Epidemiology of Cytochrome P450-mediated Drug-Drug Interactions

Drug-drug interactions (DDIs) comprise an important cause of adverse drug reactions leading to excess hospitalizations. Drug metabolism is catalyzed by 75% by cytochrome P450 (CYP) enzymes and thus they are often involved in pharmacokinetic DDIs. In general, DDIs are studied in randomized controlled clinical trials in selected study populations. The overall aim of the present studies was to perform observational pharmacoepidemiological surveys on CYP-mediated DDIs in diseases important at the population level. The prevalence of co-administrations of four prodrugs (losartan, codeine, tramadol, and clopidogrel), three sulphonylureas (glibenclamide, glimepiride, and glipizide), or two statins (lovastatin and simvastatin) with well established agents altering CYP activity, as well as of statins with fibrates, was studied in Finland utilizing data from a university hospital medication database (inpatients) and the National Prescription Register of the Social Insurance Institution of Finland, Kela (outpatients). Clinical consequences of potential DDIs were estimated by reviewing laboratory data, and information from hospital care and cause-of-death registers. Concomitant use of study substrates with interacting medication was detected in up to one fifth of patients in both hospital and community settings. Potential CYP3A4 interactions in statin users did not manifest in clear adverse laboratory values but pharmacodynamic DDIs between statins and fibrates predisposed patients to muscular toxicity. Sulphonylurea DDIs with CYP2C9 inhibitors increased the risk of hypoglycaemia. CYP3A4 inhibitor use with clopidogrel was not associated with significant changes in mortality but non-fatal thrombosis and haemorrhage complications were seen less often in this group. Concomitant administration of atorvastatin with clopidogrel moderately attenuated the antithrombotic effect by clopidogrel. The overall mortality was increased in CYP3A4 inducer and clopidogrel co-users. Atorvastatin used concomitantly with prodrug clopidogrel seems to be beneficial in terms of total and LDL cholesterol concentrations, and overall mortality compared with clopidogrel use without interacting medication. In conclusion, CYP-mediated DDIs are a common and often unrecognized consequence of irrational drug prescribing.

Pharmacokinetics of Oxycodone and Paracetamol in the Elderly. Clinical Pharmacokinetic Study on Orthopaedic Surgical Patients and Healthy Volunteers

The proportion of elderly people over 65 years of age in Finland is expected to grow to over 25% by the 2025. It has been estimated that elderly people today consume nearly 40% of all drugs. Age brings about number of physiological changes that may affect the disposition, metabolism and excretion of drugs. The function of heart, lungs, liver and kidneys decreases even in healthy people, as they get older. The proportion of total body water decreases and the relative fat percentage increases. Also several other factors such as concurrent diseases, concomitant medication and nutritional factors have an effect on drug therapy in elderly. Age increases the risk of adverse drug reactions, which most often are dose-dependent. Despite all this there are not enough studies involving the elderly people and the elderly are most often excluded from clinical trials. Oxycodone is a strong opioid analgesic, which is used to treat moderate or severe pain. Paracetamol is a widely used nonopioid analgesic, which has become popular in the treatment of pain in many patient groups. In this series of studies the pharmacokinetics of oral and intravenous oxicodone as well as intravenous paracetamol in the elderly and young adult patients were investigated. Also a study investigating the interaction of oral antibiotic clarityhromycin, a known cytochrome P450 (CYP) 3A4 inhibitor, with oxycodone pharmacokinetics and pharmacodynamics in elderly and young healthy volunteers was carried out. The pharmacokinetics of oxycodone showed a clear age depency. Patients over 70 years had 50-80% higher mean exposure to oral oxycodone and a twofold greater plasma concentration than young adults 12 h after ingestion of the drug. Elderly patients had 40-80% greater exposure to intravenous oxycodone and patients over 80 years had over twofold greater plasma concentrations 8 h post dose than the young adults. The elderly patients had also greater exposure to intra venous paracetamol compared to young adults. Clarithromycin increased the exposure to oral oxycodone in both young and elderly volunteers. The elderly had marked interindividual variation in the pharmacokinetics and pharmacodynamics when clarithromycin was given concomitantly with oxycodone. Because the pharmacokinetics of oxycodone and intravenous paracetamol depend on the age of the subject, it is important to titrate the analgesic dose individually in the elderly.

Pharao - lisäpotkua Sfinxiin

Lääkehoidon arvioinnin sähköiset työkalut ja niiden hyödyntäminen potilastyössä.

Potential of the Osteoclast’s Proton Pump as a Drug Target in Osteoporosis

Decreasing bone mass during aging predisposes to fractures and it is estimated that every second woman and one in five men will suffer osteoporotic fractures during their lifetime. Bone is an adaptive tissue undergoing continuous remodeling in response to physical and metabolic stimuli. Bone mass decreases through a net negative balance in the bone remodeling process of bone, in which the new bone incompletely replaces the resorbed bone mass. Bone resorption is carried out by the osteoclasts; the bone mineral is solubilized by acidification and the organic matrix is subsequently degraded by proteases. Several classes of drugs are available for prevention of osteoporotic fractures. They act by different mechanisms to increase bone mass, and some of them act mainly as antiresorptives by inhibition of osteoclast formation or their function. Optimally, a drug should act selectively on a specific process, since other processes affected usually result in adverse effects. The purpose of this study was to evaluate whether the osteoclastic vacuolar adenosine trisphosphatases (V-ATPase), which drives the solubilization of bone mineral, can be selectively inhibited despite its ubiquitous cellular functions. The V-ATPase is a multimeric protein composed of 13 subunits of which six possesses two or more isoforms. Selectivity for the osteoclastic V-ATPase could be provided if it has some structural uniqueness, such as a unique isoform combination. The a3 isoform of the 116kDa subunit is inevitable for bone resorption; however, it is also present in, and mainly limited to, the lysosomes of other cells. No evidence of a structural uniqueness of the osteoclastic V-ATPase compared to the lysosomal V-ATPase was found, although this can not yet be excluded. Thus, an inhibitor selective for the a3 isoform would target the lysosomal V-ATPase as well. However, the results suggest that selectivity for bone resorption over lysosomal function can be obtained by two other mechanisms, suggesting that isoform a3 is a valid target. The first is differential compensation; bone resorption depends on the high level of a3 expression, and is not compensated for by other isoforms, while the lower level of a3 in lysosomes of other cells may be partly compensated for. The second mechanism is because the bone resorption process itself is fundamentally different from lysosomal acidification because of the chemistry of bone dissolution and the anatomy of the resorbing osteoclast. By this mechanism, full inhibition of bone resorption is obtained with more than tenfold lower inhibitor concentration than those needed to fully inhibit lysosomal acidification. The two mechanisms are additive. Based on the results, we suggest that bone resorption can be selectively inhibited if VATPase inhibitors that are sufficiently selective for the a3 isoform over the other isoforms are developed.

The spindle assembly checkpoint as a drug target - Novel small-molecule inhibitors of Aurora kinases

Cell division (mitosis) is a fundamental process in the life cycle of a cell. Equal distribution of chromosomes between the daughter cells is essential for the viability and well-being of an organism: loss of fidelity of cell division is a contributing factor in human cancer and also gives rise to miscarriages and genetic birth defects. For maintaining the proper chromosome number, a cell must carefully monitor cell division in order to detect and correct mistakes before they are translated into chromosomal imbalance. For this purpose an evolutionarily conserved mechanism termed the spindle assembly checkpoint (SAC) has evolved. The SAC comprises a complex network of proteins that relay and amplify mitosis-regulating signals created by assemblages called kinetochores (KTs). Importantly, minor defects in SAC signaling can cause loss or gain of individual chromosomes (aneuploidy) which promotes tumorigenesis while complete failure of SAC results in cell death. The latter event has raised interest in discovery of low molecular weight (LMW) compounds targeting the SAC that could be developed into new anti-cancer therapeutics. In this study, we performed a cell-based, phenotypic high-throughput screen (HTS) to identify novel LMW compounds that inhibit SAC function and result in loss of cancer cell viability. Altogether, we screened 65 000 compounds and identified eight that forced the cells prematurely out of mitosis. The flavonoids fisetin and eupatorin, as well as the synthetic compounds termed SACi2 and SACi4, were characterized in more detail utilizing versatile cell-based and biochemical assays. To identify the molecular targets of these SAC-suppressing compounds, we investigated the conditions in which SAC activity became abrogated. Eupatorin, SACi2 and SACi4 preferentially abolished the tensionsensitive arm of the SAC, whereas fisetin lowered also the SAC activity evoked by lack of attachments between microtubules (MTs) and KTs. Consistent with the abrogation of SAC in response to low tension, our data indicate that all four compounds inhibited the activity of Aurora B kinase. This essential mitotic protein is required for correction of erratic MT-KT attachments, normal SAC signaling and execution of cytokinesis. Furthermore, eupatorin, SACi2 and SACi4 also inhibited Aurora A kinase that controls the centrosome maturation and separation and formation of the mitotic spindle apparatus. In line with the established profound mitotic roles of Aurora kinases, these small compounds perturbed SAC function, caused spindle abnormalities, such as multi- and monopolarity and fragmentation of centrosomes, and resulted in polyploidy due to defects in cytokinesis. Moreover, the compounds dramatically reduced viability of cancer cells. Taken together, using a cell-based HTS we were able to identify new LMW compounds targeting the SAC. We demonstrated for the first time a novel function for flavonoids as cellular inhibitors of Aurora kinases. Collectively, our data support the concept that loss of mitotic fidelity due to a non-functional SAC can reduce the viability of cancer cells, a phenomenon that may possess therapeutic value and fuel development of new anti-cancer drugs.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.