Evaluation of OCT2-mediated drug-drug interactions between ulotaront and metformin in subjects with schizophrenia

Ulotaront (SEP-363856) is a TAAR1 agonist, with 5-HT1A agonist activity, currently in clinical development for the treatment of schizophrenia. In vitro studies indicate ulotaront is an OCT2-specific inhibitor with IC50 of 1.27 μM. The primary objective of this study is to determine if a single dose of ulotaront affects the PK of metformin, an index substrate of OCT2, in subjects with schizophrenia. In a randomized, single-blind, 2-period crossover study, 25 adults with schizophrenia received a single dose of metformin-HCl 850 mg (approximately 663 mg metformin) with and without coadministration of 100 mg ulotaront. The plasma samples were analyzed by fully validated LC-MS/MS methods. The primary PK endpoints for metformin were AUCinf, AUClast, Cmax, and tmax. The highest-anticipated clinical dose of ulotaront (100 mg) had no statistically significant effect on the PK of a single dose of metformin based on Cmax and AUCinf. Geometric least squares mean ratios were 89.98% and 110.63%, respectively, with the 90% confidential interval (CI) for each parameter contained within 80%-125%. Median tmax was comparable across the treatments. Ulotaront does not act as a perpetrator of OCT2-mediated DDI against metformin. Co-administration of ulotaront is not expected to require dose adjustment of metformin or other drugs cleared by OCT2.

Effect of Pharmacogenomic Testing for Drug-Gene Interactions on Medication Selection and Remission of Symptoms in Major Depressive Disorder: The PRIME Care Randomized Clinical Trial

IMPORTANCE

Selecting effective antidepressants for the treatment of major depressive disorder (MDD) is an imprecise practice, with remission rates of about 30% at the initial treatment.

OBJECTIVE

To determine whether pharmacogenomic testing affects antidepressant medication selection and whether such testing leads to better clinical outcomes.

DESIGN, SETTING, AND PARTICIPANTS

A pragmatic, randomized clinical trial that compared treatment guided by pharmacogenomic testing vs usual care. Participants included 676 clinicians and 1944 patients. Participants were enrolled from 22 Department of Veterans Affairs medical centers from July 2017 through February 2021, with follow-up ending November 2021. Eligible patients were those with MDD who were initiating or switching treatment with a single antidepressant. Exclusion criteria included an active substance use disorder, mania, psychosis, or concurrent treatment with a specified list of medications.

INTERVENTIONS

Results from a commercial pharmacogenomic test were given to clinicians in the pharmacogenomic-guided group (n = 966). The comparison group received usual care and access to pharmacogenomic results after 24 weeks (n = 978).

MAIN OUTCOMES AND MEASURES

The co-primary outcomes were the proportion of prescriptions with a predicted drug-gene interaction written in the 30 days after randomization and remission of depressive symptoms as measured by the Patient Health Questionnaire-9 (PHQ-9) (remission was defined as PHQ-9 ≤ 5). Remission was analyzed as a repeated measure across 24 weeks by blinded raters.

RESULTS

Among 1944 patients who were randomized (mean age, 48 years; 491 women [25%]), 1541 (79%) completed the 24-week assessment. The estimated risks for receiving an antidepressant with none, moderate, and substantial drug-gene interactions for the pharmacogenomic-guided group were 59.3%, 30.0%, and 10.7% compared with 25.7%, 54.6%, and 19.7% in the usual care group. The pharmacogenomic-guided group was more likely to receive a medication with a lower potential drug-gene interaction for no drug-gene vs moderate/substantial interaction (odds ratio [OR], 4.32 [95% CI, 3.47 to 5.39]; P < .001) and no/moderate vs substantial interaction (OR, 2.08 [95% CI, 1.52 to 2.84]; P = .005) (P < .001 for overall comparison). Remission rates over 24 weeks were higher among patients whose care was guided by pharmacogenomic testing than those in usual care (OR, 1.28 [95% CI, 1.05 to 1.57]; P = .02; risk difference, 2.8% [95% CI, 0.6% to 5.1%]) but were not significantly higher at week 24 when 130 patients in the pharmacogenomic-guided group and 126 patients in the usual care group were in remission (estimated risk difference, 1.5% [95% CI, -2.4% to 5.3%]; P = .45).

CONCLUSIONS AND RELEVANCE

Among patients with MDD, provision of pharmacogenomic testing for drug-gene interactions reduced prescription of medications with predicted drug-gene interactions compared with usual care. Provision of test results had small nonpersistent effects on symptom remission.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03170362.

Pharmacogenomics Biomarker Discovery and Validation for Translation in Clinical Practice

Interindividual variability in drug efficacy and toxicity is a major challenge in clinical practice. Variations in drug pharmacokinetics (PKs) and pharmacodynamics (PDs) can be, in part, explained by polymorphic variants in genes encoding drug metabolizing enzymes and transporters (absorption, distribution, metabolism, and excretion) or in genes encoding drug receptors. Pharmacogenomics (PGx) has allowed the identification of predictive biomarkers of drug PKs and PDs and the current knowledge of genome-disease and genome-drug interactions offers the opportunity to optimize tailored drug therapy. High-throughput PGx genotyping, from targeted to more comprehensive strategies, allows the identification of PK/PD genotypes to be developed as clinical predictive biomarkers. However, a biomarker needs a robust process of validation followed by clinical-grade assay development and must comply to stringent regulatory guidelines. We here discuss the methodological challenges and the emerging technological tools in PGx biomarker discovery and validation, at the crossroad among molecular genetics, bioinformatics, and clinical medicine.

How a concentration-effect analysis of data from the eliglustat thorough electrocardiographic study was used to support dosing recommendations

Eliglustat is a first-line oral treatment for adults with Gaucher disease type 1 who have cytochrome P450 (CYP) 2D6 extensive, intermediate, or poor metabolizer phenotypes. Per International Conference on Harmonisation (ICH) E14 guidance, a Phase 1 thorough electrocardiographic (ECG) study was done during drug development to assess eliglustat's effects on cardiac repolarization by measuring ECG intervals in healthy adult subjects. Using data from the thorough ECG study, we performed pharmacokinetic/pharmacodynamic-ECG modeling to establish the relationship between eliglustat concentrations and their effects on ECG intervals. We then used that concentration-response relationship to predict the effects of eliglustat on each ECG interval for each CYP2D6 metabolizer phenotype (the main determinant of eliglustat exposure) and in different drug-drug interaction scenarios. These predictions, together with other exposure-related factors, contributed to the CYP2D6 phenotype-based dosing recommendations for eliglustat, including dose adjustments and contraindications when co-administered with drugs metabolized by the CYP2D6 and CYP3A pathways.

Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer

Cancer cells with heterogeneous mutation landscapes and extensive functional redundancy easily develop resistance to monotherapies by emerging activation of compensating or bypassing pathways. To achieve more effective and sustained clinical responses, synergistic interactions of multiple druggable targets that inhibit redundant cancer survival pathways are often required. Here, we report a systematic polypharmacology strategy to predict, test, and understand the selective drug combinations for MDA-MB-231 triple-negative breast cancer cells. We started by applying our network pharmacology model to predict synergistic drug combinations. Next, by utilizing kinome-wide drug-target profiles and gene expression data, we pinpointed a synergistic target interaction between Aurora B and ZAK kinase inhibition that led to enhanced growth inhibition and cytotoxicity, as validated by combinatorial siRNA, CRISPR/Cas9, and drug combination experiments. The mechanism of such a context-specific target interaction was elucidated using a dynamic simulation of MDA-MB-231 signaling network, suggesting a cross-talk between p53 and p38 pathways. Our results demonstrate the potential of polypharmacological modeling to systematically interrogate target interactions that may lead to clinically actionable and personalized treatment options.

Projected Prevalence of Actionable Pharmacogenetic Variants and Level A Drugs Prescribed Among US Veterans Health Administration Pharmacy Users

IMPORTANCE

Implementation of pharmacogenetic testing to guide drug prescribing has potential to improve drug response and prevent adverse events. Robust data exist for more than 30 gene-drug pairs linking genotype to drug response phenotypes; however, it is unclear which pharmacogenetic tests, if implemented, would provide the greatest utility for a given patient population.

OBJECTIVES

To project the proportion of veterans in the US Veterans Health Administration (VHA) with actionable pharmacogenetic variants and evaluate how testing might be associated with prescribing decisions.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included veterans who used national VHA pharmacy services from October 1, 2011, to September 30, 2017. Data analyses began April 26, 2018, and were completed February 6, 2019.

EXPOSURES

Receipt of level A drugs based on VHA pharmacy dispensing records.

MAIN OUTCOMES AND MEASURES

Projected prevalence of actionable pharmacogenetic variants among VHA pharmacy users based on variant frequencies from the 1000 Genomes Project and veteran demographic characteristics; incident number of level A prescriptions, and proportion of new level A drug recipients projected to carry an actionable pharmacogenetic variant.

RESULTS

During the study, 7 769 359 veterans (mean [SD] age, 58.1 [17.8] years; 7 021 504 [90.4%] men) used VHA pharmacy services. It was projected that 99% of VHA pharmacy users would carry at least 1 actionable pharmacogenetic variant. Among VHA pharmacy users, 4 259 153 (54.8%) received at least 1 level A drug with 1 188 124 (15.3%) receiving 2 drugs, and 912 189 (11.7%) receiving 3 or more drugs. The most common incident prescriptions during the study were tramadol (923 671 new recipients), simvastatin (533 928 new recipients), citalopram (266 952 new recipients), and warfarin (205 177 new recipients). Gene-drug interactions projected to have substantial clinical impacts in the VHA population include the interaction of SLCO1B1 with simvastatin (1 988 956 veterans [25.6%]), CYP2D6 with tramadol (318 544 veterans [4.1%]), and CYP2C9 or VKORC1 with warfarin (7 163 349 veterans [92.2%]).

CONCLUSIONS AND RELEVANCE

Clinically important pharmacogenetic variants are highly prevalent in the VHA population. Almost all veterans would carry an actionable variant, and more than half of the population had been exposed to a drug affected by these variants. These results suggest that pharmacogenetic testing has the potential to affect pharmacotherapy decisions for commonly prescribed outpatient medications for many veterans.

Leveraging genetic interactions for adverse drug-drug interaction prediction

In light of increased co-prescription of multiple drugs, the ability to discern and predict drug-drug interactions (DDI) has become crucial to guarantee the safety of patients undergoing treatment with multiple drugs. However, information on DDI profiles is incomplete and the experimental determination of DDIs is labor-intensive and time-consuming. Although previous studies have explored various feature spaces for in silico screening of interacting drug pairs, their use of conventional cross-validation prevents them from achieving generalizable performance on drug pairs where neither drug is seen during training. Here we demonstrate for the first time targets of adversely interacting drug pairs are significantly more likely to have synergistic genetic interactions than non-interacting drug pairs. Leveraging genetic interaction features and a novel training scheme, we construct a gradient boosting-based classifier that achieves robust DDI prediction even for drugs whose interaction profiles are completely unseen during training. We demonstrate that in addition to classification power—including the prediction of 432 novel DDIs—our genetic interaction approach offers interpretability by providing plausible mechanistic insights into the mode of action of DDIs.

Adverse drug-drug interactions are adverse side effects caused by taking two or more drugs together. As co-prescription of multiple drugs becomes an increasingly prevalent practice, affecting 42.2% of Americans over 65 years old, adverse drug-drug interactions have become a serious safety concern, accounting for over 74,000 emergency room visits and 195,000 hospitalizations each year in the United States alone. Since experimental determination of adverse drug-drug interactions is labor-intensive and time-consuming, various machine learning-based computational approaches have been developed for predicting drug-drug interactions. Considering the fact that drugs effect through binding and modulating the function of their targets, we have explored whether drug-drug interactions can be predicted from the genetic interaction between the gene targets of two drugs, which characterizes the unexpected fitness effect when two genes are simultaneously knocked out. Furthermore, we have built a fast and robust classifier that achieves accurate prediction of adverse drug-drug interactions by incorporating genetic interaction and several other types of widely used features. Our analyses suggest that genetic interaction is an important feature for our prediction model, and that it provides mechanistic insight into the mode of action of drugs leading to drug-drug interactions.

Complex Drug-Drug-Gene-Disease Interactions Involving Cytochromes P450: Systematic Review of Published Case Reports and Clinical Perspectives

Drug pharmacokinetics (PK) is influenced by multiple intrinsic and extrinsic factors, among which concomitant medications are responsible for drug-drug interactions (DDIs) that may have a clinical relevance, resulting in adverse drug reactions or reduced efficacy. The addition of intrinsic factors affecting cytochromes P450 (CYPs) activity and/or expression, such as genetic polymorphisms and diseases, may potentiate the impact and clinical relevance of DDIs. In addition, greater variability in drug levels and exposures has been observed when such intrinsic factors are present in addition to concomitant medications perpetrating DDIs. This variability results in poor predictability of DDIs and potentially dramatic clinical consequences. The present review illustrates the issue of complex DDIs using systematically searched published case reports of DDIs involving genetic polymorphisms, renal impairment, cirrhosis, and/or inflammation. Current knowledge on the impact of each of these factors on drug exposure and DDIs is summarized and future perspectives for the management of such complex DDIs in clinical practice are discussed, including the use of advanced Computerized Physician Order Entry (CPOE) systems, the development of model-based dose optimization strategies, and the education of healthcare professionals with respect to personalized medicine.

A Phase Ib Study of Sorafenib (BAY 43-9006) in Patients with Kaposi Sarcoma

Lessons Learned.

Oral targeted agents are desirable for treatment of Kaposi sarcoma (KS); however, in patients with HIV, drug–drug interactions must be considered. In this study to treat KS, sorafenib was poorly tolerated at doses less than those approved by the U.S. Food and Drug Administration for hepatocellular carcinoma and other cancers, and showed only modest activity.

Sorafenib's metabolism occurs via the CYP3A4 pathway, which is inhibited by ritonavir, a commonly used antiretroviral agent used by most patients in this study. Strong CYP3A4 inhibition by ritonavir may contribute to the observed sorafenib toxicity.

Alternate antiretroviral agents without predicted interactions are preferred for co‐administration in patients with HIV and cancers for which sorafenib is indicated.

Background.

We conducted a phase Ib study of sorafenib, a vascular epithelial growth factor receptor (VEGFR), c‐kit, and platelet derived growth factor receptor (PDGFR)‐targeted treatment in Kaposi sarcoma (KS). We evaluated drug–drug interactions between sorafenib and ritonavir, an HIV medication with strong CYP3A4 inhibitory activity.

Methods.

Two cohorts were enrolled: HIV‐related KS on ritonavir (Cohort R) and HIV‐related or classical KS not receiving ritonavir (Cohort NR). Sorafenib dose level 1 in cohort R (R1) was 200 mg daily and 200 mg every 12 hours in cohort NR (NR1). Steady‐state pharmacokinetics were evaluated at cycle 1, day 8. KS responses and correlative factors were assessed.

Results.

Ten patients (nine HIV⁺) were enrolled: R1 (eight), NR1 (two). Median CD4⁺ count (HIV⁺) was 500 cells/µL. Dose‐limiting toxicities (DLTs) were grade 3 elevated lipase (R1), grade 4 thrombocytopenia (R1), and grade 3 hand‐foot syndrome (NR1). Two of seven evaluable patients had a partial response (PR; 29%; 95% CI 4%–71%). Steady‐state area under the curve of the dosing interval (AUC_TAU) of sorafenib was not significantly affected by ritonavir; however, a trend for decreased AUC_TAU of the CYP3A4 metabolite sorafenib‐N‐oxide (3.8‐fold decrease; p = .08) suggests other metabolites may be increased.

Conclusion.

Sorafenib was poorly tolerated, and anti‐KS activity was modest. Strong CYP3A4 inhibitors may contribute to sorafenib toxicity, and ritonavir has previously been shown to be a CYP3A4 inhibitor. Alternate antiretroviral agents without predicted interactions should be used when possible for concurrent administration with sorafenib. The Oncologist 2017;22:505–e49

Metabolomic and Genome-wide Association Studies Reveal Potential Endogenous Biomarkers for OATP1B1

Transporter-mediated drug-drug interactions (DDIs) are a major cause of drug toxicities. Using published genome-wide association studies (GWAS) of the human metabolome, we identified 20 metabolites associated with genetic variants in organic anion transporter, OATP1B1 (P < 5 × 10-8 ). Of these, 12 metabolites were significantly higher in plasma samples from volunteers dosed with the OATP1B1 inhibitor, cyclosporine (CSA) vs. placebo (q-value < 0.2). Conjugated bile acids and fatty acid dicarboxylates were among the metabolites discovered using both GWAS and CSA administration. In vitro studies confirmed tetradecanedioate (TDA) and hexadecanedioate (HDA) were novel substrates of OATP1B1 as well as OAT1 and OAT3. This study highlights the use of multiple datasets for the discovery of endogenous metabolites that represent potential in vivo biomarkers for transporter-mediated DDIs. Future studies are needed to determine whether these metabolites can serve as qualified biomarkers for organic anion transporters. Quantitative relationships between metabolite levels and modulation of transporters should be established.

Interindividual Variability in Cytochrome P450-Mediated Drug Metabolism

The cytochrome P450 (P450) enzymes are the predominant enzyme system involved in human drug metabolism. Alterations in the expression and/or activity of these enzymes result in changes in pharmacokinetics (and consequently the pharmacodynamics) of drugs that are metabolized by this set of enzymes. Apart from changes in activity as a result of drug-drug interactions (by P450 induction or inhibition), the P450 enzymes can exhibit substantial interindividual variation in basal expression and/or activity, leading to differences in the rates of drug elimination and response. This interindividual variation can result from a myriad of factors, including genetic variation in the promoter or coding regions, variation in transcriptional regulators, alterations in microRNA that affect P450 expression, and ontogenic changes due to exposure to xenobiotics during the developmental and early postnatal periods. Other than administering a probe drug or cocktail of drugs to obtain the phenotype or conducting a genetic analysis to determine genotype, methods to determine interindividual variation are limited. Phenotyping via a probe drug requires exposure to a xenobiotic, and genotyping is not always well correlated with phenotype, making both methodologies less than ideal. This article describes recent work evaluating the effect of some of these factors on interindividual variation in human P450-mediated metabolism and the potential utility of endogenous probe compounds to assess rates of drug metabolism among individuals.

Recent examples on the clinical relevance of the CYP2D6 polymorphism and endogenous functionality of CYP2D6

The cytochrome P450 2D6 (CYP2D6) belongs to a group of CYPs considered of utmost importance in the metabolism of xenobiotics. Despite being of only minor abundance in the liver, it is involved in the clearance of >25% of marketed drugs. Accordingly, CYP2D6 can be very efficiently inhibited by a couple of commonly used drugs such as some antidepressants, although induction by any drug has not been observed thus far. CYP2D6 was also one of the first enzymes for which a highly polymorphic expression could be shown leading to a widespread range of functionality, from a complete lack of a functional enzyme to overexpression due to multiplication of active alleles. A clear relationship between the CYP2D6 genotype and adverse events during treatment with CNS-active drugs such as codeine, antidepressants, or antipsychotics could be demonstrated. More recently, some new aspects emerged about the potential endogenous function of CYP2D6 in terms of behavior and brain disorders.

Understanding and preventing drug-drug and drug-gene interactions

Concomitant administration of multiple drugs can lead to unanticipated drug interactions and resultant adverse drug events with their associated costs. A more thorough understanding of the different cytochrome P450 isoenzymes and drug transporters has led to new methods to try to predict and prevent clinically relevant drug interactions. There is also an increased recognition of the need to identify the impact of pharmacogenetic polymorphisms on drug interactions. More stringent regulatory requirements have evolved for industry to classify cytochrome inhibitors and inducers, test the effect of drug interactions in the presence of polymorphic enzymes, and evaluate multiple potentially interacting drugs simultaneously. In clinical practice, drug alert software programs have been developed. This review discusses drug interaction mechanisms and strategies for screening and minimizing exposure to drug interactions. We also provide future perspectives for reducing the risk of clinically significant drug interactions.

[Pharmacogenetics of clopidogrel and its clinical significance]

The review is devoted to pharmacogenetics of clopidogrel and its value for the clinic. Mechanism of action of clopidogrel and main trials which has proven its efficacy are presented as well as results of main large studies including authors own results demonstrating dependence of clinical efficacy of clopidogrel on carriage of polymorphisms of gene of CYP2C19 which accomplishes metabolism of the drug in the liver. Problems of interaction of clopidogrel with proton pump inhibitors and other drugs as well as ways of overcoming "resistance" to clopidogrel are considered. Clinical efficacy of other P2Y12 receptors of platelets in patients with IHD is characterized in comparison with clopidogrel.

Byakangelicin induces cytochrome P450 3A4 expression via transactivation of pregnane X receptors in human hepatocytes

BACKGROUND AND PURPOSE

Byakangelicin is found in extracts of the root of Angelica dahurica, used in Korea and China as a traditional medicine to treat colds, headache and toothache. As byakangelicin can inhibit the effects of sex hormones, it may increase the catabolism of endogenous hormones. Therefore, this study investigated the effects of byakangelicin on the cytochrome P450 isoform cytochrome (CY) P3A4 in human hepatocytes.

EXPERIMENTAL APPROACH

Cultures of human hepatocytes and a hepatoma cell line (Huh7 cells) were used. mRNA and protein levels were measured by quantitative reverse transcription-polymerase chain reaction and Western blot. Plasmid constructs and mutants were prepared by cloning and site-directed mutagenesis. Reporter (luciferase) activity was determined by transient co-transfection experiments.

KEY RESULTS

In human primary hepatocytes, byakangelicin markedly induced the expression of CYP3A4 both at the mRNA level (approximately fivefold) and the protein level (approximately threefold) but did not affect expression of human pregnane X receptor (hPXR). In reporter assays, byakangelicin activated CYP3A4 promoter in a concentration-dependent manner (EC₅₀ = 5 µM), and this activation was enhanced by co-transfection with hPXR. Further reporter assays demonstrated that the eNR4 binding element in the CYP3A4 promoter was required for the transcriptional activation of CYP3A4 by byakangelicin.

CONCLUSIONS AND IMPLICATIONS

Byakangelicin induced expression and activity of CYP3A4 in human hepatocytes. This induction was achieved by the transactivation of PXR and not by increased expression of PXR. Therefore, byakangelicin is likely to increase the expression of all PXR target genes (such as MDR1) and induce a wide range of drug-drug interactions.

In vitro inhibitory effect of West African medicinal and food plants on human cytochrome P450 3A subfamily

AIM OF THE STUDY

In Africa, medicinal plants are used intensively and concomitantly with allopathic medicines in the treatment of opportunity diseases by many patients or by healthy person to prevent diseases. However, there is little information about the interactions between medicines and botanical products used currently in West Africa area. Therefore, the aim of the present investigation is to study the effect of some plant products on CYP3A4, CYP3A5 and CYP3A7, three individual enzymes of CYP3A subfamily, in vitro.

MATERIALS AND METHODS

Teas and ethanolic extracts of medicinal, food and co-administered plants were evaluated on CYP3A4, CYP3A5 and CYP3A7 individual enzymes in vitro using fluorometric assays.

RESULTS

Extracts of adjuvant plants such as Aframomum cuspidatum, and Aframomum melegueta, as well as one medicinal plant (Harrisonia abyssinica) inhibited CYP3A4, CYP3A5 and CYP3A7 activity more than 90%. Phyllanthus amarus showed high inhibition of CYP3A5 and CYP3A7. Food plants (Solanum macrocarpon and Talinum triangulare) inhibited CYP3A4 and CYP3A5 less than 20%.

CONCLUSION

These results indicate that plants tested in this study affect in vitro the activity of the main three CYP3A subfamily enzymes. These active plants could interfere with the metabolism at phase I of conventional drugs in vivo as well act as pharmacoenhancers in herbal mixtures.

Pharamacogenetics and antidepressant treatment in integrative psychiatry perspective

The concept of individualized drug therapy on the basis of pharmacogenetics has become a central focus in the treatment of depression. There is an increasing agreement about the importance of polymorphisms in cytochrome P450 enzymes and the effects of drug-drug interactions in relation to the incidence of adverse effects. There has been also increasing focus on the role of the drug transporter P-glycoprotein (P-gp) with regard to drug penetration into the brain. P-gp at the blood-brain barrier can exert a profound effect on the ability of some antidepressants to enter the brain. In addition, genetic polymorphism of the serotonin transporter has been investigated in relationship to the therapeutic response to several antidepressants, especially SSRIs. However, prediction of response on the basis of variants of candidate genes is incipient and remains elusive.

[Effect of genetic polymorphism on the activity of drug transporters and its clinical significance]

Drug transport is an important source of inter-individual variations in drug responses and is also a common site where drug-drug interactions happen. In recent years, more and more novel identified transporters have been added into the transporter super family, and this trend will continue in the future. Among the transporter members of this family, ATP-dependent efflux transporter P-glycoprotein (MDR1) and organic anion transporters (OATP) are the most important proteins involved in drug transport. MDR1 is the most well known transporter. Widely distributed in tissues such as the gastrointestinal tract, liver, kidney and so on, MDR1 plays an important role in drug absorption, distribution and excretion. Its functional genetic polymorphisms have significantly changed the pharmacokinetics of its substrate drugs, which has important clinical implications. OATP expressed in multiple tissues, and it mediated the drug excretion through the bile acid and kidney. Some genetic polymorphism of OATP genes is the cause of some abnormal drug responses.

[Pharmacogenetic testing: soon before every prescription?]

Genetic polymorphisms have currently been described in more than 200 systems affecting pharmacological responses (cytochromes P450, conjugation enzymes, transporters, receptors, effectors of response, protection mechanisms, determinants of immunity). Pharmacogenetic testing, i.e. the profiling of individual patients for such variations, is about to become largely available. Recent progress in the pharmacogenetics of tamoxifen, oral anticoagulants and anti-HIV agents is reviewed to discuss critically their potential impact on prescription and contribution/limits for improving rational and safe use of pharmaceuticals. Prospective controlled trials are required to evaluate large-scale pharmacogenetic testing in therapeutics. Ethical, social and psychological issues deserve particular attention.

A global view of drug-therapy interactions

BACKGROUND

Network science is already making an impact on the study of complex systems and offers a promising variety of tools to understand their formation and evolution in many disparate fields from technological networks to biological systems. Even though new high-throughput technologies have rapidly been generating large amounts of genomic data, drug design has not followed the same development, and it is still complicated and expensive to develop new single-target drugs. Nevertheless, recent approaches suggest that multi-target drug design combined with a network-dependent approach and large-scale systems-oriented strategies create a promising framework to combat complex multi-genetic disorders like cancer or diabetes.

RESULTS

We here investigate the human network corresponding to the interactions between all US approved drugs and human therapies, defined by known relationships between drugs and their therapeutic applications. Our results show that the average paths in this drug-therapy network are shorter than three steps, indicating that distant therapies are separated by a surprisingly low number of chemical compounds. We also identify a sub-network composed by drugs with high centrality measures in the drug-therapy network, which represent the structural backbone of this system and act as hubs routing information between distant parts of the network.

CONCLUSION

These findings provide for the first time a global map of the large-scale organization of all known drugs and associated therapies, bringing new insights on possible strategies for future drug development. Special attention should be given to drugs which combine the two properties of (a) having a high centrality value in the drug-therapy network and (b) acting on multiple molecular targets in the human system.

Prävention unerwünschter Arzneimittelwirkungen bei älteren Patienten

Adverse drug reactions are among the most common adverse events and a significant cause of preventable morbidity and mortality. As multimorbidity and polypharmacy are frequent in this population, the elderly are at special risk for adverse drug events, although the calendar age has not been proved as independent risk factor in this context. In particular falls and delirium are clinically significant and typical adverse drug events in the elderly. In this review mechanisms and factors which determine adverse drug re actions are described, and possible strategies for an effective prevention are given. This covers pharmacokinetic, pharmacogenetic and pharmacodynamic aspects as well as factors influencing individual adherence to drug therapy. A significant portion of adverse drug reaction may be prevented by a thorough indication and prudent monitoring of pharmacotherapy. Also adherence to pharmacotherapy may be improved by tailored and individual means referring to the patient's needs and expectancies. In the elderly functional limitations such as reduced cognitive abilities, reduced visual acuity and impaired dexterity determine an ineffective pharmacotherapy and medication errors. Hereby these functional limitations are significant predictors of adverse drug events in the context of self-management of pharmacotherapy. Testing of functional abilities as provided in the geriatric assessment is helpful to identify these factors. Among altered pharmacokinetic factors in the elderly, reduced renal function is most important to avoid overdosage. Although a precise measurement of renal function is not possible in a bed-side manner, an estimation of actual renal function utilizing estimation-formulas should always take place.

Pharmacogenetics and pharmacogenomics of schizophrenia: a review of last decade of research

The last decade of research into the pharmacogenetics of antipsychotics has seen the development of genetic tests to determine the patients' metabolic status and the first attempts at personalization of antipsychotic treatment. The most significant results are the association between drug metabolic polymorphisms, mainly in cytochrome P450 genes, with variations in drug metabolic rates and side effects. Patients with genetically determined CYP2D6 poor metabolizer (PMs) status may require lower doses of antipsychotic. Alternatively, CYP2D6 ultrarapid matabolizers (UMs) will need increased drug dosage to obtain therapeutic response. Additionally, polymorphisms in dopamine and serotonin receptor genes are repeatedly found associated with response phenotypes, probably reflecting the strong affinities that most antipsychotics display for these receptors. In particular, there is important evidence suggesting association between dopamine 2 receptor (D2) polymorphisms (Taq I and -141-C Ins/Del) and a dopamine 3 receptor (D3) polymorphism (Ser9Gly) with antipsychotic response and drug-induced tardive dyskinesia. Additionally, there is accumulating evidence indicating the influence of a 5-HT2C polymorphism (-759-T/C) in antipsychotic-induced weight gain. Application of this knowledge to clinical practice is slowly gathering pace, with pretreatment determination of individual's drug metabolic rates, via CYP genotyping, leading the field. Genetic determination of patients' metabolic status is expected to bring clinical benefits by helping to adjust therapeutic doses and reduce adverse reactions. Genetic tests for the pretreatment prediction of antipsychotic response, although still in its infancy, have obvious implications for the selection and improvement of antipsychotic treatment. These developments can be considered as successes, but the objectives of bringing pharmacogenetic and pharmacogenomic research in psychiatric clinical practice are far from being realized. Further development of genetic tests is required before the concept of tailored treatment can be applied to psychopharmatherapy. This review aims to summarize the key findings from the last decade of research in the field. Current knowledge on genetic prediction of drug metabolic status, general response and drug-induced side effects will be reviewed and future pharmacogenomic and epigenetic research will be discussed.

Minocycline and riluzole brain disposition: interactions with p-glycoprotein at the blood-brain barrier

Amyotrophic lateral sclerosis is a neurodegenerative fatal disease. The only drug recognized to increase the survival time is riluzole(RLZ). In animal models, minocycline (MNC) delayed the onset of the disease and increased the survival time (in combination with RLZ). The objective of our work was to study the interactions between RLZ, MNC and the efflux pump p-glycoprotein (p-gp) at the blood-brain barrier. We investigated these two drugs as: (i) p-gp substrates by comparing their brain uptake in CF1 mdr1a (-/-) and mdr1a (+/+) mice, (ii) p-gp modulators by studying their effect on the cerebral uptake of digoxin. mdr1a (-/-) mice showed higher brain uptake of MNC and RLZ than mdr1a (+/+) (in a 1.6- and 1.4-fold, respectively); and in mdr1a (+/+) mice pre-treated with repeated doses of MNC, brain uptake of digoxin was increased. When both drugs were administrated to mdr1a (+/+) mice, MNC increased the brain uptake of RLZ in a 2.1-fold. In conclusion, MNC and RLZ are both p-gp substrates. MNC is also a p-gp inhibitor and increases the brain diffusion of RLZ. In vitro experiments with the GPNT cell line confirmed these results. These interactions should be taken into account in the design of future clinical trials.

Venlafaxine induces P-glycoprotein in human Caco-2 cells

PURPOSE

The objective of this study was to evaluate the effect of a treatment with venlafaxine on the expression of multidrug resistance-associated protein (MRP) gene and multidrug resistance-related proteins (MDR) in human colon carcinoma cells (Caco-2) compared to a known P-glycoprotein (PGY1) inducer, rifampine.

METHODS

Caco-2 cells were treated with venlafaxine (50 microM, 100 microM, 250 microM, and 500 microM) and rifampin (25 microM and 50 microM) to test the possible induction of MRP and MDR expression. The treatment times used were 1.5, 3, 6, 12, 24, 48, and 72 h. RNA was isolated from the cells, and MDR and MRP genes were amplified using PCR.

RESULTS

Both venlafaxine and rifampine had the most dramatic effect at the 50 microM concentration. There was an increase in MDR and MRP expression in Caco-2 cells after the acute treatment (1.5, 3, and 6 h) with venlafaxine. These results were similar to those with rifampine.

CONCLUSIONS

PGY1 contributes to renal and biliary elimination of drugs by transporting the drug out of the cell and back into the intestinal lumen, where drugs may be further metabolized by intestinal enzymes such as Cytochrome P (CYP)-450 3A4. Its function is to limit the bioavailability of orally administered compounds. Due to the increase in MDR and MRP gene expression seen after the acute treatment with venlafaxine, there could be a potential drug-drug interaction with other medications that are metabolized via CYP450-3A4 when coadministered with venlafaxine.

The effects of human CYP2C8 genotype and fluvoxamine on the pharmacokinetics of rosiglitazone in healthy subjects

AIMS

To determine the effect of CYP2C8 genotype and of fluvoxamine on the pharmacokinetics of rosiglitazone.

METHODS

Twenty-three healthy subjects with the following genotypes were included in a two-phase, open-label, cross-over trial: CYP2C8*3/ *3 (n = 3), CYP2C8*1/ *3 (n = 10) and CYP2C8*1/ *1 (n = 10). In Phase A, the subjects were given 4 mg rosiglitazone as a single oral dose. In Phase B, the subjects were treated with multiple oral doses of 50 mg fluvoxamine maleate for 3 days prior to the single oral administration of 4 mg rosiglitazone. Plasma concentrations of rosiglitazone and relative amounts of N-desmethylrosiglitazone were measured in both phases for 24 h after drug administration.

RESULTS

The pharmacokinetics of rosiglitazone and N-desmethylrosiglitazone were not significantly different between the CYP2C8 genotypic groups. Fluvoxamine caused a statistically significant (P = 0.0066) increase in the AUC(0-infinity) of rosiglitazone, with a geometric mean ratio of 1.21 [95% confidence interval (CI) 1.06-1.39]. The elimination half-life (t(1/2)) was also significantly higher (P = 0.0203) with a geometric mean ratio of 1.38 [95% CI 1.06-1.79]. The coadministration of fluvoxamine had no influence on the pharmacokinetics of N-desmethylrosiglitazone.

CONCLUSION

The importance of the CYP2C8*3 mutation in the in vivo metabolism of rosiglitazone could not be confirmed. Fluvoxamine increased the AUC(0-infinity) and t(1/2) of rosiglitazone moderately and hence may be a weak inhibitor of CYP2C8.

Unrecognized drug-drug interactions: a cause of intraoperative cardiac arrest?

Many physicians overlook, or are unaware of, most drug-drug interactions. In our patient, the local anesthetic used for an axillary block may have been the precipitating drug in a cascade of drug-drug interactions that resulted in a cardiac arrest. The combination of multiple preoperative drug-drug interactions prevented the return of a stable native cardiac rhythm for almost 24 h. The mechanisms of interactions of these frequently used drugs are described, and the reader is guided to sources that identify and simplify the understanding of potentially dangerous drug-drug interactions.

The influence of co-treatment with carbamazepine, amiodarone and statins on warfarin metabolism and maintenance dose

AIMS

Warfarin is a frequently used anticoagulant drug with narrow therapeutic index and high interindividual variability in the dose requirement. We have previously shown that warfarin dose is influenced by cytochrome P450 (CYP) 2C9 genotype, age, body weight and co-treatment with drugs that interfere with warfarin metabolism. As, in many patients, drug co-treatment cannot be avoided, we investigated the effect of co-treatment with carbamazepine, amiodarone and statins on warfarin metabolism and maintenance dose.

METHODS

Caucasian patients on stable maintenance warfarin therapy with CYP2C9*1/*1 genotype (n=82) were included in the study. Plasma concentrations of (S)- and (R)-warfarin as well as warfarin hydroxylated metabolites were determined using HPLC assay and corresponding clearances of (S)- and (R)-warfarin were calculated.

RESULTS

Patients co-treated with carbamazepine (n=5) had significantly higher plasma 10-hydroxywarfarin concentrations than patients not taking any interacting drugs (n=54) (median: 0.327 microg/ml vs 0.030 microg/ml, p=0.003). (S)- and (R)-warfarin clearances were also higher in the carbamazepine co-treated group (p=0.003), as were warfarin dose requirements (median: 9.00 mg/day vs 3.86 mg/day, p=0.003). Under the conditions of this study, patients co-treated with amiodarone (n=6) did not differ significantly regarding any measured characteristic from patients with no interacting drug treatment, while patients co-treated with simvastatin or lovastatin (n=17) had lower 10-hydroxywarfarin concentration (p=0.02).

CONCLUSIONS

We confirmed important interaction between carbamazepine and warfarin metabolism which can be of major clinical importance. If treatment with carbamazepine cannot be avoided, patients taking warfarin should be frequently monitored, especially when initiating or stopping carbamazepine therapy.

Bench to bedside: Pharmacogenomics, adverse drug interactions, and the cytochrome P450 system

As physicians attempt to improve the quality of health care, one area of particular concern has been preventable medical errors from adverse drug interactions. The cytochrome P450 family of enzymes has been implicated in a large number of these preventable, adverse drug interactions. This report reviews the basic biochemistry and pharmacogenomics underlying the reactions catalyzed by the cytochrome P450 family of enzymes. An emphasis is placed on the phenotypic variations within a population and the resulting clinical effects. In addition, six members of the cytochrome P450 superfamily that are responsible for the metabolism of the majority of pharmaceutical agents are profiled in detail. These enzymes, CYP3A4, CYP2D6, CYP2C9, CYP2C19, CYP2E1, and CYP1A2, are reviewed with regard to their phenotypic variation in the population and the resulting clinical and therapeutic implications.

Polymorphisme génétique et interactions médicamenteuses : leur importance dans le traitement de la douleur

OBJECTIVES

To evaluate the impact of certain genetic polymorphisms on variable responses to analgesics

SOURCES

Systematic review, by means of a structured computerized search in the Medline database (1966-2004). Articles in English and French were selected. References in relevant articles were also retrieved.

MAIN FINDINGS

Most analgesics are metabolized by CYP isoenzymes subject to genetic polymorphism. NSAIDs are metabolized by CYP2C9; opioids described as "weak" (codeine, tramadol), anti-depressants and dextromethorphan are metabolized by CYP2D6 and some "potent" opioids (buprenorphine, methadone or fentanyl) by CYP3A4/5. After the usual doses have been administered, drug toxicity or, on the contrary, therapeutic ineffectiveness may occur, depending on polymorphism and the substance. Drug interactions mimicking genetic defects because of the existence of CYP inhibitors and inducers, also contribute to the variable response to analgesics. Some opioids are substrates of P-gp, a transmembrane transporter also subject to genetic polymorphism. However, P-gp could only play a minor modulating role in man on the central effects of morphine, methadone and fentanyl.

CONCLUSION

In the near future, pharmacogenetics should enable us to optimize therapeutics by individualizing our approach to analgesic drugs and making numerous analgesics safer and more effective. The clinical usefulness of these individualized approaches will have to be demonstrated by appropriate pharmacoeconomic studies and analyses.

Allelic variants of cytochrome P450 2C9 modify the interaction between nonsteroidal anti-inflammatory drugs and coumarin anticoagulants

INTRODUCTION

Cytochrome P450 (CYP) plays a key role in the metabolism of coumarin anticoagulants and nonsteroidal anti-inflammatory drugs (NSAIDs). Because CYP2C9 is a genetically polymorphic enzyme, genetic variability could play an important role in the potential interaction between NSAIDs and coumarins. We investigated whether NSAIDs were associated with overanticoagulation during therapy with coumarins and evaluated the effect of the CYP2C9 polymorphisms on this potential interaction.

METHODS

We conducted a population-based cohort study among patients of an anticoagulation clinic who were treated with acenocoumarol or phenprocoumon between April 1, 1991, and May 31, 2003, and whose CYP2C9 status was known. Patients were followed up until an international normalized ratio (INR) of 6.0 or greater was reached or until the end of treatment, death, or the end of the study. Proportional hazards regression analysis was used to estimate the risk of an INR of 6.0 or greater in relation to concomitant use of a coumarin anticoagulant and NSAIDs after adjustment for several potentially confounding factors. To study effect modification by CYP2C9 genotype, stratified analyses were performed for wild-type patients and patients with a variant genotype.

RESULTS

Of the 973 patients in the cohort, 415 had an INR of 6.0 or greater. Several NSAIDs increased the risk of overanticoagulation. The risk of overanticoagulation was 2.98 (95% confidence interval, 1.09-7.02) in coumarin-treated patients taking NSAIDs with a CYP2C9*2 allele and 10.8 (95% confidence interval, 2.57-34.6) in those with a CYP2C9*3 allele.

CONCLUSIONS

Several NSAIDs were associated with overanticoagulation. For NSAIDs that are known CYP2C9 substrates, this risk was modified by allelic variants of CYP2C9. More frequent INR monitoring of patients taking NSAIDs is warranted.

Effect of the genotype on the pharmacokinetics, pharmacodynamics, and drug interactions of intravenous lorazepam in healthy volunteers

OBJECTIVE

Our objective was to investigate the effect of the uridine 5'-diphosphate-glucuronosyltransferase (UGT) 2B15 genetic polymorphism on the pharmacokinetics and pharmacodynamics of lorazepam in basal, inhibited, and induced metabolic states in healthy normal volunteers.

METHODS

Twenty-four healthy subjects were enrolled and grouped into UGT2B15*1/*1 or UGT2B15*2/*2 genotype groups. The pharmacokinetic and pharmacodynamic profiles of intravenous lorazepam were characterized before and after inhibition with 600 mg valproate once daily for 4 days and after induction with rifampin (INN, rifampicin) pretreatment (600 mg once daily for 10 days), with a washout period of 10 days between. The plasma concentrations of lorazepam and lorazepam glucuronide were analyzed before and at 0.25, 0.5, 1, 1.5, 2, 4, 6, 8, 12, 24, and 48 hours after lorazepam administration by liquid chromatography-tandem mass spectrometry. Visual analog scale assessments and psychomotor coordination tests were administered before and up to 12 hours after drug administration.

RESULTS

The UGT2B15*2/*2 group showed 0.58-fold (95% confidence interval, 0.43-0.72; P < .0001) lower systemic clearance during the basal state and 1.37-fold (95% confidence interval, 1.05-1.88; P = .037) higher area under the visual analog scale-time curve during the induced state compared with the UGT2B15*1/*1 group. The mean systemic clearance of lorazepam decreased by 20% in the inhibited state and increased by 140% in the induced state. During the inhibited or induced state, absolute values of clearance were consistently lower in the *2/*2 group, but the percent changes from baseline did not differ significantly by genotype.

CONCLUSIONS

Our results suggest that the UGT2B15*2 polymorphism is a major determinant of interindividual variability with respect to the pharmacokinetics and pharmacodynamics of lorazepam.

Pharmacokinetic interactions between omeprazole/pantoprazole and clarithromycin in health volunteers

The association omeprazole/clarithromycin is of current wide use in the treatment of Helicobacter pylori associated gastroduodenal ulcer. This combination may result in increased levels of omeprazole with potential interactions with commonly associated drugs. Kinetic/metabolic changes occurring after omeprazole/clarithromycin were compared to those occurring after pantoprazole/clarithromycin in healthy volunteers. Eight healthy volunteers, all males, age 25-34 years, all EM for CYP2C19, participated in a randomized, double blind crossover study in two periods of 7 days, separated by a 14-day washout. In each treatment period, subjects took either omeprazole 20mg b.i.d. together with clarithromycin 500 mg b.i.d., or pantoprazole 40 mg b.i.d. with the same dose of the antibiotic. The pharmacokinetic parameters of omeprazole and pantoprazole were compared to those after intake of both agents alone. Kinetics of unchanged clarithromycin was evaluated at the end of the two periods. The mean value of the area under the plasma concentration versus time curve (AUC) of unchanged omeprazole increased almost two-fold after concomitant administration of clarithromycin; the average 5-OH-omeprazole AUC was instead significantly reduced by 42%. Omeprazole clearance and volume of distribution were reduced significantly by 75 and 56%, respectively, after administration of the drug with clarithromicyn. No significant changes of the kinetic of pantoprazole and metabolites were observed. Kinetics of clarithromycin did not differ after the two associated treatments. The administration of clarithromycin with two different proton pump inhibitors indicates that the antibiotic can markedly increase omeprazole, not pantoprazole, levels. This observation may result in a better therapeutic response to omeprazole, but it may also potentially affect either the metabolism of CYP3A4 substrates or interfere with the absorption of drugs requiring an intact gastric digestion system.

Pharmacokinetics, pharmacodynamics and drug interaction potential of enfuvirtide

Enfuvirtide, the first fusion inhibitor approved for the treatment of HIV-1 infection, is a synthetic peptide that binds to HIV-1 glycoprotein 41, blocking the fusion of viral and cellular membranes. When administered subcutaneously at the recommended dose of 90 mg twice daily with optimised background antiretroviral therapy, enfuvirtide significantly reduces plasma HIV-1 RNA levels up to 48 weeks compared with optimised background therapy alone. Enfuvirtide exhibits a small volume of distribution (5.48 L), low systemic clearance (1.4 L/h) and high plasma protein binding (92%). Less than 17% of enfuvirtide is converted to a minimally active deaminated form of the parent drug. Both enfuvirtide and its metabolite are primarily eliminated via catabolism to amino acid residues. Following subcutaneous administration, enfuvirtide is almost completely absorbed, and exposure increases almost linearly with dose over the range 45-180 mg. When administered at the recommended dose in adults, subcutaneous absorption is slow and protracted, resulting in relatively flat steady-state plasma concentration-time profiles. Bioavailability is high (84.3%) and the elimination half-life (3.8 hours) supports twice-daily administration. Comparable absorption was observed from three different anatomical injection sites. The pharmacokinetic-pharmacodynamic relationship indicates that the recommended dose, in combination with other active antiretrovirals, is optimal. Enfuvirtide clearance is influenced to a small extent by sex and bodyweight but this does not necessitate dosage adjustment. In vitro and in vivo studies indicate that enfuvirtide has a low potential to interact with concomitantly administered drugs. Enfuvirtide did not influence concentrations of drugs metabolised by cytochrome P450 (CYP) 3A4, CYP2D6 or N-acetyltransferase, and had only minimal effects on those metabolised by CYP1A2, CYP2E1 or CYP2C19. Coadministration of ritonavir, ritonavir-boosted saquinavir or rifampicin (rifampin) did not result in clinically significant changes in enfuvirtide pharmacokinetics. In HIV-1-infected paediatric patients, subcutaneous dosages based on bodyweight (2 mg/kg twice daily) produce pharmacokinetics broadly similar to those observed in adults administered 90 mg twice daily.

UDP-glucuronosyltransferases and clinical drug-drug interactions

UDP-glucuronosyltransferase (UGT) enzymes catalyze the conjugation of various endogenous substances (e.g., bilirubin) and exogenous compounds (e.g., drugs). The human UGT superfamily is comprised of 2 families (UGT1 and UGT2) and 3 subfamilies (UGT1A, UGT2A, and UGT2B). Many of the individual UGT enzymes are expressed not only in liver but also in extrahepatic tissues, where the extent of glucuronidation can be substantial. Several others (e.g., UGT1A7, UGT1A8, and UGT1A10) are expressed only in extrahepatic tissues. The molecular regulation of UGT enzyme is still not fully understood, but various transcription factors appear to play a regulatory role. The expression of individual UGT enzymes is subject to genetic polymorphism and these enzymes can be inhibited or induced by xenobiotics. Experimental evidence in humans indicates that the glucuronidation of acetaminophen, codeine, zidovudine, carbamazepine, lorazepam, and propafenone can influenced by specific interacting drugs. In contrast, the glucuronidation of diflunisal, morphine, naproxen, and temazepam is not affected appreciably by the drugs investigated to date. In general, UGT-mediated human drug interaction studies are difficult to interpret. The factors that complicate the interpretation of this type of drug interaction data are discussed.

[Metabolism of drugs. III. Genetic factors inducing and inhibiting metabolism]

In this review, a role of influence of some genetic factors on drug metabolism in liver was presented. The drug induction and inhibition of CYP enzymes whose activity is strictly genetically determined (slow and fast metabolizers), were extensively discussed. The influence of age (activity of microsomal enzymes in pediatric patients) and of food components (grapefruit juice inducing CYP enzymes) was also presented in this paper.

Using genomics to help predict drug interactions

This article proposes using genomic information to help tailor the output of a drug interaction program for a patient. This paper focuses on a particular CYP450 enzyme to illustrate adding genomic information to an existing drug interaction database. The data are formatted as an Extensible Markup Language (XML) document. The additional interaction information based on genomics for a patient is added to an XML document using XML tags. The suggestion is to combine specifics about a patient's genome with genomic information in the drug interactions database to increase the accuracy and details of a drug interaction program.

Pharmacogenomics and Systems Biology of Membrane Transporters

Membrane transporters are essential for fundamental cellular functions and normal physiological processes. These molecules influence drug absorption and distribution, and play key roles in drug therapeutic effects. A primary goal of current research in drug discovery and development is to fully understand the interaction between transporters and drugs at both system level and individual level for personalized therapy. Pharmacogenomics studies the genetic basis of the individual variations in response to drug therapy, whereas systems biology provides the understanding of biological processes at the system level. The integration of pharmacogenomics with systems biology in membrane transporter study is necessary to solve complex problems in diseases and drug effects. Such integration provides insight to key issues of pharmacogenomics and systems biology of membrane transporters. These key issues include the correlations between structure and function, genotype and phenotype, and systematic interactions between different transporters, between transporters and other proteins, and between transporters and drugs. The exploration in these key issues may ultimately contribute to the personalized medicine with high efficacy but less toxicity, which is the overall goal of pharmacogenomics and systems biology.

The Epidemiologic Approach to Pharmacogenomics

The epidemiologic approach enables the systematic evaluation of potential improvements in the safety and efficacy of drug treatment which might result from targeting treatment on the basis of genomic information. The main epidemiologic designs are the randomized control trial, the cohort study, and the case-control study, and derivatives of these proposed for investigating gene-environment interactions. However, no one design is ideal for every situation, and methodological issues, notably selection bias, information bias, confounding and chance, all play a part in determining which study design is best for a given situation. There is also a need to employ a range of different designs to establish a portfolio of evidence about specific gene-drug interactions. In view of the complexity of gene-drug interactions, pooling of data across studies is likely to be needed in order to have adequate statistical power to test hypotheses. We suggest that there may be opportunities (i) to exploit samples from trials already completed to investigate possible gene-drug interactions; (ii) to consider the use of the case-only design nested within randomized controlled trials as a possible means of reducing genotyping costs when dichotomous outcomes are being investigated; and (iii) to make use of population-based disease registries that can be linked with tissue samples, treatment information and death records, to investigate gene-treatment interactions in survival.

Pharmacogenetics and enzyme induction/inhibition properties of antiepileptic drugs

One of the major differences between the older antiepileptic drugs (AEDs) and the newer AEDs is the potential of the older AEDs for significant interactions with other medications. Many of the drug-drug interactions involving the older AEDs are reciprocal, i.e., both drugs affect each other. In contrast, the newer AEDs have either no or limited drug interaction potential. Despite our extensive understanding of and our ability to predict drug-drug interactions, serious drug interactions still occur. More than 30% of all new seizures occur in the elderly, and because this population may be taking a variety of other medications the addition of an AED can have profound impact on these other therapies. In women, the use of enzyme-inducing AEDs can cause significant alterations of sex hormones and can decrease the efficacy of oral contraceptives. In children and adults, the use of enzyme inducers may result in long-term endocrine effects, including bone loss and lipid, thyroid, and sex hormone abnormalities. Phenytoin and phenobarbital are metabolized by cytochrome P450 isozymes, with activity dependent on genetic polymorphism (CYP2C9, CYP2C19). The dosing of the newer AEDs is not affected by genetic polymorphism. The decreased induction and inhibition effects and the lack of significant genetic polymorphism of the newer AEDs allow increased ease of use and perhaps greater safety, especially for patients taking multiple medications.

The putative glutamate receptor 1.1 (AtGLR1.1) in Arabidopsis thaliana regulates abscisic acid biosynthesis and signaling to control development and water loss

The involvement of the putative glutamate receptor 1.1 (AtGLR1.1) gene in the regulation of abscisic acid (ABA) biosynthesis and signaling was investigated in Arabidopsis. Seeds from AtGLR1.1-deficient (antiAtGLR1.1) lines had increased sensitivity to exogenous ABA with regard to the effect of the hormone on the inhibition of seed germination and root growth. Seed germination, which was inhibited by an animal ionotropic glutamate receptor antagonist, 6,7-dinitroquinoxaline-2,3-[1H,4H]-dione, was restored by co-incubation with an inhibitor of ABA biosynthesis, fluridone. These results confirm that germination in antiAtGLR1.1 lines was inhibited by increased ABA. When antiAtGLR1.1 and WT seeds were co-incubated in fluridone and exogenous ABA, the antiAtGLR1.1 seeds were more sensitive to ABA. In addition, the antiAtGLR1.1 lines exhibited altered expression of ABA biosynthetic (ABA) and signaling (ABI) genes, when compared with WT. Combining the physiological and molecular results suggest that ABA biosynthesis and signaling in antiAtGLR1.1 lines are altered. ABA levels in leaves of antiAtGLR1.1 lines are higher than those in WT. In addition, the antiAtGLR1.1 lines had reduced stomatal apertures, and exhibited enhanced drought tolerance due to deceased water loss compared with WT lines. The results from these experiments imply that ABA biosynthesis and signaling can be regulated through AtGLR1.1 to trigger pre- and post-germination arrest and changes in whole plant responses to water stress. Combined with our earlier results, these findings suggest that AtGLR1.1 integrates and regulates the different aspects of C, N and water balance that are required for normal plant growth and development.

Increased liability of tramadol?warfarin interaction in individuals with mutations in the cytochrome P 450 2D6 gene

OBJECTIVE

This study aimed to investigate the importance of cytochrome P(450) enzymes for the reported interaction between tramadol and warfarin.

MATERIALS AND METHODS

Cases of suspected interaction between tramadol and warfarin resulting in International Normalised Ratios increases that were reported to the Swedish Adverse Drug Reactions Advisory Committee until March 2003 were included. Ten cases had been genotyped for known polymorphisms of CYP2D6, CYP2C9 and CYP2C19.

RESULTS

Seven of ten patients carried defective CYP2D6 alleles (population prevalence 42.2%) (one-sided binomial test, P=0.07). A further patient received concomitant drug treatments that may have resulted in CYP2D6 enzyme inhibition.

CONCLUSION

The liability to an interaction between tramadol and warfarin may be related to the CYP2D6 activity.

Genetic polymorphisms, drugs, and proarrhythmia

Humans vary widely in their response to drug therapy. This may reflect variability in the relationship between a drug dose and the concentrations of drug and metabolite(s) at relevant target sites; this is termed pharmacokinetic variability. Another mechanism is that individuals vary in their response to identical exposures to drug (pharmacodynamic variability). In this case, there may be variability in the target molecule(s) with which a drug interacts, or more generally in the broad biologic context in which the drug-target interaction occurs; for example, ischemia, electrolyte disturbances, or hypertrophy can all modulate drug effects. Variants in the genes encoding proteins important for pharmacokinetics or for pharmacodynamics have now been described as important contributors to variable drug actions, including proarrhythmia, and are described here. These increasingly well-recognized examples have two important implications; first, it may be possible to develop drugs devoid of heretofore-unexplained adverse effects and, second, it may become possible to preselect drug for individual patients based on specific genetic factors.

[Adverse effects and drug interactions]

Adverse drug reactions represent a common clinical problem. They are partly induced by a large variability in drug response, which results from the complex interplay between pharmacokinetics, pharmacodynamics and other disease-associated factors. The review describes metabolic changes caused by polymorphism in the cytochrome P450 and gives examples of induction and inhibition of this enzyme system in relation to adverse drug interaction. From the clinical point of view, attention should be paid especially to antidiabetics, anticoagulants and phenytoin. Therapeutic drug monitoring and genetic-based individualization of the therapy with polymorphically metabolized drugs with narrow therapeutic range can contribute to the decreased incidence of adverse drug reactions.