Drug Interactions of Clinical Importance

  title={Drug Interactions of Clinical Importance},
  author={D. Quinn and R. Day},
  journal={Drug Safety},
An Exact Cutting Plane Method for $k$-submodular Function Maximization
A natural and important generalization of submodularity—k-submodularity—applies to set functions with k arguments and appears in a broad range of applications, such as infrastructure design, machineExpand
An Exact Method for Bisubmodular Function Maximization
It is shown that maximizing a bisubmodular function is equivalent to solving a mixed-integer linear program with exponentially many bisubModular inequalities, and the first exact algorithm to solve general bisub modular maximization problems is designed. Expand
Detecting high-quality signals of adverse drug-drug interactions from spontaneous reporting data
A new method is proposed which employs the framework of Bayesian network to infer the direct associations between the target ADE and medicines, and uses domain knowledge to facilitate the learning ofBayesian network structures to search for high-quality ADDI signals. Expand
The Concurrent Initiation of Medications Is Associated with Discontinuation of Buprenorphine Treatment for Opioid Use Disorder
Concurrent initiation of medications is associated with increased discontinuation risk of buprenorphine for patients without previous exposure of pain medications. Expand
Causality Discovery with Domain Knowledge for Drug-Drug Interactions Discovery
Bayesian Network Probabilistic Graphs have recently been applied to the problem of discovery drug-drug interactions, i.e., the identification of drugs that, when consumed together, produce anExpand
DDIGIP: predicting drug-drug interactions based on Gaussian interaction profile kernels
DDRGIP is an effective method to predict DDIs while being beneficial to drug development and disease treatment and compares the prediction performance of DDIGIP with other competing methods via the 5-fold cross validation, 10-cross validation and de novo drug validation. Expand
Novel deep learning model for more accurate prediction of drug-drug interaction effects
This model uses autoencoders and a deep feed-forward network that are trained using the structural similarity profiles (SSP), Gene Ontology (GO) term similarity profile (GSP), and target gene similarity profiles of known drug pairs to predict the pharmacological effects of DDIs. Expand
Review of Statistical Methodologies for Detecting Drug–Drug Interactions Using Spontaneous Reporting Systems
This article reviews the studies on the latest statistical methodologies from classical methodologies for signal detection of DDIs using spontaneous reporting system, and describes how to calculate for each detection method and the major findings from the published literatures about DDIs. Expand
A New Search Method Using Association Rule Mining for Drug-Drug Interaction Based on Spontaneous Report System
The proposed association rule mining (AR) method has the same detection power as the conventional methods, with the significant advantage that its calculation process is simple. Expand
Deep learning improves prediction of drug–drug and drug–food interactions
  • J. Ryu, H. Kim, S. Lee
  • Computer Science, Medicine
  • Proceedings of the National Academy of Sciences
  • 2018
A computational framework DeepDDI is presented that accurately predicts DDI types for given drug pairs and drug–food constituent pairs using only name and structural information as inputs and can provide important information on drug prescription and even dietary suggestions while taking certain drugs and also guidelines during drug development. Expand


Interactions with selective MAOIs
Pseudo‐phaeochromocytoma after multiple drug interactions involving the selective monoamine oxidase inhibitor selegiline
This syndrome probably arose as a consequence of an interaction between the monoamine oxidase inhibitor selegiline, the sympathomimetic agent ephedrine, and a tricyclic antidepressant. Expand
Do Nonsteroidal Anti-inflammatory Drugs Affect Blood Pressure? A Meta-Analysis
A stable estimate of the overall effect of various NSAIDs on blood pressure is produced to evaluate possible mechanisms by which NSAID therapy may alter blood pressure and to determine potential predisposing factors for this interaction. Expand
Lithium in the treatment of mood disorders.
This review summarizes the history, pharmacology, efficacy, clinical use, and toxicity of lithium, with a brief discussion of other thymoleptic drugs proposed as alternatives or adjuncts to lithium. Expand
Risk-Benefit Assessment of Omeprazole in the Treatment of Gastrointestinal Disorders
A slight increase of the agyrophil (endocrine) cell volume density and an extension of micronodular hyperplasia in the oxyntic mucosa after several years of omeprazole treatment seem to be related to the severity of the corpus gastritis and not to drug-induced hypergastrinaemia, because similar changes have been observed in equal frequency in patients not receiving antisecretory drugs. Expand
Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance.
  • J. Houston
  • Biology, Medicine
  • Biochemical pharmacology
  • 1994
Epidemiology of Drug-Drug Interactions as a Cause of Hospital Admissions
A review of the adverse drug reaction literature found that nine ADR studies were found that either included a D-DI category as a cause for hospital admissions, or provided sufficient information so that a causal relationship could be inferred, and it is not possible to provide a meaningful summary of risk factors specific for D- DI admissions. Expand
Serotonin syndrome produced by a combination of fluoxetine and lithium.