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HINTERGRUND UND ZIELE: Es ist allgemein anerkannt, dass neben Umweltfaktoren auch erbliche Faktoren in hohem Maße für interindividuelle Unterschiede in der Wirkweise von Arzneimitteln ursächlich sind. Die Spannweite der Arzneimittelwirkung bei gleicher Dosis kann individuell von Therapieversagen bis hin zu toxischer Überdosierung reichen und ist dabei stark von Arzneimittel-metabolisierenden Enzymen und Transportern beeinflusst. Genetische Varianten können teilweise interindividuelle Unterschiede in der Aktivität dieser Enzyme und Transporter erklären. Es bleibt jedoch unbekannt, wie viel der Variation in der Aktivität durch Erblichkeit bedingt ist und nicht durch bereits bekannte genetische Varianten erklärt werden kann. Primäres Ziel der Studie war es, diesen unbekannten erblichen Anteil in der Variation der Aktivität der Enzyme CY2D6 und CYP2C9 sowie des Transporters OATP1B1 zu quantifizieren. METHODEN: Die Erblichkeit in der Variation der Aktivität von CY2D6, CYP2C9 und OATP1B1 wurde in 20 mono- und 9 dizygoten, gleichgeschlechtlichen Zwillingspaaren untersucht. Die Testsubstanzen Metoprolol (CYP2D6) und Torasemid (CYP2C9 und OATP1B1) wurden jedem Studienteilnehmer wiederholt verabreicht und die Fläche unter der Kurve bis unendlich (AUC0-inf) für jedes Medikament und seinen Metaboliten als Marker der Enzym- (CYP2D6, CYP2C9) und Transporter- (OATP1B1) Aktivitäten bestimmt. Erblichkeit wurde mithilfe von Formeln mit den Korrelationskoeffizienten der Geschwister in den Gruppen mono- und dizygote Zwillingspaare, durch eine Strukturgleichungsmodellierung und durch Vergleich der intra- und interindividuellen Variation berechnet. ERGEBNISSE: Es wurde ein hohe Erblichkeit in der Variation der Aktivität von CYP2D6, CYP2C9 und OATP1B1 berechnet. Für CYP2D6 lag die Erblichkeit bei 88,5% -100%, für CYP2C9 und OATP1B1 bei 81% - 100%. Die bekannten genetischen Varianten konnten lediglich einen geringen Anteil der Variation in der AUC0-inf in der Studienpopulation erklären (38,2% durch genetische Varianten in CYP2D6, 6,5% durch genetische Varianten in CYP2C9 und 20,4% durch genetische Varianten in OATP1B1). FAZIT: Die Berechnungen zeigen, dass Erblichkeit einen großen Einfluss auf die Variation in der Aktivität der Enzyme CYP2D6, CYP2C9 und den Transporter OATP1B1 hat. Bekannte genetische Varianten können hiervon nur einen Teil erklären. Weitere Untersuchungen zu genetischen Regulation der Wirkweise von Arzneimitteln erscheinen vielversprechend.

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Drug transport across cells and cell membranes in the human body is crucial for the pharmacological effect of drugs. Active transport governed by transport proteins plays an important role in this process. A vast number of transport proteins with a wide tissue distribution have been identified during the last 15 years. Several important examples of their role in drug disposition and drug-drug interactions have been described to date. Investigation of drug-drug interactions at the transport protein level are therefore of increasing interest to the academic, industrial and regulatory research communities. The gene expression of transport proteins involved in drug transport was investigated in the jejunum, liver, kidney and colon to better understand their influence on the ADMET properties of drugs. In addition, the gene and protein expression of transport proteins in cell lines, widely used for predictions of drug transport and metabolism, was examined. The substrate and inhibitor heterogeneity of many transport proteins makes it difficult to foresee whether the transport proteins will cause drug-drug interactions. Therefore, in vitro assays for OCT1 and OATP1B1, among the highest expressed transport proteins in human liver, were developed to allow investigation of the inhibitory patterns of these proteins. These assays were used to investigate two data sets, consisting of 191 and 135 registered drugs and drug-like molecules for the inhibition of OCT1 and OATP1B1, respectively. Numerous new inhibitors of the transport proteins were identified in the data sets and the properties governing inhibition were determined. Further, antidepressant drugs and statins displayed strong inhibition of OCT1 and OATP1B1, respectively. The inhibition data was used to develop predictive in silico models for each of the two transport proteins. The highly polymorphic nature of some transport proteins has been shown to affect drug response and may lead to an increased risk of drug-drug interactions, and therefore, the OCT1 in vitro assay was used to study the effect of common genetic variants of OCT1 on drug inhibition and drug-drug interactions. The results indicated that OCT1 variants with reduced function were more susceptible to inhibition. Further, a drug-drug interaction of potential clinical significance in the genetic OCT1 variant M420del was proposed. In summary, gene expression of transport proteins was investigated in human tissues and cell lines. In vitro assays for two of the highest expressed liver transport proteins were used to identify previously unknown SLC transport protein inhibitors and to develop predictive in silico models, which may detect previously known drug-drug interactions and enable new ones to be identified at the transport protein level. In addition, the effect of genetic variation on inhibition of the OCT1 was investigated.

The liver is the major detoxifying organ, clearing the blood from drugs and other xenobiotics. The extent of hepatic clearance (CL) determines drug exposure and hence, the efficacy and toxicity associated with exposure. Drug-drug interactions (DDIs) that alter the hepatic CL may cause more or less severe outcomes, such as adverse drug reactions. Accurate predictions of drug CL and DDI risk from in vitro data are therefore crucial in drug development. Liver CL depends on several factors including the activities of transporters involved in the hepatic uptake and efflux. The work in this thesis aimed at developing new in vitro and in silico methods to predict hepatic transporter-mediated CL and DDIs in vivo. Particular emphasis was placed on interactions involving the hepatic uptake transporters OATP1B1, OATP1B3, and OATP2B1. These transporters regulate the plasma concentration-time profiles of many drugs including statins. Inhibition of OATP-mediated transport by 225 structurally diverse drugs was investigated in vitro. Several novel inhibitors were identified. The data was used to develop in silico models that could predict OATP inhibitors from molecular structure. Models were developed for static and dynamic predictions of in vivo transporter-mediated drug CL and DDIs. These models rely on a combination of in vitro studies of transport function and mass spectrometry-based quantification of protein expression in the in vitro models and liver tissue. By providing estimations of transporter contributions to the overall hepatic uptake/efflux, the method is expected to improve predictions of transporter-mediated DDIs. Furthermore, proteins of importance for hepatic CL were quantified in liver tissue and isolated hepatocytes. The isolation of hepatocytes from liver tissue was found to be associated with oxidative stress and degradation of transporters and other proteins expressed in the plasma membrane. This has implications for the use of primary hepatocytes as an in vitro model of the liver. Nevertheless, by taking the altered transporter abundance into account using the method developed herein, transport function in hepatocyte experiments can be scaled to the in vivo situation. The concept of protein expression-dependent in vitro-in vivo extrapolations was illustrated using atorvastatin and pitavastatin as model drugs.

Indiana University-Purdue University Indianapolis (IUPUI) / Drug-drug interactions (DDIs) refer to situations where one drug affects the pharmacokinetics or pharmacodynamics of another. DDIs represent a major cause of morbidity and mortality. A common adverse drug reaction (ADR) that can result from, or be exacerbated by DDIs is drug-induced myopathy. Identifying DDIs and understanding their underlying mechanisms is key to the prevention of undesirable effects of DDIs and to efforts to optimize therapeutic outcomes. This dissertation is dedicated to identification of clinically important myopathic DDIs and to elucidation of their underlying mechanisms. Using data mined from the published cytochrome P450 (CYP) drug interaction literature, 13,197 drug pairs were predicted to potentially interact by pairing a substrate and an inhibitor of a major CYP isoform in humans. Prescribing data for these drug pairs and their associations with myopathy were then examined in a large electronic medical record database. The analyses identified fifteen drug pairs as DDIs significantly associated with an increased risk of myopathy. These significant myopathic DDIs involved clinically important drugs including alprazolam, chloroquine, duloxetine, hydroxychloroquine, loratadine, omeprazole, promethazine, quetiapine, risperidone, ropinirole, trazodone and simvastatin. Data from in vitro experiments indicated that the interaction between quetiapine and chloroquine (risk ratio, RR, 2.17, p-value 5.29E-05) may result from the inhibitory effects of quetiapine on chloroquine metabolism by cytochrome P450s (CYPs). The in vitro data also suggested that the interaction between simvastatin and loratadine (RR 1.6, p-value 4.75E-07) may result from synergistic toxicity of simvastatin and desloratadine, the major metabolite of loratadine, to muscle cells, and from the inhibitory effect of simvastatin acid, the active metabolite of simvastatin, on the hepatic uptake of desloratadine via OATP1B1/1B3. Our data not only identified unknown myopathic DDIs of clinical consequence, but also shed light on their underlying pharmacokinetic and pharmacodynamic mechanisms. More importantly, our approach exemplified a new strategy for identification and investigation of DDIs, one that combined literature mining using bioinformatic algorithms, ADR detection using a pharmacoepidemiologic design, and mechanistic studies employing in vitro experimental models.