous in vitro and clinical studies have evaluated the consequences of these variants to interindividual differences in drug disposition and response. OATP1B1 is particularly important for the disposition of HMG-CoA reductase inhibitors, or statins, as it is known to efficiently transport most statins to their site of action within hepatocytes. Many studies have focused on the consequences of OATP1B1 variants to statin disposition in vitro and in vivo and would suggest that genetic variability in SLCO1B1 has important implications for statin pharmacokinetics, risk for statin-induced myopathy, and modulation of statin treatment response. This review describes what is currently known regarding SLCO1B1 genotype, OATP1B1 protein expression and interindividual and interethnic consequences to drug disposition, with particular focus on statin pharmacokinetics and implications for drug response and toxicity.

SLCO1B1 polymorphism markedly affects the pharmacokinetics of lovastatin acid

OBJECTIVE

Organic anion transporting polypeptide 1B1 (OATP1B1, encoded by SLCO1B1 gene) is a hepatic uptake transporter, and its genetic variability is associated with pharmacokinetics and muscle toxicity risk of simvastatin. We examined the possible effects of variations in the SLCO1B1 gene on the pharmacokinetics of lovastatin in a prospective genotype panel study.

PARTICIPANTS AND METHODS

Seven healthy volunteers with the SLCO1B1*1B/*1B genotype, five with the SLCO1B1*5/*15 or *15/*15 genotype, and 15 with the SLCO1B1*1A/*1A genotype (controls) were recruited. Each study participant ingested a single 40-mg dose of lovastatin. Plasma concentrations of lovastatin (inactive lactone) and its active metabolite lovastatin acid were measured up to 24 h.

RESULTS

In the SLCO1B1*5/*15 or *15/*15 genotype group, the geometric mean Cmax and AUC0-24 of lovastatin acid were 340 and 286% of the corresponding values in the SLCO1B1*1A/*1A (reference) genotype group (P<0.005). In contrast, the AUC0-24 of lovastatin acid in the SLCO1B1*1B/*1B genotype group was only 68% of that in the reference genotype group (P=0.03). No statistically significant association was observed between the SLCO1B1 genotype and the pharmacokinetics of lovastatin lactone.

CONCLUSION

SLCO1B1*5/*15 and *15/*15 genotypes markedly increase the exposure to active lovastatin acid, but have no significant effect on lovastatin lactone, similar to their effects on simvastatin and simvastatin acid. Accordingly, it is probable that the risk of muscle toxicity during lovastatin treatment is increased in individuals carrying the SLCO1B1*5 or *15 allele. The SLCO1B1*1B/*1B genotype is associated with reduced lovastatin acid concentrations, consistent with enhanced hepatic uptake.

Drug-drug interactions that interfere with statin metabolism

INTRODUCTION

Lipid-lowering drugs, especially hydroxymethylglutaryl-CoA reductase inhibitors (statins), are widely used in the treatment and prevention of atherosclerotic diseases. The benefits of statins are well documented. However, myotoxic side effects, which can sometimes be severe, including myopathy or rhabdomyolysis, have been associated with the use of statins. In some cases, this toxicity is associated with pharmacokinetic alterations. Potent inhibitors of CYP 3A4 significantly increase plasma concentrations of the active forms of simvastatin, lovastatin and atorvastatin. Fluvastatin is metabolized by CYP2C9, while pravastatin, rosuvastatin and pitavastatin are not susceptible to inhibition by any CYP.

AREAS COVERED

This review discusses the pharmacokinetic aspects of the drug-drug interaction with statins and genetic polymorphisms in CYPs, which are involved in the metabolism of statins, and highlights the importance of establishing a system utilizing electronic medical information practically to avoid adverse drug reactions.

EXPERT OPINION

An understanding of the mechanisms underlying statin interactions will help to minimize drug interactions and develop statins that are less prone to adverse interactions. Quantitatively analyzed information for the low-density lipoprotein cholesterol lowering effects of statin based on electronic medical records may be useful for avoiding the adverse effect of statins.

Pharmacogenomics and herb-drug interactions: merge of future and tradition

The worldwide using of herb products and the increasing potential herb-drug interaction issue has raised enthusiasm on discovering the underlying mechanisms. Previous review indicated that the interactions may be mediated by metabolism enzymes and transporters in pharmacokinetic pathways. On the other hand, an increasing number of studies found that genetic variations showed some influence on herb-drug interaction effects whereas these genetic factors did not draw much attention in history. We highlight that pharmacogenomics may involve the pharmacokinetic or pharmacodynamic pathways to affect herb-drug interaction. We are here to make an updated review focused on some common herb-drug interactions in association with genetic variations, with the aim to help safe use of herbal medicines in different individuals in the clinic.

SLCO1B1, SLCO2B1, and SLCO1B3 polymorphisms and susceptibility to bladder cancer risk

A variety of carcinogens are excreted in urine and may be actively transported by organic anion-transporting polypeptides that encoded by SLCOs. In this study, we evaluated whether single nucleotide polymorphisms (SNPs) in SLCO1B1, SLCO2B1, and SLCO1B3 are associated with bladder cancer susceptibility. Our results, for the first time, indicated that polymorphisms of SLCO1B1 rs2306283 might be associated with bladder cancer risk. Therefore, SNPs in SLCO1B1 may be potential biomarkers for assessing the risk of bladder cancer.

The pharmacogenomics of statins

The statin class of cholesterol-lowering drugs have been used for decades to successfully lower plasma cholesterol concentrations and cardiovascular risk. Adverse effects of statins are generally considered mild, but increase with age of patients and polypharmacy. One aspect of statin therapy that is still difficult for prescribers to predict is the individual's response to statin therapy. Recent advances in the field of pharmacogenomics have indicated variants of candidate genes that affect statin efficacy and safety. In this review, a number of candidates that affect statin pharmacokinetics and pharmacodynamics are discussed. Some of these candidates, in particular those involved in import and efflux of statins, have now been linked to increased risk of side effects. Furthermore, pharmacogenomic studies continue to reveal new players that are involved in the fine-tuning of the complex regulation of cholesterol homeostasis and response to statins.

Evaluation of the pharmacokinetics and drug interactions of the two recently developed statins, rosuvastatin and pitavastatin

INTRODUCTION

Statins are the cornerstone of lipid-lowering therapy to reduce the risk of coronary heart disease. Rosuvastatin and pitavastatin are the two recently developed statins with less potential for drug interaction resulting in improved safety profiles.

AREAS COVERED

This review summarizes the pharmacokinetics and drug interactions of rosuvastatin and pitavastatin. The materials reviewed were identified by searching PubMed for publications using 'rosuvastatin', 'pitavastatin', 'statins', 'pharmacokinetics' and 'drug interaction' as the search terms.

EXPERT OPINION

Rosuvastatin and pitavastatin have favorable pharmacokinetic and safety profiles as their disposition does not depend on or is only marginally influenced by cytochrome P450 (CYP) enzymes, thus potentially reducing the risk of drug-drug interactions of these two statins with other drugs known to inhibit CYP enzymes. However, drug transporters play a significant role in the disposition of rosuvastatin and pitavastatin and drug interactions may occur through these. Genetic polymorphisms in drug transporters may also affect the pharmacokinetics, drug interactions and/or the lipid-lowering effect of these statins to a different extent.