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PubMed2000

Physician versus computer knowledge of potential drug interactions in the emergency department.

INTRODUCTION: Proliferation of Food and Drug Administration-approved drugs makes it impossible for emergency medicine (EM) faculty to stay current on potential interactions between drugs, and with diseases, laboratory tests, and ethanol. A computer database may augment physician knowledge. OBJECTIVES: To compare the performance of EM faculty and an "expert" emergency physician (EP) with that of a criterion standard computer database in identifying potential drug interactions, and to report the incidence of drug-ethanol and drug-laboratory test interactions. METHODS: This was a retrospective review of 276 emergency department charts for drug, ethanol, lab, and medical history. Evaluation by both EM faculty and an "expert" EP of patient history was done to identify potential interactions, and comparison with the Micromedex Drug-Reax database for potential interactions (graded minor, moderate, or major) was made. Clinical significance of potential interactions was judged by a second EM faculty member. RESULTS: Seventeen percent of the patients had potential drug-drug interactions, and 25% of these were judged to be clinically significant. Up to 52% of the patients had potential drug-ethanol interactions, while 38% of the patients could have potential drug-lab interactions. Sensitivity, specificity, and positive and negative predictive values of the EM faculty for potential drug-drug interactions compared with the computer were poor, at 14%, 58%, 6%, and 23%, respectively. The corresponding values for the "expert" EP were 25%, 86%, 26%, and 85%. The "expert" EP was statistically better than the EM faculty, but still less sensitive and predictive than the computer. CONCLUSIONS: A computer can aid the physician in avoiding potential drug interactions. Prospective validation of these findings should be done.

California↗
PubMed2005

Bimolecular fluorescence complementation analysis of cytochrome p450 2c2, 2e1, and NADPH-cytochrome p450 reductase molecular interactions in living cells.

Interactions between cytochromes P450 (P450s) and P450 reductase are required for enzymatic activity, and homo- or heterooligomerization of P450s may also be functionally important. Bimolecular fluorescence complementation (BiFC) was used to examine P450 interactions in a natural membrane context within living cells. BiFC detects protein interactions in living cells by reconstitution of a fluorescent protein from two fragments that are fused to the two interacting proteins. Nonspecific protein-protein interactions were detected if proteins were expressed at high levels. At low protein expression levels, homo-oligomerization of P450 2C2, but not P450 2E1, and interactions of these P450s with P450 reductase were detected by BiFC, consistent with interactions detected previously by fluorescence resonance emission transfer. Weak interaction of P450 2C2 with P450 2E1 and homooligomerization of P450 reductase was also detected by BiFC. Homo-oligomerization of the N-terminal P450 2C1 signal anchor sequence and interactions between the signal anchor and full-length P450 2C2 were detected, suggesting that homo-oligomerization of P450 2C2 is mediated by the signal anchor. However, interactions between the signal anchor and either P450 2E1 or P450 reductase were not detected by BiFC. Although high concentrations of the substrate lauric acid increased BiFC for both P450 2E1 and P450 2C2 with P450 reductase, the concentration dependence did not correlate with reported K(m) values. These results demonstrate that BiFC is an effective method to study the complex protein interactions that occur within the microsomal P450 system in living cells.

Animals↗
PubMed2003

Alteration of protein-protein interactions of congenital cataract crystallin mutants.

PURPOSE: A recent study demonstrated the presence of protein-protein interactions among lens crystallins in a mammalian cell two-hybrid system assay and speculated about the significance of these interactions for protein solubility and lens transparency. The current study extends those findings to the following crystallin genes involved in some congenital cataracts: CRYAA (R116C), CRYAB (R120G), and CRYGC (T5P). METHODS: A mammalian two-hybrid system was used to assay the protein-protein interactions. Congenital cataract crystallin genes were cloned and fused into the two-hybrid system vectors (target and prey proteins). Together, with the third vector containing a reporter gene, chloramphenicol acetyltransferase (CAT), they were cotransfected into human HeLa cells. The presence of protein-protein interactions and the strength of these interactions were assayed by CAT ELISA. RESULTS: The pattern of changes in protein-protein interactions of those congenital cataract gene products with the three major crystallins, alphaA- or alphaB-, betaB2-, and gammaC-crystallins, differed. For the T5P gammaC-crystallin, most of the interactions were decreased; for the R116C alphaA-crystallin, the interactions with betaB2- and gammaC-crystallin decreased and those with alphaB-crystallin and heat-shock protein (Hsp)27 increased; and for the R120G alphaB-crystallin, the interactions with alphaA- and alphaB-crystallin decreased, but those with betaB2- and gammaC-crystallin increased slightly. An attempt was made to interpret the results on the basis of conformational change and disruption of dimeric interaction involving beta-strands. CONCLUSIONS: The results clearly indicate that crystallin mutations involved in congenital cataracts altered protein-protein interactions, which may contribute to decreased protein solubility and formation of cataract.

Blotting, Western↗
PubMed2005

Computational verification of protein-protein interactions by orthologous co-expression.

BACKGROUND: High-throughput methods identify an overwhelming number of protein-protein interactions. However, the limited accuracy of these methods results in the false identification of many spurious interactions. Accordingly, the resulting interactions are regarded as hypothetical and computational methods are needed to increase their confidence. Several methods have recently been suggested for this purpose including co-expression as a confidence measure for interacting proteins, but their performance is still quite poor. RESULTS: We introduce a novel computational method for verification of protein-protein interactions based on the co-expression of orthologs of interacting partners. The performance of our method is analysed using known S. cerevisiae interactions, and is shown to overcome limitations of previous methods. We present specific examples of known and putative interactions that are detected by our method and not by previous methods, and suggest that they represent transient interactions that might have been conserved and stabilized in other species. CONCLUSION: Co-expression of orthologous protein-pairs can be used to increase the confidence of hypothetical protein-protein interactions in S. cerevisiae as well as in other species. This approach may be especially useful for species with no available expression profiles and for transient interactions.

Animals↗
PubMed2005

An in vivo analysis of the localisation and interactions of human p66 DNA polymerase delta subunit.

BACKGROUND: DNA polymerase delta is essential for eukaryotic DNA replication and also plays a role in DNA repair. The processivity of this polymerase complex is dependent upon its interaction with the sliding clamp PCNA and the polymerase-PCNA interaction is largely mediated through the p66 polymerase subunit. We have analysed the interactions of the human p66 DNA polymerase delta subunit with PCNA and with components of the DNA polymerase delta complex in vivo. RESULTS: Using the two-hybrid system, we have mapped the interaction domains for binding to the p50 polymerase delta subunit and with PCNA to the N-terminus and the C-terminus of p66, respectively. Co-immunoprecipitation experiments confirm that these interaction domains are functional in vivo. Expression of EGFP-p66 shows that it is a nuclear protein which co-localises with PCNA throughout the cell cycle. p66 is localised to sites of DNA replication during S phase and to repair foci following DNA damage. We have identified a functional nuclear localisation sequence and shown that localisation to replication foci is not dependent upon active nuclear import. Sub-domains of p66 act as dominant negative suppressors of colony formation, suggesting that p66 forms an essential structural link between the p50 subunit and PCNA. Analysis of the C-terminal PCNA binding motif shows that deletion of the QVSITGFF core motif results in a reduced affinity for PCNA, while deletion of a further 20 amino acids completely abolishes the interaction. A reduced affinity for PCNA correlates with reduced targeting to replication foci. We have confirmed the p66-PCNA interaction in vivo using fluorescence resonance energy transfer (FRET) techniques. CONCLUSION: We have defined the regions of p66 required for its interaction with PCNA and the p50 polymerase subunit. We demonstrate a functional link between PCNA interaction and localisation to replication foci and show that there is a direct interaction between p66 and PCNA in living cells during DNA replication. The dominant negative effect upon growth resulting from expression of p66 sub-domains confirms that the p66-PCNA interaction is essential in vivo.

Amino Acid Sequence↗
PubMed2004

A first-draft human protein-interaction map.

BACKGROUND: Protein-interaction maps are powerful tools for suggesting the cellular functions of genes. Although large-scale protein-interaction maps have been generated for several invertebrate species, projects of a similar scale have not yet been described for any mammal. Because many physical interactions are conserved between species, it should be possible to infer information about human protein interactions (and hence protein function) using model organism protein-interaction datasets. RESULTS: Here we describe a network of over 70,000 predicted physical interactions between around 6,200 human proteins generated using the data from lower eukaryotic protein-interaction maps. The physiological relevance of this network is supported by its ability to preferentially connect human proteins that share the same functional annotations, and we show how the network can be used to successfully predict the functions of human proteins. We find that combining interaction datasets from a single organism (but generated using independent assays) and combining interaction datasets from two organisms (but generated using the same assay) are both very effective ways of further improving the accuracy of protein-interaction maps. CONCLUSIONS: The complete network predicts interactions for a third of human genes, including 448 human disease genes and 1,482 genes of unknown function, and so provides a rich framework for biomedical research.

Databases, Protein↗
PubMed2000

Drug interactions in palliative care.

PURPOSE: This review of drug interactions in palliative care examines the relevant literature in this area and summarizes the information on interactions of drugs, nutrients, and natural products that are used in the palliative care setting. Particular emphasis is placed on describing the newer information on the cytochrome P450 (CYP) system and the interactions of opioids, antidepressants, and the antitussive, dextromethorphan. METHODS: We performed a search of the MEDLINE database of the time period from 1966 until April 1998, using medical subject headings such as the names of selective serotonin reuptake inhibitors and other relevant medications in palliative care. Literature reviewed included both human and animal articles as well as non-English literature. Bibliographies of these articles and the personal libraries of several palliative care specialists were reviewed. Software developed by The Medical Letter-The Drug Interaction Program was also used. RESULTS: Drug interactions can be categorized in several ways. Drug-drug interactions are the most well known and can be kinetic, dynamic, or pharmaceutical. Pharmacokinetic interactions can involve CYP 2D6, which acts on drugs such as codeine and is responsible for its conversion to morphine. Poor metabolizers, either genotypic or due to phenocopying, are at risk for undertreatment if not recognized. Pharmacodynamic interactions with dextromethorphan may produce serotonin syndrome. CONCLUSION: Drug interactions are important in palliative care as in other aspects of medicine. These interactions are similar to those seen in other areas of medical care but have significant consequences in pain management. Failure to recognize these interactions can lead to either overdosing or undertreatment.

Drug Interactions↗
PubMed2003

Computer-assisted generation of a protein-interaction database for nuclear receptors.

With the increasing amount of biological data available, automated methods for information retrieval become necessary. We employed computer-assisted text mining to retrieve all protein-protein interactions for nuclear receptors from MEDLINE in a systematic way. A dictionary of protein names and of terms denoting interactions was generated, and trioccurrences of two protein names and one interaction term in one sentence were retrieved. Abstracts containing at least one such trioccurrence were manually checked by biologists to select the relevant interactions out of the automatically extracted data. In total, 4360 abstracts were retrieved containing data on protein interactions for nuclear receptors. The resulting database contains all reported protein interactions involving nuclear receptors from 1966 to September 2001. Remarkably, the annual increase in number of reported interactors for nuclear receptors has been following an exponential growth curve in the years 1991 to 2001. Apparent in the data set is the high complexity of protein interactions for nuclear receptors. The number of interactions correlates with the number of published papers for a given receptor, suggesting that the number of reported interactors is a reflection of the intensity of research dedicated to a given receptor. Indeed, comparison of the retrieved data to a systematic yeast two-hybrid-based interaction analysis suggests that most NRs are similar with respect to the number of interacting proteins. The data set obtained serves as a source for information on NR interactions, as well as a reference data set for the improvement of advanced text-mining methods.

Computers↗
PubMed1998

Statistically designed experiments to screen chemical mixtures for possible interactions.

For the accurate analysis of possible interactive effects of chemicals in a defined mixture, statistical designs are necessary to develop clear and manageable experiments. For instance, factorial designs have been successfully used to detect two-factor interactions. Particularly useful for this purpose are fractionated factorial designs, requiring only a fraction of all possible combinations of a full factorial design. Once the potential interaction has been detected with a fractionated design, a more accurate analysis can be performed for the particular binary mixtures to ensure and characterize these interactions. In this paper this approach is illustrated using an in vitro cytotoxicity assay to detect the presence of mixtures of Fusarium mycotoxins in contaminated food samples. We have investigated interactions between five mycotoxin species (Trichothecenes, Fumonisins, and Zearalenone) using the DNA synthesis inhibition assay in L929 fibroblasts. First, a central composite design was applied to identify possible interactive effects between mycotoxins in the mixtures (27 combinations from 5(5) possible combinations). Then two-factor interactions of particular interest were further analyzed by the use of a full factorial design (5 x 5 design) to characterize the nature of those interactions more precisely. Results show that combined exposure to several classes of mycotoxins generally results in effect addition with a few minor exceptions indicating synergistic interactions. In general, the nature of the interactions characterized in the full factorial design was similar to the nature of those observed in the central composite design. However, the magnitude of interaction was relatively small in the full factorial design.

Algorithms↗
PubMed1999

Significant interactions with new antiretrovirals and psychotropic drugs.

OBJECTIVE: To provide an update on relevant antiretroviral interactions and psychotropic medications for healthcare practitioners managing complex HIV-related pharmacotherapy. DATA SOURCES: Information was retrieved via a MEDLINE search (January 1966-September 1998) using MeSH headings human immunodeficiency virus, drug interactions, psychiatry, psychotropics, psychiatric illness, and names of medications commonly prescribed for the management of HIV infection. Abstracts of international and national conferences (until February 1999), review articles, textbooks, and references of all articles also were searched. STUDY SELECTION AND DATA EXTRACTION: Literature on pharmacokinetic interactions was considered for inclusion. Pertinent information was selected and summarized for discussion. In the absence of specific data, pharmacokinetic and pharmacodynamic properties were considered in order to predict the likelihood of potential drug interactions. DATA SYNTHESIS: All protease inhibitors and nonnucleoside reverse transcriptase inhibitors are substrates of the cytochrome P450 system and possess enzyme-inhibiting and/or -inducing properties. Psychotropic medications also possess similar metabolic characteristics and may interact with antiretrovirals. Modifications in drug selection, dose, or dosing regimen may be needed to ensure adequate antiretroviral concentrations and thus minimize the risk of incomplete viral suppression and/or development of drug resistance. In the absence of specific data, consideration of metabolic characteristics may assist practitioners in predicting the likelihood of possible interactions. RESULTS: The incidence and implications of antiretroviral drug interactions are reviewed. Practical management strategies are also discussed. Comprehensive tables on clinically significant interactions with antiretroviral combinations and with psychiatric medications are provided. CONCLUSIONS: Given the increasing use of multiple-drug therapy, the potential for drug interactions is extremely high. Drug interactions may lead to undesirable outcomes including subtherapeutic drug concentrations and risk of antiretroviral resistance. Practitioners need to consider pharmacokinetic, pharmacologic, therapeutic, and adherence factors when managing interactions with complex antiretroviral therapy.

Antipsychotic Agents↗
PubMedDate not supplied

Phenytoin and enteral feedings: does evidence support an interaction?

OBJECTIVE: To systematically review the reported interaction between oral dosage forms of phenytoin and enteral feeding formulations with respect to the evidence supporting or refuting its existence, proposed mechanism(s) underlying the interaction, and recommended interventions. DATA SOURCES: We conducted a MEDLINE search (1966-April 2000) for English-language articles on phenytoin-enteral feeding interactions; the search terms used were phenytoin, enteral feeding, and/or interaction, and/or in vitro. This search was supplemented by a bibliographic review of all relevant articles. STUDY SELECTION: Prospective, randomized, controlled studies; prospective, nonrandomized, controlled studies; prospective, nonrandomized, uncontrolled studies; retrospective studies; clinical experience reports; case reports; in vitro studies; and letters were evaluated for relevant information. DATA EXTRACTION: Data elements abstracted from these articles were study design, type (patients or healthy volunteers) and number of subjects involved, method of administration of phenytoin and enteral feeding, formulation of phenytoin, type of feeding (and whether it was continuous or interrupted), major findings, and proposed mechanisms of the interaction. DATA SYNTHESIS: Although four prospective, randomized, controlled trials in healthy human volunteers refute the existence of the interaction, there are numerous reports and studies showing dramatic decreases of serum phenytoin concentrations in patients when it is coadministered with enteral feeding formulations. Therefore, evidence supports the existence of this interaction in patients and in vitro studies, but not in healthy volunteers. Unfortunately, the exact mechanisms underlying this interaction remain unknown. Many methods have been devised to prevent and treat the interaction once it has occurred; however, a single, generally accepted, and practical intervention strategy is still lacking. CONCLUSIONS: The exact role of enteral feeding in this interaction is unclear due to the lack of prospective, randomized, controlled trials performed in patients. However, decreased serum phenytoin concentrations associated with enteral feeding may increase the risk of seizures. Clinicians should be aware of this potential drug-nutrient interaction and design a patient-specific care plan that includes consideration of the enteral feeding formulation and method of administration, as well as the phenytoin dosage form, schedule of administration, and monitoring.

Administration, Oral↗
PubMed2006

Stratus not altocumulus: a new view of the yeast protein interaction network.

Systems biology approaches can reveal intermediary levels of organization between genotype and phenotype that often underlie biological phenomena such as polygenic effects and protein dispensability. An important conceptualization is the module, which is loosely defined as a cohort of proteins that perform a dedicated cellular task. Based on a computational analysis of limited interaction datasets in the budding yeast Saccharomyces cerevisiae, it has been suggested that the global protein interaction network is segregated such that highly connected proteins, called hubs, tend not to link to each other. Moreover, it has been suggested that hubs fall into two distinct classes: "party" hubs are co-expressed and co-localized with their partners, whereas "date" hubs interact with incoherently expressed and diversely localized partners, and thereby cohere disparate parts of the global network. This structure may be compared with altocumulus clouds, i.e., cotton ball-like structures sparsely connected by thin wisps. However, this organization might reflect a small and/or biased sample set of interactions. In a multi-validated high-confidence (HC) interaction network, assembled from all extant S. cerevisiae interaction data, including recently available proteome-wide interaction data and a large set of reliable literature-derived interactions, we find that hub-hub interactions are not suppressed. In fact, the number of interactions a hub has with other hubs is a good predictor of whether a hub protein is essential or not. We find that date hubs are neither required for network tolerance to node deletion, nor do date hubs have distinct biological attributes compared to other hubs. Date and party hubs do not, for example, evolve at different rates. Our analysis suggests that the organization of global protein interaction network is highly interconnected and hence interdependent, more like the continuous dense aggregations of stratus clouds than the segregated configuration of altocumulus clouds. If the network is configured in a stratus format, cross-talk between proteins is potentially a major source of noise. In turn, control of the activity of the most highly connected proteins may be vital. Indeed, we find that a fluctuation in steady-state levels of the most connected proteins is minimized.

Computational Biology↗
PubMed1993

Drug interactions of clinical significance with opioid analgesics.

Opioid analgesics and other drugs interact through multiple mechanisms, resulting in pharmacological effects that depend upon the pharmacodynamic action studied, the interacting agents and the route of administration. Many interactions result from induction or inhibition of the hepatic cytochrome P450 mono-oxygenase system. The elimination of opioids is largely dependent on hepatic metabolism, and drug interactions involving this mechanism can therefore be clinically significant. Antibiotics are often used concomitantly with opioids in patients undergoing medical or surgical procedures; the best documented metabolic interactions are with erythromycin and rifampicin (rifampin). Erythromycin increases and rifampicin decreases the effects of opioids. Cimetidine may increase the effects of opioids by increasing their duration of action; there have been no documented cases of interactions with ranitidine. Carbamazepine, phenytoin and the barbiturates can enhance the metabolism of opioids that rely on hepatic metabolism. Other pharmacokinetic interactions include those with benzodiazepines, tricyclic antidepressants, phenothiazines and metoclopramide. Interactions involving pharmacodynamic mechanisms are more common than pharmacokinetic ones. Such interactions are manifested clinically as as a summation (additive or synergistic) of similar or opposing pharmacological effects on the same body system. Idiosyncratic interactions also occur, the mechanisms of which have not been proven to be solely modulated by either pharmacokinetic or pharmacodynamic means. The knowledge of particular opioid-drug interactions, and the causative pharmacokinetic, pharmacodynamic, and idiosyncratic mechanisms, allows for the safer administration of opioid analgesics.

Analgesics↗
PubMed1976

Drug interactions and clinical pharmacokinetics.

Some drugs influence the gastro-intestinal absorption, distribution , metabolism or renal excretion of other drugs, i.e., processes involved in pharmacokinetic interactions. The clinical consequences of pharmacokinetic drug-drug interactions will be either an increase or a decrease in known therapeutic or toxic effects of the interacting drug. In order to evaluate the importance of drug interaction affecting gastro-intestinal absorption, it is necessary to distinguish between interactions which alter the rate of absorption of another drug and those which alter the amount of drug absorbed. Many drugs displace other drugs from their protein binding sites in vitro. This may cause an increase in the pharmacological effect of the displaced drug. However, much discrepancy exists between in vitro findings. In some cases, the enhanced effect only seems to be a temporary phenomenon. The degree of protein binding and the size of apparent volume of distribution (Vd) must also be taken into consideration. Perhaps the importance of interaction involving protein binding has been overemphasized. Barbiturates, glutethimide, rifampicin and phenytoin increase the rate of drug metabolism in man. The most important interactions reported are between oral anti-coagulants and barbiturates. After withdrawal of these hepatic microsomal enzyme inducing drugs, it takes 2 to 3 weeks before the rate of drug metabolism reaches the pretreatment level. In this period, risk of haemorrhage exists. Induction seems to be dose-dependent, but not all persons are inducible. Many drugs compete for the drug metabolising enzyme system in the liver and consequently some drugs inhibit the biotransformation of other drugs. The time course of these interactions depends on the pharmacokinetic properties of the drug involved, and these interactions also seem to be dose-dependent. The most important of such interactions, clinically involved the oral sulphonylurea hypoglycaemic drugs and the antiepilepic drug phenytoin. Drugs are eliminated by urinary excretion through three mechanisms: glomerular filtration, tubular reabsorption, and active tubular secretion. The most important interactions seem to be those involving competition for tubular secretion.

Acid-Base Equilibrium↗
PubMed1993

Drug interactions in primary health care. A retrospective database study and its implications for the design of a computerized decision support system.

OBJECTIVE: To investigate the occurrence of potential drug interactions in primary health care from the perspective of the prescribing general practitioner. DESIGN: Retrospective database study of computer-based patient records with a query language. All drug prescriptions during a four year period were compared with concurrent or overlapping prescriptions for the same patient and these drug pairs were compared with a database of drug interactions from the Swedish drug catalogue. SETTING: One health centre in Sweden with six general practitioners and two doctors on vocational training. PARTICIPANTS: All patients who had visited a doctor at the health centre between 1 November 1986 and 31 October 1990. MAIN OUTCOME MEASURES: The rate of potential interactions in relation to all drug prescriptions and the incidence rate of potential interactions for patients at risk (those receiving two or more drugs). RESULTS: Approximately 55,000 drug prescriptions were analysed for potential drug interactions. A total of 1,074 cases of potential drug interactions were found, which corresponds to a rate of 1.9% of all drug prescriptions. The incidence rate of potential interactions was 12% for all patients at risk (those receiving two or more drugs) and 22% for elderly (> = 65 years of age) patients at risk. Major interactions were investigated concerning the extent to which the prescribing doctors were aware of the potential interactions. CONCLUSION: Potential drug interactions occur at a high rate in general practice, in particular for elderly patients. Properly designed computer-based decision-support might increase the prescribing doctor's awareness of clinically significant interactions and improve the quality of drug treatment.

Adult↗
PubMed1994

NSAID-related adverse drug interactions with clinical relevance. An update.

The prevalence and incidence of adverse drug interactions involving NSAIDs remain unknown. To identify those proposed drug interactions of greatest clinical significance, it is appropriate to focus on interactions between commonly used and/or commonly coprescribed drugs, interactions for which there are numerous well documented case reports in reputable journals, interactions validated by well designed in vivo human studies and interactions affecting high-risk drugs and/or high-risk patients. While most interactions between NSAIDs and other drugs are pharmacokinetic, NSAID-related pharmacodynamic interactions may be considerably more important in the clinical context. However, prescriber ignorance is likely to be a major determinant of many adverse drug interactions. Adverse drug interactions involving NSAIDs may be restricted by rational prescribing and by careful monitoring, particularly high-risk patients, drugs and therapy periods. Prescribing NSAIDs is relatively contra-indicative for patients on oral anticoagulants due to hemorrhage and for patients taking high dose methotrexate due to bone marrow toxicity, renal failure and hepatic dysfunction. Combination NSAID therapy cannot be justified since toxicity may be increased without any improvement in efficacy. Where lithium or antihypertensives are coprescribed with NSAIDs, aspirin or sulindac are preferred and close monitoring is mandatory for lithium toxicity and hypertension respectively. Phenytoin or oral hypoglycemic agents may be administered with NSAIDs other than pyrazoles and salicylates, provided, the patients are monitored carefully at the initiation and cessation of NSAID treatment. Digoxin, aminoglycosides and probenecid may be coprescribed with NSAIDs but close monitoring is required, particularly for high-risk patients such as the elderly. Indomethacin and triamterine should be avoided due to the risk of renal failure, high dose aspirin should be replaced by naproxen in patients on sodium valproate and care is required when corticosteroids are administered to patients taking salicylates long term in high dosage. Interactions between NSAIDs and antacids or cholestyramine are generally avoidable by administering these drugs at different times.

Anti-Inflammatory Agents, Non-Steroidal↗
PubMed1997

Interactions between promazine and antidepressants at the level of cellular distribution.

The pharmacokinetic interactions in clinical combinations of a phenothiazine neuroleptic and antidepressants at the level of cellular distribution were investigated. Uptake experiments were performed on slices of various rat tissues as a system with intact lysosomes. Promazine and antidepressants (imipramine, amitriptyline, sertraline, fluoxetine) were incubated separately or jointly with tissue slices for 1 hr. Initial concentration of each drug was 5 microM. The interaction studies were carried out in the absence and presence of ammonium chloride (20 mM), a lysosomotropic compound which increases the internal pH value of lysosomes. All the tissues known for their abundance of lysosomes (the lungs, liver, kidneys) were the site of an interaction between promazine and antidepressants. The neuroleptic and antidepressants mutually inhibited their tissue uptake. The potency of interference of each antidepressant with the lysosomal uptake of promazine was similar. The interactions did not occur in the presence of ammonium chloride, which indicates involvement of the lysosomal trapping. Carbamazepine, a lipophilic but non-lysosomotropic drug, did not interfere with the promazine uptake, and the adipose tissue containing very few lysosomes was never the site of interaction in our experiment. Distribution interactions were also observed in the brain and in some cases in muscles (the tissues less abundant of lysosomes), the effect of the inhibitory drug being usually more potent than that of ammonium chloride. Most of the interactions occurring in these two tissues were also observed in the presence of ammonium chloride. Most of the interactions occurring in these two tissues were also observed in the presence of ammonium chloride, which suggests involvement, at least partially, of a non-lysosomal trapping mechanism. The consequences of the observed distributive interactions at the level of lysosomal trapping in vitro are diminished intralysosomal concentration of the basic lipophilic psychotropic and its increase in cell membranes and fluids. In vivo, a shift from the organs or tissues rich in lysosomes to those less abundant in these organella, and an increase in the free drug concentration in body fluids may be expected. In conclusion, the obtained results show that, regardless of the previously known metabolic interactions between psychotropics, interactions at the levels of cellular and body distribution are also feasible.

1-Naphthylamine↗
PubMed1997

[Potential and real drug interactions in critical care patients].

OBJECTIVES: To detect potential drug interactions occurring during treatment of critically ill patients and to evaluate the real clinical and analytical repercussions of such interactions. PATIENTS AND METHODS: Seventy consecutive patients in a six-bed medical-surgical intensive care unit (ICU) were studied prospectively over a period of five months. The pharmacological department of the hospital provided the drugs through a computerized unit dosing system, using a program that gave warnings of possible drug interactions as each patient's treatment was entered. Interactions were cataloged according to clinical importance following the criteria of Hansten. The repercussions were evaluated by clinical and analytical monitoring. RESULTS: On hundred two potential interactions were detected in 44.3% of patients (1.5 interactions per patient). In 6 patients (19.3%) analytical alterations were observed but only 2 (6.4%) of them presented clinical manifestations. Most of the interactions were cataloged as being of moderate clinical importance. Digoxin was the most frequently implicated drug. The number of drugs administered per patient was 14.7 and patients receiving the most drugs were the most likely to experience and interaction. We found a significant correlation (p < 0.05) between the number of interactions and age, APACHE III score, length of ICU stay and number of drugs administered. CONCLUSIONS: The frequently of drug interactions in critically ill patients can be high, given the large number of drugs they receive. Although the real clinical repercussions of interactions are few, physicians should watch for them and the act appropriately.

Critical Care↗