SLCO1B1 polymorphism markedly affects the pharmacokinetics of simvastatin acid

Redefining Statin Dosage Post-Gastric Bypass: Insights from a Population Pharmacokinetics-Pharmacodynamics Link Approach

Roux-en-Y gastric bypass (RYGB) involves creating a small stomach pouch, bypassing part of the small intestine, and rerouting the digestive tract. These alterations can potentially change the drug exposure and response. Our primary aim was to assess the impact of RYGB on the pharmacokinetics of simvastatin lactone (SV) and its active metabolite, simvastatin hydroxy acid (SVA). Ultimately, we aimed to optimize dosing for this understudied population by employing a population pharmacokinetic-pharmacodynamic link approach. The study comprised patients who had undergone RYGB surgery and individuals without a previous history of RYGB. All participants received a single oral dose of simvastatin. Plasma concentration data were analyzed with a nonlinear mixed-effect modeling approach. A parent-metabolite model with first-order absorption, 2-compartments for SV and 1-compartment for SVA, linear elimination, and enterohepatic circulation best described the data. The model was linked to the turnover pharmacodynamic model to describe the SVA inhibition on LDL-cholesterol production. Our simulations indicated that following RYGB surgery, the exposure to SV and SVA decreased by 40%. Consequently, for low-intensity statin patients, we recommend increasing the dose from 10 to 20 mg in post-RYGB patients to maintain a comparable response to that of non-operated subjects. Moderate-intensity statin patients should require increasing doses to 40 or 60 mg or the addition of a non-statin medication to achieve similar therapeutic outcomes. In conclusion, individuals post-RYGB exhibit diminished exposure to SV and may benefit from increasing the dose or adjunctive therapy with non-statin drugs to attain equivalent responses and mitigate potential adverse events.

Physiologically based pharmacokinetics modeling and transporter proteomics to predict systemic and local liver and muscle disposition of statins

Statins are used to reduce liver cholesterol levels but also carry a dose-related risk of skeletal muscle toxicity. Concentrations of statins in plasma are often used to assess efficacy and safety, but because statins are substrates of membrane transporters that are present in diverse tissues, local differences in intracellular tissue concentrations cannot be ruled out. Thus, plasma concentration may not be an adequate indicator of efficacy and toxicity. To bridge this gap, we used physiologically based pharmacokinetic (PBPK) modeling to predict intracellular concentrations of statins. Quantitative data on transporter clearance were scaled from in vitro to in vivo conditions by integrating targeted proteomics and transporter kinetics data. The developed PBPK models, informed by proteomics, suggested that organic anion-transporting polypeptide 2B1 (OATP2B1) and multidrug resistance-associated protein 1 (MRP1) play a pivotal role in the distribution of statins in muscle. Using these PBPK models, we were able to predict the impact of alterations in transporter function due to genotype or drug-drug interactions on statin systemic concentrations and exposure in liver and muscle. These results underscore the potential of proteomics-guided PBPK modeling to scale transporter clearance from in vitro data to real-world implications. It is important to evaluate the role of drug transporters when predicting tissue exposure associated with on- and off-target effects.

Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment

Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.

Impact of liver diseases and pharmacological interactions on the transportome involved in hepatic drug disposition

The liver plays a pivotal role in drug disposition owing to the expression of transporters accounting for the uptake at the sinusoidal membrane and the efflux across the basolateral and canalicular membranes of hepatocytes of many different compounds. Moreover, intracellular mechanisms of phases I and II biotransformation generate, in general, inactive compounds that are more polar and easier to eliminate into bile or refluxed back toward the blood for their elimination by the kidneys, which becomes crucial when the biliary route is hampered. The set of transporters expressed at a given time, i.e., the so-called transportome, is encoded by genes belonging to two gene superfamilies named Solute Carriers (SLC) and ATP-Binding Cassette (ABC), which account mainly, but not exclusively, for the uptake and efflux of endogenous substances and xenobiotics, which include many different drugs. Besides the existence of genetic variants, which determines a marked interindividual heterogeneity regarding liver drug disposition among patients, prevalent diseases, such as cirrhosis, non-alcoholic steatohepatitis, primary sclerosing cholangitis, primary biliary cirrhosis, viral hepatitis, hepatocellular carcinoma, cholangiocarcinoma, and several cholestatic liver diseases, can alter the transportome and hence affect the pharmacokinetics of drugs used to treat these patients. Moreover, hepatic drug transporters are involved in many drug-drug interactions (DDI) that challenge the safety of using a combination of agents handled by these proteins. Updated information on these questions has been organized in this article by superfamilies and families of members of the transportome involved in hepatic drug disposition.

Non-targeted metabolomics for the identification of plasma metabolites associated with organic anion transporting polypeptide 1B1 function

Our aim was to evaluate biomarkers for organic anion transporting polypeptide 1B1 (OATP1B1) function using a hypothesis-free metabolomics approach. We analyzed fasting plasma samples from 356 healthy volunteers using non-targeted metabolite profiling by liquid chromatography high-resolution mass spectrometry. Based on SLCO1B1 genotypes, we stratified the volunteers to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Linear regression analysis, and random forest (RF) and gradient boosted decision tree (GBDT) regressors were used to investigate associations of plasma metabolite features with OATP1B1 function. Of the 9152 molecular features found, 39 associated with OATP1B1 function either in the linear regression analysis (p < 10-5) or the RF or GBDT regressors (Gini impurity decrease > 0.01). Linear regression analysis showed the strongest associations with two features identified as glycodeoxycholate 3-O-glucuronide (GDCA-3G; p = 1.2 × 10-20 for negative and p = 1.7 × 10-19 for positive electrospray ionization) and one identified as glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G; p = 2.7 × 10-16). In both the RF and GBDT models, the GCDCA-3G feature showed the strongest association with OATP1B1 function, with Gini impurity decreases of 0.40 and 0.17. In RF, this was followed by one GDCA-3G feature, an unidentified feature with a molecular weight of 809.3521, and the second GDCA-3G feature. In GBDT, the second and third strongest associations were observed with the GDCA-3G features. Of the other associated features, we identified with confidence two representing lysophosphatidylethanolamine 22:5. In addition, one feature was putatively identified as pregnanolone sulfate and one as pregnenolone sulfate. These results confirm GCDCA-3G and GDCA-3G as robust OATP1B1 biomarkers in human plasma.

Mining local exome and HLA data to characterize pharmacogenetic variants in Saudi Arabia

Pharmacogenomics (PGx) is a promising field of precision medicine where efficacy of drugs is maximized while side effects are minimized for individual patients. Knowledge of the frequency of PGx-relevant variants (pharmacovariants) in the local population is a pre-requisite to informed policy making. Unfortunately, such knowledge is largely lacking from the Middle East. Here, we describe the use of a large clinical exome database (n = 13,473) and HLA haplotypes (n = 64,737) from Saudi Arabia, one of the largest countries in the Middle East, along with previously published data from the local population to ascertain allele frequencies of known pharmacovariants. In addition, we queried another exome database (n = 816) of well-phenotyped research subjects from Saudi Arabia to discover novel candidate variants in known PGx genes (pharmacogenes). Although our results show that only 26% (63/242) of class 1A/1B PharmGKB variants were identified, we estimate that 99.57% of the local population have at least one such variant. This translates to a minimum estimated impact of 9% of medications dispensed by our medical center annually. We also highlight the contribution of rare variants where 71% of the pharmacogenes devoid of common pharmacovariants had at least one potentially deleterious rare variant. Thus, we show that approaches that go beyond the use of commercial PGx kits that have been optimized for other populations should be implemented to ensure universal and equitable access of all members of the local population to personalized prescription practices.

SLCO1B1 Genetic Variation Influence on Atorvastatin Systemic Exposure in Pediatric Hypercholesterolemia

This clinical study examined the influence of SLCO1B1 c.521T>C (rs4149056) on plasma atorvastatin concentrations in pediatric hypercholesterolemia. The participants (8-21 years), including heterozygous (c.521T/C, n = 13), homozygous (c.521C/C, n = 2) and controls (c.521T/T, n = 13), completed a single-oral-dose pharmacokinetic study. Similar to in adults, the atorvastatin (AVA) area-under-concentration-time curve from 0 to 24 h (AUC0-24) was 1.7-fold and 2.8-fold higher in participants with c.521T/C and c.521C/C compared to the c.521T/T participants, respectively. The inter-individual variability in AVA exposure within these genotype groups ranged from 2.3 to 4.8-fold, indicating that additional factors contribute to the inter-individual variability in the AVA dose-exposure relationship. A multivariate model reinforced the SLCO1B1 c.521T>C variant as the central factor contributing to AVA systemic exposure in this pediatric cohort, accounting for ~65% of the variability in AVA AUC0-24. Furthermore, lower AVA lactone concentrations in participants with increased body mass index contributed to higher exposure within the c.521T/T and c.521T/C genotype groups. Collectively, these factors contributing to higher systemic exposure could increase the risk of toxicity and should be accounted for when individualizing the dosing of atorvastatin in eligible pediatric patients.

Interindividual variability in statin pharmacokinetics and effects of drug transporters

INTRODUCTION

Statins are HMG-CoA reductase inhibitors that primarily lower plasma cholesterol levels. It has been suggested that the myotoxic response is a direct result of hydroxymethylglutaryl-CoA reductase inhibition and dose-dependent. Therefore, an accurate understanding of the combination of drugs that inhibit statin metabolism and factors that cause interindividual variability in the pharmacokinetics of statin is important to avoid serious side effects of statins. Relevant articles included in this review were identified through a PubMed search (through May 2023).

AREAS COVERED

This review provides an overview of hepatic and intestinal metabolism of statins, followed by a discussion of drug-drug interactions and interindividual variables that influence statin pharmacokinetics: gut bacteria, disease, and pharmacokinetics-related genetic polymorphisms.

EXPERT OPINION

Drug-drug interactions have a strong influence on statin pharmacokinetics, and gut microbiota, disease, and genetic polymorphisms all contribute significantly to interindividual variation in statin pharmacokinetics. Individual optimization of statin treatment requires studies that consider the progression of the disease and associated changes in concomitant medications.

Association between SLCO1B1 genetic polymorphisms and bleeding risk in patients treated with edoxaban

Since SLCO1B1 encodes the uptake transporter OATP1B1, which can influence the pharmacokinetic and pharmacodynamic profiles of edoxaban, polymorphisms in SLCO1B1 may affect the edoxaban response. This study aimed to investigate the association between SLCO1B1 gene polymorphisms and the bleeding risk in patients receiving edoxaban. We genotyped 10 single-nucleotide polymorphisms (SNPs) from the SLCO1B1 gene in patients receiving edoxaban. We also analyzed rs3842 of ABCB1 as a confounder. The odds ratio (OR) and adjusted OR (AOR) were calculated from univariate and multivariable analysis, respectively. The area under the receiver operating characteristic curve (AUROC) was constructed for the discrimination of the model. A total of 159 patients receiving edoxaban were analyzed. Overdose and rs4149056 showed significant association with bleeding complications by around 11- and 5.5-fold, respectively. Additionally, patients with the rs4149057 variant allele (C) had a 3.9-fold increased bleeding risk compared with wild-type homozygote carriers (TT), whereas rs2306283 variant homozygote (GG) carriers had a 0.27-fold reduced bleeding risk compared with wild-type allele (A) carriers. Patients with the variant-type homozygote (CC) of ABCB1 rs3842 had a higher bleeding risk than T allele carriers (AOR = 5.3 and 5.9). The final models for multivariable analyses were acceptable based on the AUROC values (> 0.70). These findings may help predict bleeding risk in patients taking edoxaban and help personalize treatment.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

BACKGROUND AND AIMS

The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance.

METHODS AND RESULTS

A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02).

CONCLUSION

We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

SLCO1B1*5 is protective against non-senile cataracts in cohort prescribed statins: analysis in a British-South Asian cohort

BACKGROUND

Reported association between statin use and cataract risk is controversial. The SLCO1B1 gene encodes a transport protein responsible for statin clearance. The aim of this study was to investigate a possible association between the SLCO1B1*5 reduced function variant and cataract risk in statin users of South Asian ethnicity.

METHODS

The Genes & Health cohort consists of British-Bangladeshi and British-Pakistani participants from East London, Manchester and Bradford, UK. SLCO1B1*5 genotype was assessed with the Illumina GSAMD-24v3-0-EA chip. Medication data from primary care health record linkage was used to compare those who had regularly used statins compared to those who had not. Multivariable logistic regression was used to test for association between statin use and cataracts, adjusting for population characteristics and potential confounders in 36,513 participants. Multivariable logistic regression was used to test association between SLCO1B1*5 heterozygotes or homozygotes and cataracts, in subgroups having been regularly prescribed statins versus not.

RESULTS

Statins were prescribed to 35% (12,704) of participants (average age 41 years old, 45% male). Non-senile cataract was diagnosed in 5% (1686) of participants. An apparent association between statins and non-senile cataract (12% in statin users and 0.8% in non-statin users) was negated by inclusion of confounders. In those prescribed a statin, presence of the SLCO1B1*5 genotype was independently associated with a decreased risk of non-senile cataract (OR 0.7 (CI 0.5-0.9, p 0.007)).

CONCLUSIONS

Our findings suggest that there is no independent association between statin use and non-senile cataract risk after adjusting for confounders. Among statin users, the SLCO1B1*5 genotype is associated with a 30% risk reduction of non-senile cataracts. Stratification of on-drug cohorts by validated pharmacogenomic variants is a useful tool to support or repudiate adverse drug events in observational cohorts.

Real-world pharmacogenetics of statin intolerance: effects of SLCO1B1, ABCG2 , and CYP2C9 variants

OBJECTIVE

The association of SLCO1B1 c.521T>C with simvastatin-induced muscle toxicity is well characterized. However, different statins are subject to metabolism and transport also by other proteins exhibiting clinically meaningful genetic variation. Our aim was to investigate associations of SLCO1B1 c.521T>C with intolerance to atorvastatin, fluvastatin, pravastatin, rosuvastatin, or simvastatin, those of ABCG2 c.421C>A with intolerance to atorvastatin, fluvastatin, or rosuvastatin, and that of CYP2C9*2 and *3 alleles with intolerance to fluvastatin.

METHODS

We studied the associations of these variants with statin intolerance in 2042 patients initiating statin therapy by combining genetic data from samples from the Helsinki Biobank to clinical chemistry and statin purchase data.

RESULTS

We confirmed the association of SLCO1B1 c.521C/C genotype with simvastatin intolerance both by using phenotype of switching initial statin to another as a marker of statin intolerance [hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.08-3.25, P  = 0.025] and statin switching along with creatine kinase measurement (HR 5.44, 95% CI 1.49-19.9, P  = 0.011). No significant association was observed with atorvastatin and rosuvastatin. The sample sizes for fluvastatin and pravastatin were relatively small, but SLCO1B1 c.521T>C carriers had an increased risk of pravastatin intolerance defined by statin switching when compared to homozygous reference T/T genotype (HR 2.11, 95% CI 1.01-4.39, P  = 0.047).

CONCLUSION

The current results can inform pharmacogenetic statin prescribing guidelines and show feasibility for the methodology to be used in larger future studies.

Effect of SLCO1B1 c.521T>C polymorphism on the lipid response to statins in people living with HIV on a boosted protease inhibitor-containing regimen

AIMS

We previously observed that some individuals on HIV boosted protease inhibitor-containing regimen do not achieve their lipid targets despite elevated statin concentrations. This study evaluated whether the common single polymorphism c.521T>C in SLCO1B1, associated with reduced statin uptake in the liver, could explain this observation.

METHODS

People living with HIV in the Swiss HIV Cohort Study were eligible if they were on a boosted protease inhibitor concomitantly with a statin for at least 6 months and if their SLCO1B1 genotype was available. Furthermore, their lipids had to be documented before and after the introduction of the statin. The statin efficacy was defined as % change in total cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol and triglycerides levels after statin initiation compared to pretreatment levels. Lipid response was adjusted for differences in potency and dose between statins.

RESULTS

In total, 88 people living with HIV were included, of whom 58, 28 and 2 carried the SLCO1B1 TT, TC and CC genotypes, respectively. The change in lipid levels after statin initiation tended to be lower in carriers of the polymorphism although the difference was not statistically significant (TT vs. TC/CC: total cholesterol: -11.7 vs. -4.8%; low-density lipoprotein- cholesterol: -20.6 vs. -7.4%; high-density lipoprotein-cholesterol: 1.6 vs. 0%; triglycerides: -11.5 vs. -7.9%). In the multiple linear regression, change in total cholesterol was inversely correlated with the total cholesterol level prestatin treatment (coefficient -6.60, 95% confidence interval: -9.63 to -3.56, P < .001).

CONCLUSION

The lipid-lowering effect of statins tended to be attenuated by SLCO1B1 polymorphism and progressively declined as total cholesterol under the boosted protease inhibitor treatment decreased.

Towards Evidence-Based Implementation of Pharmacogenomics in Southern Africa: Comorbidities and Polypharmacy Profiles across Diseases

Pharmacogenomics may improve patient care by guiding drug selection and dosing; however, this requires prior knowledge of the pharmacogenomics of drugs commonly used in a specific setting. The aim of this study was to identify a preliminary set of pharmacogenetic variants important in Southern Africa. We describe comorbidities in 3997 patients from Malawi, South Africa, and Zimbabwe. These patient cohorts were included in pharmacogenomic studies of anticoagulation, dyslipidemia, hypertension, HIV and breast cancer. The 20 topmost prescribed drugs in this population were identified. Using the literature, a list of pharmacogenes vital in the response to the top 20 drugs was constructed leading to drug-gene pairs potentially informative in translation of pharmacogenomics. The most reported morbidity was hypertension (58.4%), making antihypertensives the most prescribed drugs, particularly amlodipine. Dyslipidemia occurred in 31.5% of the participants, and statins were the most frequently prescribed as cholesterol-lowering drugs. HIV was reported in 20.3% of the study participants, with lamivudine/stavudine/efavirenz being the most prescribed antiretroviral combination. Based on these data, pharmacogenes of immediate interest in Southern African populations include ABCB1, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLC22A1, SLCO1B1 and UGT1A1. Variants in these genes are a good starting point for pharmacogenomic translation programs in Southern Africa.

PharmVar GeneFocus: SLCO1B1

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Bioaccumulation and biotransformation of simvastatin in probiotic bacteria: A step towards better understanding of drug-bile acids-microbiome interactions

Introduction: Although pharmacogenetics and pharmacogenomics have been at the forefront of research aimed at finding novel personalized therapies, the focus of research has recently extended to the potential of intestinal microbiota to affect drug efficacy. Complex interplay of gut microbiota with bile acids may have significant repercussions on drug pharmacokinetics. However, far too little attention has been paid to the potential implication of gut microbiota and bile acids in simvastatin response which is characterized by large interindividual variations. The Aim: In order to gain more insight into the underlying mechanism and its contribution in assessing the clinical outcome, the aim of our study was to examine simvastatin bioaccumulation and biotransformation in probiotic bacteria and the effect of bile acids on simvastatin bioaccumulation in in vitro conditions. Materials and methods: Samples with simvastatin, probiotic bacteria and three different bile acids were incubated at anaerobic conditions at 37°C for 24 h. Extracellular and intracellular medium samples were collected and prepared for the LC-MS analysis at predetermined time points (0 min, 15 min, 1 h, 2 h, 4 h, 6 h, 24 h). The concentrations of simvastatin were analyzed by LC-MS/MS. Potential biotransformation pathways were analyzed using a bioinformatics approach in correlation with experimental assay. Results: During the incubation, simvastatin was transported into bacteria cells leading to a drug bioaccumulation over the time, which was augmented upon addition of bile acids after 24 h. A decrease of total drug level during the incubation indicates that the drug is partly biotransformed by bacterial enzymes. According to the results of bioinformatics analysis, the lactone ring is the most susceptible to metabolic changes and the most likely reactions include ester hydrolysis followed by hydroxylation. Conclusion: Results of our study reveal that bioaccumulation and biotransformation of simvastatin by intestinal bacteria might be the underlying mechanisms of altered simvastatin bioavailability and therapeutic effect. Since this study is based only on selected bacterial strains in vitro, further more in-depth research is needed in order to elicit completely the contribution of complex drug-microbiota-bile acids interactions to overall clinical response of simvastatin which could ultimately lead to novel approaches for the personalized lipid-lowering therapy.

ABCG2 and SLCO1B1 gene polymorphisms in the Croatian population

BACKGROUND

Organic anion-transporting polypeptide 1B1 (OATP1B1) and the ATP-binding cassette subfamily G member 2, ABCG2, are important transporters involved in the transport of endogenous substrates and xenobiotics, including drugs. Genetic polymorphisms of these transporters have effect on transporter activity. There is significant interethnic variability in the frequency of allele variants.

AIM

To determined allele and genotype frequencies of ABCG2 and SLCO1B1 genes in Croatian populations of European descent.

SUBJECTS AND METHODS

A total of 905 subjects (482 women) were included. Genotyping for ABCG2 c.421C > A (rs2231142) and for SLCO1B1 c.521T > C (rs4149056), was performed by real-time polymerase chain reaction (PCR) using TaqMan^® DME Genotyping Assays.

RESULTS

For ABCG2 c.421C > A, the frequency of CC, CA and AA genotypes was 81.4%, 17.8% and 0.8% respectively. The frequency of variant ABCG2 421 A allele was 9.7%. For SLCO1B1 c.521T > C, the frequency of TT, TC and CC genotypes was 61.7%, 34.8% and 3.5% respectively. The frequency of variant SLCO1B1 521 C allele was 20.9%.

CONCLUSION

The frequency of the ABCG2 and SLCO1B1 allelic variants and genotypes in the Croatian population is in accordance with other European populations. Pharmacogenetic analysis can serve to individualise drug therapy and minimise the risk of developing adverse drug reactions.

Lung penetration and pneumococcal target binding of antibiotics in lower respiratory tract infection

OBJECTIVES

To achieve the therapeutic effects, antibiotics must penetrate rapidly into infection sites and bind to targets. This study reviewed updated knowledge on the ability of antibiotics to penetrate into the lung, their physicochemical properties influencing the pulmonary penetration and their ability to bind to targets on pneumococci.

METHODS

A search strategy was developed using PubMED, Web of Science, and ChEMBL. Data on serum protein binding, drug concentration, target binding ability, drug transporters, lung penetration, physicochemical properties of antibiotics in low respiratory tract infection (LRTI) were collected.

RESULTS

It was seen that infection site-to-serum concentration ratios of most antibiotics are >1 at different time points except for ceftriaxone, clindamycin and vancomycin. Most agents have proper physicochemical properties that facilitate antibiotic penetration. In antimicrobial-resistant Streptococcus pneumoniae, the binding affinity of antibiotics to targets mostly decreases compared to that in susceptible strains. The data on binding affinity of linezolid, clindamycin and vancomycin were insufficient. The higher drug concentration at the infection sites compared to that in the blood can be associated with inflammation conditions. Little evidence showed the effect of drug transporters on the clinical efficacy of antibiotics against LRTI.

CONCLUSIONS

Data on antibiotic penetration into the lung in LRTI patients and binding affinity of antibiotics for pneumococcal targets are still limited. Further studies are required to clarify the associations of the lung penetration and target binding ability of antibitotics with therapeutic efficacy to help propose the right antibiotics for LRTI.

Pharmacogenomics of lipid-lowering agents: the impact on efficacy and safety

Hyperlipidemia is a significant risk factor for cardiovascular disease morbidity and mortality. The lipid-lowering drugs are considered the cornerstone of primary and secondary prevention of atherosclerotic cardiovascular disease. Unfortunately, the lack of efficacy and associated adverse effects, ranging from mild-to-moderate to potentially life-threatening, lead to therapy discontinuation. Numerous reports support the role of gene polymorphisms in drugs' pharmacokinetic parameters and their associated adverse reactions. Therefore, this study aims to understand the pharmacogenomics of lipid-lowering drugs and the impact of genetic variants of key genes on the drugs' efficacy and toxicity. Indeed, genetically guided lipid-lowering therapy enhances overall safety, improves drug adherence and achieves long-term therapy.

Effects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment

Organic-anion-transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), is highly expressed in the liver and transports several endogenous metabolites into the liver, including statins. Previous studies have not investigated the association of SLCO1B1 rs4149056 variant with the risk of type 2 diabetes (T2D) or determined the metabolite signature of the C allele of SLCO1B1 rs4149056 (SLCO1B1 rs4149056-C allele) in a large randomly selected population. SLCO1B1 rs4149056-C inhibits OATP1B1 transporter and is associated with increased levels of blood simvastatin concentrations. Our study is to first to show that SLCO1B1 rs4149056 variant is not significantly associated with the risk of T2D, suggesting that simvastatin has a direct effect on the risk of T2D. Additionally, we investigated the effects of SLCO1B1 rs4149056-C on plasma metabolite concentrations in 1373 participants on simvastatin treatment and in 1368 age- and body-mass index (BMI)-matched participants without any statin treatment. We found 31 novel metabolites significantly associated with SLCO1B1 rs4149056-C in the participants on simvastatin treatment and in the participants without statin treatment. Simvastatin decreased concentrations of dicarboxylic acids, such as docosadioate and dodecanedioate, that may increase beta- and peroxisomal oxidation and increased the turnover of cholesterol into bile acids, resulting in a decrease in steroidogenesis due to limited availability of cholesterol for steroid synthesis. Our findings suggest that simvastatin exerts its effects on the lowering of low-density lipoprotein (LDL) cholesterol concentrations through several distinct pathways in the carriers of SLCO1B1 rs4149056-C, including dicarboxylic acids, bile acids, steroids, and glycerophospholipids.

Organic Anion Transporter Gene Variants Associated With Plasma Exposure and Long-Term Response to Atrasentan in Patients With Diabetic Kidney Disease

Plasma exposure of the endothelin receptor antagonist atrasentan varies between individuals and is associated with nephroprotective effects and the risk of heart failure. We examined the influence of genetic polymorphisms on atrasentan plasma exposure and pharmacodynamic effects. We performed a substudy of the Study of Diabetic Nephropathy With Atrasentan (SONAR) trial which enrolled adults with type 2 diabetes and chronic kidney disease (estimated glomerular filtration rate: 25-75 mL/min/1.73 m² , and a urine albumin-to-creatinine ratio of 300-5,000 mg/g). Single nucleotide polymorphisms (SNPs) were determined for prespecified membrane transporters, metabolizing enzymes, and the endothelin-1 peptide. The associations among genotype, atrasentan plasma exposure, and the effect of atrasentan on the prespecified kidney and heart failure hospitalization (HHF) outcomes was assessed with Cox proportional hazards regression models. Of 3,668 patients randomized, 2,329 (63.5%) consented to genotype analysis. Two SNPs in the SLCO1B1 gene (rs4149056 and rs2306283), encoding the hepatic organic anion transporter 1B1 (OATP1B1), showed the strongest association with atrasentan plasma exposure. Based on their SLCO1B1 genotype, patients were classified into normal (atrasentan area under the plasma-concentration time curve from zero to infinity (AUC_0-inf ) 41.3 ng·h/mL) or slow (atrasentan AUC_0-inf 49.7 ng·h/mL, P < 0.001) OATP1B1 transporter phenotypes. Among patients with a normal OATP1B1 phenotype, the hazard ratio (HR) with atrasentan for the primary kidney and HHF outcomes were 0.61 (95% confidence interval (CI): 0.45-0.81) and 1.35 (95% CI: 0.84-2.13), respectively. In the slow transporter phenotype, HRs for kidney and HHF outcomes were 1.95 (95% CI: 0.95-4.03, P-interaction normal phenotype = 0.004), and 4.18 (95% CI: 1.37-12.7, P-interaction normal phenotype = 0.060), respectively. OATP1B1 gene polymorphisms are associated with significant between-patient variability in atrasentan plasma exposure and long-term efficacy and safety.

Statin-related Muscle Toxicity: An Evidence-based Review

The efficacy of statins in the primary and secondary prevention of cardiovascular disease has been proven beyond doubt. The number needed to treat to prevent one cardiovascular event is 1 in 30 over 10 years, and the number needed to treat for secondary prevention is much lower. However, a recent study demonstrated that only 68% of eligible patients are on statin therapy. Moreover, there seems to be a reluctance to escalate statin doses due to the fear of adverse effects. The adverse effects that worries patients and their physicians most frequently are those related to muscular symptoms. N-of-1 trial evidence suggests that muscular symptoms attributed to statins are often caused by the nocebo effect. This article aims to provide a structured, evidence-based approach to suspected statin-related muscle toxicity.

Does the choice of applied physiologically‐based pharmacokinetics platform matter? A case study on simvastatin disposition and drug–drug interaction

Physiologically‐based pharmacokinetic (PBPK) models have an important role in drug discovery/development and decision making in regulatory submissions. This is facilitated by predefined PBPK platforms with user‐friendly graphical interface, such as Simcyp and PK‐Sim. However, evaluations of platform differences and the potential implications for disposition‐related applications are still lacking. The aim of this study was to assess how PBPK model development, input parameters, and model output are affected by the selection of PBPK platform. This is exemplified via the establishment of simvastatin PBPK models (workflow, final models, and output) in PK‐Sim and Simcyp as representatives of established whole‐body PBPK platforms. The major finding was that the choice of PBPK platform influenced the model development strategy and the final model input parameters, however, the predictive performance of the simvastatin models was still comparable between the platforms. The main differences between the structure and implementation of Simcyp and PK‐Sim were found in the absorption and distribution models. Both platforms predicted equally well the observed simvastatin (lactone and acid) pharmacokinetics (20–80 mg), BCRP and OATP1B1 drug–gene interactions (DGIs), and drug–drug interactions (DDIs) when co‐administered with CYP3A4 and OATP1B1 inhibitors/inducers. This study illustrates that in‐depth knowledge of established PBPK platforms is needed to enable an assessment of the consequences of PBPK platform selection. Specifically, this work provides insights on software differences and potential implications when bridging PBPK knowledge between Simcyp and PK‐Sim users. Finally, it provides a simvastatin model implemented in both platforms for risk assessment of metabolism‐ and transporter‐mediated DGIs and DDIs.

Frequency of functional exonic single-nucleotide polymorphisms and haplotype distribution in the SLCO1B1 gene across genetic ancestry groups in the Qatari population

Organic anion transporting polypeptides (OATP), which are encoded by SLCO genes, participate in the hepatic elimination of drugs and xenobiotics. SLCO1B1 is an important pharmacogenomic gene (encoding OATP1B1) associated with response to the uptake of endogenous compounds, such as statin and bilirubin. Ethnicity of the patient modulates the response to these drugs; the frequency and haplotype data for SLCO1B1 genetic variants in the Arab population is lacking. Therefore, we determined the frequencies of two well-characterized SLCO1B1 single nucleotide polymorphisms (SNP) and haplotypes that affect the OATP1B1 drugs transportation activity in Qatari population. Genotyping data for two SLCO1B1 SNPs (c.388A > G, c.521 T > C) were extracted from whole exome data of 1050 Qatari individuals, who were divided into three ancestry groups, namely Bedouins, Persians/South Asians, and Africans. By way of using Fisher's exact and Chi-square tests, we evaluated the differences in minor allele frequency (MAF) of the two functional SNPs and haplotype frequencies (HF) among the three ancestry groups. The OATP1B1 phenotypes were assigned according to their function by following the guidelines from the Clinical Pharmacogenetics Implementation Consortium for SLCO1B1 and Simvastatin-Induced Myopathy.The MAF of SLCO1B1:c.388A > G was higher compared to that of SLCO1B1:c.521 T > C in the study cohort. It was significantly high in the African ancestry group compared with the other two groups, whereas SLCO1B1:c.521 T > C was significantly low in the African ancestry group compared with the other two groups. The SLCO1B1 *15 haplotype had the highest HF, followed by *1b, *1a, and *5. Only the SLCO1B1 *5 haplotype showed no significant difference in frequency across the three ancestry groups. Furthermore, we observed that the OATP1B1 normal function phenotype accounted for 58% of the Qatari individuals, the intermediate function phenotype accounted for 35% with significant differences across the ancestry groups, and the low function phenotype accounted for 6% of the total Qatari individuals with a higher trend observed in the Bedouin group.The results indicate that the phenotype frequencies of the OATP1B1 intermediate and low function in the Qatari population appear at the higher end of the frequency range seen worldwide. Thus, a pharmacogenetic screening program for SLCO1B1 variants may be necessary for the Qatari population.

Novel Insights in Drug Transporter Sciences: the Year 2021 in Review

On behalf of the team I am pleased to present the second annual 'novel insights into drug transporter sciences review' focused on peer-reviewed articles that were published in the year 2021. In compiling the articles for inclusion, preprints available in 2021 but officially published in 2022 were considered to be in scope. To support this review the contributing authors independently selected one or two articles that were thought to be impactful and of interest to the broader research community. A similar approach as published last year was adopted whereby key observations, methods and analysis of each paper is concisely summarized in the synopsis followed by a commentary highlighting the impact of the paper in understanding of drug transporters' role in drug disposition.As the goal of this review is not to provide a comprehensive overview of each paper but rather highlight important findings that are well supported by the data, the reader is encouraged to consult the original articles for additional information. Further, and keeping in line with the goals of this review, it should be noted that all authors actively contributed by writing synopsis and commentary for individual papers and no attempt was made to standardize language or writing styles. In this way, the review article is reflective of not only the diversity of the articles but also that of the contributors. I extend my thanks to the authors for their continued support and also welcome Diane Ramsden and Pallabi Mitra as contributing authors for this issue.

Functional in vitro characterization of SLCO1B1 variants and simulation of the clinical pharmacokinetic impact of impaired OATP1B1 function

Organic Anion Transporting Polypeptide 1B1 is important to the hepatic elimination and distribution of many drugs. If OATP1B1 function is decreased, it can increase plasma exposure of e.g. several statins leading to increased risk of muscle toxicity. First, we examined the impact of three naturally occurring rare variants and the frequent SLCO1B1 c.388A>G variant on in vitro transport activity with cellular uptake assay using two substrates: 2', 7'-dichlorofluorescein (DCF) and rosuvastatin. Secondly, LC-MS/MS based quantitative targeted absolute proteomics measured the OATP1B1 protein abundance in crude membrane fractions of HEK293 cells over-expressing these SNVs. Additionally, we simulated the effect of impaired OATP1B1 function on rosuvastatin pharmacokinetics to estimate the need for genotype-guided dosing. R57Q impaired DCF and rosuvastatin transport significantly yet did not change protein expression considerably, while N130D and N151S did not alter activity but increased protein expression. R253Q did not change protein expression but reduced DCF uptake and increased rosuvastatin K_m. Based on pharmacokinetics simulations, doses of 30 mg (with 50% OATP1B1 function) and 20 mg (with 0% OATP1B1 function) result in plasma exposure similar to 40 mg dose (with 100% OATP1B1 function). Therefore dose reductions might be considered to avoid increased plasma exposure caused by function-impairing OATP1B1 genetic variants, such as R57Q.

Genomewide Association Study of Simvastatin Pharmacokinetics

We investigated genetic determinants of single-dose simvastatin pharmacokinetics in a prospective study of 170 subjects and a retrospective cohort of 59 healthy volunteers. In a microarray-based genomewide association study with the prospective data, the SLCO1B1 c.521T>C (p.Val174Ala, rs4149056) single nucleotide variation showed the strongest, genomewide significant association with the area under the plasma simvastatin acid concentration-time curve (AUC; P = 6.0 × 10^-10 ). Meta-analysis with the retrospective cohort strengthened the association (P = 1.6 × 10^-17 ). In a stepwise linear regression candidate gene analysis among all 229 participants, SLCO1B1 c.521T>C (P = 1.9 × 10^-13 ) and CYP3A4 c.664T>C (p.Ser222Pro, rs55785340, CYP3A4*2, P = 0.023) were associated with increased simvastatin acid AUC. Moreover, the SLCO1B1 c.463C>A (p.Pro155Thr, rs11045819, P = 7.2 × 10^-6 ) and c.1929A>C (p.Leu643Phe, rs34671512, P = 5.3 × 10^-4 ) variants associated with decreased simvastatin acid AUC. Based on these results and the literature, we classified the volunteers into genotype-predicted OATP1B1 and CYP3A4 phenotype groups. Compared with the normal OATP1B1 function group, simvastatin acid AUC was 273% larger in the poor (90% confidence interval (CI), 137%, 488%; P = 3.1 × 10^-6 ), 40% larger in the decreased (90% CI, 8%, 83%; P = 0.036), and 67% smaller in the highly increased function group (90% CI, 46%, 80%; P = 2.4 × 10^-4 ). Intermediate CYP3A4 metabolizers (i.e., heterozygous carriers of either CYP3A4*2 or CYP3A4*22 (rs35599367)), had 87% (90% CI, 39%, 152%, P = 6.4 × 10^-4 ) larger simvastatin acid AUC than normal metabolizers. These data suggest that in addition to no function SLCO1B1 variants, increased function SLCO1B1 variants and reduced function CYP3A4 variants may affect the pharmacokinetics, efficacy, and safety of simvastatin. Care is warranted if simvastatin is prescribed to patients carrying decreased function SLCO1B1 or CYP3A4 alleles.

An Updated Review of Genetic Associations With Severe Adverse Drug Reactions: Translation and Implementation of Pharmacogenomic Testing in Clinical Practice

Adverse drug reactions (ADR) remain the major problems in healthcare. Most severe ADR are unpredictable, dose-independent and termed as type B idiosyncratic reactions. Recent pharmacogenomic studies have demonstrated the strong associations between severe ADR and genetic markers, including specific HLA alleles (e.g., HLA-B*15:02/HLA-B*57:01/HLA-A*31:01 for carbamazepine-induced severe cutaneous adverse drug reactions [SCAR], HLA-B*58:01 for allopurinol-SCAR, HLA-B*57:01 for abacavir-hypersensitivity, HLA-B*13:01 for dapsone/co-trimoxazole-induced SCAR, and HLA-A*33:01 for terbinafine-induced liver injury), drug metabolism enzymes (such as CYP2C9*3 for phenytoin-induced SCAR and missense variant of TPMT/NUDT15 for thiopurine-induced leukopenia), drug transporters (e.g., SLCO1B1 polymorphism for statin-induced myopathy), and T cell receptors (Sulfanilamide binding into the CDR3/Vα of the TCR 1.3). This mini review article aims to summarize the current knowledge of pharmacogenomics of severe ADR, and the potentially clinical use of these genetic markers for avoidance of ADR.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.

Evaluation of the EMPAR study population on the basis of metabolic phenotypes of selected pharmacogenes

The impact of genetic variability of pharmacogenes as a possible risk factor for adverse drug reactions is elucidated in the EMPAR (Einfluss metabolischer Profile auf die Arzneimitteltherapiesicherheit in der Routineversorgung/English: influence of metabolic profiles on the safety of drug therapy in routine care) study. EMPAR evaluates possible associations of pharmacogenetically predicted metabolic profiles relevant for the metabolism of frequently prescribed cardiovascular drugs. Based on a German study population of 10,748 participants providing access to healthcare claims data and DNA samples for pharmacogenetic assessment, first analyses were performed and evaluated. The aim of this first evaluation was the characterization of the study population with regard to general parameters such as age, gender, comorbidity, and polypharmacy at baseline (baseline year) as well as important combinations of cardiovascular drugs with relevant genetic variants and predicted metabolic phenotypes. The study was registered in the German Clinical Trials Register (DRKS) on July 6, 2018 (DRKS00013909).

Pharmacogenetics to Avoid Adverse Reactions in Cardiology: Ready for Implementation?

Cardiovascular Diseases (CVs) are one of the main causes of mortality and disability around the world. Advances in drug treatment have greatly improved survival and quality of life in the past decades, but associated adverse events remain a relevant problem. Pharmacogenetics can help individualize cardiovascular treatment, reducing associated toxicities and improving outcomes. Several scientific societies and working groups periodically review available studies and provide consensus recommendations for those gene-drug pairs with a sufficient level of evidence. However, these recommendations are rarely mandatory, and the indications on how to adjust treatment can vary between different guidelines, which limits their clinical applicability. The aim of this review is to compile, compare and discuss available guidelines and recommendations by the main Pharmacogenetics Consortiums (Clinical Pharmacogenetics Implementation Consortium (CPIC); Dutch Pharmacogenetics Working Group (DPWG); the French Network of Pharmacogenetics (Réseau national de pharmacogénétique (RNPGx) and The Canadian Pharmacogenomics Network for Drug Safety (CPNDS) regarding how to apply pharmacogenetic results to optimize pharmacotherapy in cardiology. Pharmacogenetic recommendations included in European or American drug labels, as well as those included in the European Society of Cardiology (ESC) and the American College of Cardiology (ACC) and the American Heart Association (AHA) treatment guidelines are also discussed.

The Effect of Single Nucleotide Variations in the Transmembrane Domain of OATP1B1 on in vitro Functionality

Purpose

Organic Anion Transporting Polypeptide 1B1 (OATP1B1) mediates hepatic influx and clearance of many drugs, including statins. The SLCO1B1 gene is highly polymorphic and its function-impairing variants can predispose patients to adverse effects. The effects of rare genetic variants of SLCO1B1 are mainly unexplored. We examined the impact of eight naturally occurring rare variants and the well-known SLCO1B1 c.521C > T (V174A) variant on in vitro transport activity, cellular localization and abundance.

Methods

Transport of rosuvastatin and 2,7-dichlorofluorescein (DCF) in OATP1B1 expressing HEK293 cells was measured to assess changes in activity of the variants. Immunofluorescence and confocal microscopy determined the cellular localization of OATP1B1 and LC–MS/MS based quantitative targeted absolute proteomics analysis quantified the amount of OATP1B1 in crude membrane fractions.

Results

All studied variants, with the exception of P336R, reduced protein abundance to varying degree. V174A reduced protein abundance the most, over 90% compared to wild type. Transport function was lost in G76E, V174A, L193R and R580Q variants. R181C decreased activity significantly, while T345M and L543W retained most of wild type OATP1B1 activity. P336R showed increased activity and H575L decreased the transport of DCF significantly, but not of rosuvastatin. Decreased activity was interrelated with lower absolute protein abundance in the studied variants.

Conclusions

Transmembrane helices 2, 4 and 11 appear to be crucial for proper membrane localization and function of OATP1B1. Four of the studied variants were identified as loss-of-function variants and as such could make the individual harboring these variants susceptible to altered pharmacokinetics and adverse effects of substrate drugs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03107-8.

Role of Drug-Gene Interactions and Pharmacogenetics in Simvastatin-Associated Pulmonary Toxicity

Introduction

Simvastatin has previously been associated with drug-induced interstitial lung disease. In this retrospective observational study, cases with non-specific interstitial pneumonia (NSIP) or idiopathic pulmonary fibrosis (IPF) with simvastatin-associated pulmonary toxicity (n = 34) were evaluated.

Objective

To identify whether variations in genes encoding cytochrome P450 (CYP) enzymes or in the SLCO1B1 gene (Solute Carrier Organic anion transporting polypeptide 1B1 gene, encoding the organic anion transporting polypeptide 1B1 [OATP1B1] drug transporter enzyme), and/or characteristics of concomitantly used drugs, predispose patients to simvastatin-associated pulmonary toxicity.

Methods

Characteristics of concomitantly used drugs and/or variations in the CYP or SLCO1B1 genes and drug–gene interactions were assessed. The outcome after withdrawal of simvastatin and/or switch to another statin was assessed after 6 months.

Results

Multiple drug use involving either substrates and/or inhibitors of CYP3A4 and/or three or more drugs with the potential to cause acidosis explained the simvastatin-associated toxicity in 70.5% (n = 24) of cases. Cases did not differ significantly from controls regarding CYP3A4, CYP2C9, or OATP1B1 phenotypes, and genetic variation explained only 20.6% (n = 7) of cases. Withdrawal of simvastatin without switching to another statin or with a switch to a hydrophilic statin led to improvement or stabilization in all NSIP cases, whereas all cases who were switched to the lipophilic atorvastatin progressed.

Conclusion

Simvastatin-associated pulmonary toxicity is multifactorial. For patients with this drug-induced pulmonary toxicity who need to continue taking a statin, switching to a hydrophilic statin should be considered.

ClinicalTrials.gov identifier

NCT00267800, registered in 2005.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01105-8.

Protective Effects of Statin Therapy in Cirrhosis Are Limited by a Common SLCO1B1 Transporter Variant

Complications of cirrhosis and portal hypertension (PH) can be reduced by statin therapy. The common loss-of-function variant p.V174A in the solute carrier organic anion transporter gene 1B1 (SLCO1B1) gene encoding the organic anion transporting polypeptide 1B1 results in decreased hepatic uptake of statins. Our specific aim was to assess the impact of this variant in patients with cirrhosis and statin treatment while controlling for the stage of cirrhosis and other potential confounders with propensity score matching (PSM), availing of a large cohort of genotyped study patients. In total, from 1,088 patients with cirrhosis in two German academic medical centers, PSM yielded 154 patients taking statins and 154 matched controls. The effect on PH was assessed by the liver stiffness-spleen size-to-platelet score (LSPS), and complications of cirrhosis were retrospectively recorded applying consensus criteria. As hypothesized, patients on statin treatment presented less frequently with signs of PH: Esophageal varices (41% vs. 62%; P < 0.001) were less common, and LSPS (4.8 ± 11.5 vs. 5.6 ± 6.4; P = 0.01) was reduced. Correspondingly, decompensation events were also reduced in patients on statins (odds ratio [OR] = 0.54, 95% confidence interval [CI] 0.32-0.90; P = 0.02). When the variant in SLCO1B1 was present in patients on statins, esophageal varices (OR = 2.68, 95% CI 1.24-5.81; P = 0.01) and bacterial infections (OR = 2.50, 95% CI 1.14-5.47; P = 0.02) were more common as compared with wild type carriers on statins. Conclusion: In this cohort, signs and complications of PH were reduced in patients with cirrhosis treated with statins. Notably, this effect was diminished by the common loss-of-function variant in SLCO1B1. Further prospective studies in independent cohorts are warranted to confirm these genotype-specific observations.

Performance of Plasma Coproporphyrin I and III as OATP1B1 Biomarkers in Humans

A previous study in 356 healthy Finnish volunteers showed that glycochenodeoxycholate 3‐O‐glucuronide (GCDCA‐3G) and glycodeoxycholate 3‐O‐glucuronide (GDCA‐3G) are promising biomarkers of organic anion transporting polypeptide 1B1 (OATP1B1). In the same cohort, we now evaluated the performances of two other OATP1B1 biomarkers, coproporphyrin I (CPI) and III (CPIII), and compared them with GCDCA‐3G and GDCA‐3G. Based on decreased (*5 and *15) and increased (*14 and *20) function SLCO1B1 haplotypes, we stratified the participants to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Fasting plasma CPI concentration was 68% higher in the poor (95% confidence interval, 44%, 97%; P = 1.74 × 10⁻¹⁰), 7% higher in the decreased (0%, 15%; P = 0.0385), 10% lower in the increased (3%, 18%; P = 0.0087), and 23% lower in the highly increased (1%, 40%; P = 0.0387) function group than in the normal function group. CPIII concentration was 27% higher (7%, 51%; P = 0.0071) in the poor function group than in the normal function group. CPI and CPIII detected poor OATP1B1 function with areas under the precision‐recall curve (AUPRC) of 0.388 (95% confidence interval, 0.197, 0.689) and 0.0798 (0.0485, 0.203), and receiver operating characteristic curve (AUROC) of 0.888 (0.851, 0.919) and 0.731 (0.682, 0.776). The AUPRC and AUROC of GCDCA‐3G were, however, 0.389 (0.258, 0.563) and 0.100 (−0.0046, 0.204; P = 0.0610) larger than those of CPI, and 0.697 (0.555, 0.831) and 0.257 (0.141, 0.373; P < 0.0001) larger than those of CPIII. In conclusion, these data indicate that plasma CPI outperforms CPIII in detecting altered OATP1B1 function, but GCDCA‐3G is an even more sensitive OATP1B1 biomarker than CPI.

Pharmacogenetics to guide cardiovascular drug therapy

Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.

Effect of SLCO1B1 T521C on Statin-Related Myotoxicity With Use of Lovastatin and Atorvastatin

The association between the c.521T>C variant allele in SLCO1B1 (reference single nucleotide polymorphism (rs)4149056) and simvastatin-induced myotoxicity was discovered over a decade ago; however, whether this relationship represents a class effect is still not fully known. The aim of this study was to investigate the relationship between rs4149056 genotype and statin-induced myotoxicity in patients taking atorvastatin and lovastatin. Study participants were from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. A total of 233 statin-induced myopathy + rhabdomyolysis cases met the criteria for inclusion and were matched to 2,342 controls. To validate the drug response phenotype, we replicated the previously established association between rs4149056 genotype and simvastatin-induced myotoxicity. In particular, compared with homozygous T allele carriers, there was a significantly increased risk of simvastatin-induced myopathy + rhabdomyolysis in homozygous carriers of the C allele (CC vs. TT, odds ratio [OR] 4.62, 95% confidence interval [CI] 1.58-11.90, P = 0.003). For lovastatin users, homozygous carriers of the C allele were also at increased risk of statin-induced myopathy + rhabdomyolysis (CC vs. TT, OR 4.49, 95% CI 1.68-10.80, P = 0.001). In atorvastatin users, homozygous carriers of the C allele were twice as likely to experience statin-induced myopathy, though this association did not achieve statistical significance (CC vs. TT, OR 2.00, 95% CI 0.44-6.59, P = 0.30). In summary, our findings suggest that the association of rs4149056 with simvastatin-related myotoxicity may also extend to lovastatin. More data is needed to determine the extent of the association in atorvastatin users. Altogether, these data expand the evidence base for informing guidelines of pharmacogenetic-based statin prescribing practices.

Pharmacogenomics of statins: lipid response and other outcomes in Brazilian cohorts

Statins are inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase, a key enzyme in cholesterol biosynthesis, that are highly effective in reducing plasma low-density lipoprotein (LDL) cholesterol and decreasing the risk of cardiovascular events. In recent years, a multitude of variants in genes involved in pharmacokinetics (PK) and pharmacodynamics (PD) have been suggested to influence the cholesterol-lowering response. However, the vast majority of studies have analyzed the pharmacogenetic associations in populations in Europe and the USA, whereas data in other populations, including Brazil, are mostly lacking. This narrative review provides an update of clinical studies on statin pharmacogenomics in Brazilian cohorts exploring lipid-lowering response, adverse events and pleiotropic effects. We find that variants in drug transporter genes (SLCO1B1 and ABCB1) positively impacted atorvastatin and simvastatin response, whereas variants in genes of drug metabolizing enzymes (CYP3A5) decreased response. Furthermore, multiple associations of variants in PD genes (HMGCR, LDLR and APOB) with statin response were identified. Few studies have explored statin-related adverse events, and only ABCB1 but not SLCO1B1 variants were robustly associated with increased risk in Brazil. Statin-related pleiotropic effects were shown to be influenced by variants in PD (LDLR, NR1H2) and antioxidant enzyme (NOS3, SOD2, MTHFR, SELENOP) genes. The findings of these studies indicate that statin pharmacogenomic associations are distinctly different in Brazil compared to other populations. This review also discusses the clinical implications of pharmacogenetic studies and the rising importance of investigating rare variants to explore their association with statin response.

Prevalence of SLCO1B1 single nucleotide variations and their association with hypercholesterolaemia in hypercholesterolemic patients in Gauteng, South Africa

Statins, the standard treatment for hypercholesterolaemia, among the most widely prescribed, have been associated with side effects, including statin intolerance. The aim of this study was to determine the background prevalence of SLCO1B1 SNVs in a randomly selected sample and to investigate if there are associations between SLCO1B1 SNVs and hypercholesterolaemia patients on statin therapy.Using Polymerase Chain Reaction - Restriction Fragment Length Polymorphism, the presence of SLCO1B1 SNVs (rs4149056, rs2306283 and rs4363657) was identified, while ELISA was used to quantify serum CK levels. Statin intolerance risk was calculated using a quantitative questionnaire.The risk of developing statin intolerance was found to be low (in 36%), moderate (in 49%), or high (in 15%) in the statin-treated group. The prevalence of the rs4149056 variant was 16% in (controls) and 20% in (statin) group; rs2306283 variant was present in 31.5% (controls), 10.5% in (statin) group; while the prevalence of the rs4363657 variant was similar in each. No association between the presence of any one of the SNVs and the statin intolerance severity risk score or CK elevation was found.These findings will facilitate a more personalized approach to statin therapy, especially relevant within the diverse South African population.

Comparative Hepatic and Intestinal Metabolism and Pharmacodynamics of Statins

This study aimed to comprehensively investigate the in vitro metabolism of statins. The metabolism of clinically relevant concentrations of atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, simvastatin, and their metabolites were investigated using human liver microsomes (HLMs), human intestine microsomes (HIMs), liver cytosol, and recombinant cytochrome P450 enzymes. We also determined the inhibitory effects of statin acids on their pharmacological target, 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase. In HLMs, statin lactones were metabolized to a much higher extent than their acid forms. Atorvastatin lactone and simvastatin (lactone) showed extensive metabolism [intrinsic clearance (CL_int) values of 3700 and 7400 µl/min per milligram], whereas the metabolism of the lactones of 2-hydroxyatorvastatin, 4-hydroxyatorvastatin, and pitavastatin was slower (CL_int 20-840 µl/min per milligram). The acids had CL_int values in the range <0.1-80 µl/min per milligram. In HIMs, only atorvastatin lactone and simvastatin (lactone) exhibited notable metabolism, with CL_int values corresponding to 20% of those observed in HLMs. CYP3A4/5 and CYP2C9 were the main statin-metabolizing enzymes. The majority of the acids inhibited HMG-CoA reductase, with 50% inhibitory concentrations of 4-20 nM. The present comparison of the metabolism and pharmacodynamics of the various statins using identical methods provides a strong basis for further application, e.g., comparative systems pharmacology modeling. SIGNIFICANCE STATEMENT: The present comparison of the in vitro metabolic and pharmacodynamic properties of atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin and their metabolites using unified methodology provides a strong basis for further application. Together with in vitro drug transporter and clinical data, the present findings are applicable for use in comparative systems pharmacology modeling to predict the pharmacokinetics and pharmacological effects of statins at different dosages.

Pharmacogenomics in the era of next generation sequencing - from byte to bedside

Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.

Disease Status-Dependent Drug-Herb Interactions: NASH Lowered the Risk of Hepatotoxicity in Rats Coadministered With Simvastatin and Gardenia jasminoides J. Ellis

Concurrent use of simvastatin (SV) and Gardenia jasminoides J. Ellis (GJ) was adopted in patients with multi-morbidity, such as stroke rehabilitation patients with NASH. Although hepatotoxicity has been reported in both of them and NASH could alter the pharmacokinetics of drugs/herbs, the interaction between SV and GJ and the related hepatotoxicity remained uninvestigated under neither healthy nor NASH condition. The current study aimed to evaluate the potential hepatotoxicity resulted from the interactions between SV and GJ in both healthy and NASH rats. Both healthy and NASH rats received two-week SV (p. o., 8.66 mg/kg, once daily) and/or GJ (p.o., 325 mg/kg, twice daily). Pharmacokinetic profiles of SV, simvastatin acid (SVA, active metabolite of SV), and geniposide (major component in GJ); hepatic Cyp2c11/Oatp1b2/P-gp expression; and biomarker levels of liver function, lipid levels, and liver histology were compared to demonstrate the interactions in rats. To explore the mechanism of the interaction-mediated hepatotoxicity, hepatic genipin-protein adduct content and iNOS/COX-1/COX-2 expressions from related groups were compared. Moreover, liver histology of healthy/NASH rats at 90 days after discontinuation of two-week GJ in the absence and presence of SV was evaluated to estimate the long-term impact of the interactions. GJ reduced the systemic exposures of SV and SVA by up-regulating the hepatic P-gp expression in healthy but not NASH rats. Meanwhile, SV increased the systemic exposure of geniposide via inhibiting the activity of P-gp in both healthy and NASH rats. Although neither SV nor GJ induced hepatotoxicity in healthy rats, their co-treatment elevated serum ALT and AST levels, which may attribute to the aggravated genipin-protein adduct formation, inflammation infiltration, and iNOS/COX-1 expressions in the liver. In NASH rats, SV and/or GJ reduced serum ALT, AST, LDL/vLDL, and TC levels via alleviating hepatic inflammation infiltration and iNOS/COX-1 expressions. Moreover, in comparison to NASH rats, more severe fibrosis was observed in the livers of healthy rats at 90 days after discontinuation of two-week SV and GJ coadministration. Although interactions between SV and GJ induced short-term and long-term liver injuries in healthy rats, NASH condition in rats could lower such risk.

Robust Performance of Potentially Functional SNPs in Machine Learning Models for the Prediction of Atorvastatin-Induced Myalgia

Statins can cause muscle symptoms resulting in poor adherence to therapy and increased cardiovascular risk. We hypothesize that combinations of potentially functional SNPs (pfSNPs), rather than individual SNPs, better predict myalgia in patients on atorvastatin. This study assesses the value of potentially functional single nucleotide polymorphisms (pfSNPs) and employs six machine learning algorithms to identify the combination of SNPs that best predict myalgia.

Methods: Whole genome sequencing of 183 Chinese, Malay and Indian patients from Singapore was conducted to identify genetic variants associated with atorvastatin induced myalgia. To adjust for confounding factors, demographic and clinical characteristics were also examined for their association with myalgia. The top factor, sex, was then used as a covariate in the whole genome association analyses. Variants that were highly associated with myalgia from this and previous studies were extracted, assessed for potential functionality (pfSNPs) and incorporated into six machine learning models. Predictive performance of a combination of different models and inputs were compared using the average cross validation area under ROC curve (AUC). The minimum combination of SNPs to achieve maximum sensitivity and specificity as determined by AUC, that predict atorvastatin-induced myalgia in most, if not all the six machine learning models was determined.

Results: Through whole genome association analyses using sex as a covariate, a larger proportion of pfSNPs compared to non-pf SNPs were found to be highly associated with myalgia. Although none of the individual SNPs achieved genome wide significance in univariate analyses, machine learning models identified a combination of 15 SNPs that predict myalgia with good predictive performance (AUC >0.9). SNPs within genes identified in this study significantly outperformed SNPs within genes previously reported to be associated with myalgia. pfSNPs were found to be more robust in predicting myalgia, outperforming non-pf SNPs in the majority of machine learning models tested.

Conclusion: Combinations of pfSNPs that were consistently identified by different machine learning models to have high predictive performance have good potential to be clinically useful for predicting atorvastatin-induced myalgia once validated against an independent cohort of patients.

Regulation of OATP1B1 Function by Tyrosine Kinase-mediated Phosphorylation

PURPOSE

OATP1B1 (SLCO1B1) is the most abundant and pharmacologically relevant uptake transporter in the liver and a key mediator of xenobiotic clearance. However, the regulatory mechanisms that determine OATP1B1 activity remain uncertain, and as a result, unexpected drug-drug interactions involving OATP1B1 substrates continue to be reported, including several involving tyrosine kinase inhibitors (TKI).

EXPERIMENTAL DESIGN

OATP1B1-mediated activity in overexpressing HEK293 cells and hepatocytes was assessed in the presence of FDA-approved TKIs, while rosuvastatin pharmacokinetics in the presence of an OATP1B1 inhibiting TKI were measured in vivo. Tyrosine phosphorylation of OATP1B1 was determined by LC/MS-MS-based proteomics and transport function was measured following exposure to siRNAs targeting 779 different kinases.

RESULTS

Twenty-nine of 46 FDA-approved TKIs studied significantly inhibit OATP1B1 function. Inhibition of OATP1B1 by TKIs, such as nilotinib, is predominantly noncompetitive, can increase systemic concentrations of rosuvastatin in vivo, and is associated with reduced phosphorylation of OATP1B1 at tyrosine residue 645. Using genetic screens and functional validation studies, the Src kinase LYN was identified as a potential regulator of OATP1B1 activity that is highly sensitive to inhibition by various TKIs at clinically relevant concentrations.

CONCLUSIONS

A novel kinase-dependent posttranslational mechanism of OATP1B1 activation was identified and interference with this process by TKIs can influence the elimination of a broad range of xenobiotic substrates.

Relationship of hemoglobin level and plasma coproporphyrin-I concentrations as an endogenous probe for phenotyping OATP1B

Plasma coproporphyrin‐I (CP‐I) concentration is used as a sensitive and selective endogenous probe for phenotyping organic anion transporting polypeptides 1B (OATP1B) activity in many studies. CP‐I is produced in the process of heme synthesis, but the relationship between plasma CP‐I concentrations and heme synthesis activity is unknown. In this study, we evaluated the relationship between plasma CP‐I concentration and hemoglobin level as a biomarker of heme synthesis activity. The data of 391 subjects selected from the Japanese general population were analyzed. One hundred twenty‐six participants had OATP1B1*15 allele, 11 of whom were homozygous (OATP1B1*15/*15). Multiple regression analysis identified hemoglobin level as an independent variable associated with plasma CP‐I concentration (p < 0.0001). A significant positive correlation was observed between hemoglobin level and plasma CP‐I concentration in participants without OATP1B1*15 allele (n = 265; r_s = 0.35, p < 0.0001) and with OATP1B1*15 allele (n = 126; r_s =0.27, p = 0.0022). However, Kruskal–Wallis test showed no large difference in Kruskal–Wallis statistics between the distribution of plasma CP‐I concentrations and that of ratio of plasma CP‐I to hemoglobin among six OATP1B1 polymorphism groups. These findings suggest that the hemoglobin level seems to reflect biosynthesis of CP‐I. However, correction by hemoglobin level is not required when using basal plasma CP‐I concentration for phenotyping OATP1B activity.

Personalized medicine in lipid-modifying therapy

The choice of lipid-modifying treatment is largely based on the absolute level of cardiovascular risk and baseline lipid profile. Statins are the first-line treatment for most patients requiring reduction of low-density-lipoprotein cholesterol (LDL-C) and ezetimibe and proprotein convertase subtilisin/kexin type 9 inhibitors can be added to reach LDL-C targets. Statins have some adverse effects that are somewhat predictable based on phenotypic and genetic factors. Fibrates or omega-3 fatty acids can be added if triglyceride levels remain elevated. The RNA-targeted therapeutics in development offer the possibility of selective liver targeting for specific lipoproteins such as lipoprotein(a) and long-term reduction of LDL-C with infrequent administration of a small-interfering RNA may help to overcome the problem of adherence to therapy.

The Role of Pharmacogenomics in Contemporary Cardiovascular Therapy: A position statement from the European Society of Cardiology Working Group on Cardiovascular Pharmacotherapy

There is a strong and ever-growing body of evidence regarding the use of pharmacogenomics to inform cardiovascular pharmacology. However, there is no common position taken by international cardiovascular societies to unite diverse availability, interpretation and application of such data, nor is there recognition of the challenges of variation in clinical practice between countries within Europe. Aside from the considerable barriers to implementing pharmacogenomic testing and the complexities of clinically actioning results, there are differences in the availability of resources and expertise internationally within Europe. Diverse legal and ethical approaches to genomic testing and clinical therapeutic application also require serious thought. As direct-to-consumer genomic testing becomes more common, it can be anticipated that data may be brought in by patients themselves, which will require critical assessment by the clinical cardiovascular prescriber. In a modern, pluralistic and multi-ethnic Europe, self-identified race/ethnicity may not be concordant with genetically detected ancestry and thus may not accurately convey polymorphism prevalence. Given the broad relevance of pharmacogenomics to areas such as thrombosis and coagulation, interventional cardiology, heart failure, arrhythmias, clinical trials, and policy/regulatory activity within cardiovascular medicine, as well as to genomic and pharmacology subspecialists, this position statement attempts to address these issues at a wide-ranging level.

The Interface of Therapeutics and Genomics in Cardiovascular Medicine

Pharmacogenomics has a burgeoning role in cardiovascular medicine, from warfarin dosing to antiplatelet choice, with recent developments in sequencing bringing the promise of personalised medicine ever closer to the bedside. Further scientific evidence, real-world clinical trials, and economic modelling are needed to fully realise this potential. Additionally, tools such as polygenic risk scores, and results from Mendelian randomisation analyses, are only in the early stages of clinical translation and merit further investigation. Genetically targeted rational drug design has a strong evidence base and, due to the nature of genetic data, academia, direct-to-consumer companies, healthcare systems, and industry may meet in an unprecedented manner. Data sharing navigation may prove problematic. The present manuscript addresses these issues and concludes a need for further guidance to be provided to prescribers by professional bodies to aid in the consideration of such complexities and guide translation of scientific knowledge to personalised clinical action, thereby striving to improve patient care. Additionally, technologic infrastructure equipped to handle such large complex data must be adapted to pharmacogenomics and made user friendly for prescribers and patients alike.

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.