Results 11 to 20 of about 5,522,353 (395)
Pharmacointeraction network models predict unknown drug-drug interactions. [PDF]
PLoS ONE, 2013 Drug-drug interactions (DDIs) can lead to serious and potentially lethal adverse events. In recent years, several drugs have been withdrawn from the market due to interaction-related adverse events (AEs).
Aurel Cami +3 more
doaj +6 more sources
Clinical pharmacology and therapy, 2022 The coronavirus disease 2019 (COVID‐19) antiviral nirmatrelvir/ritonavir (Paxlovid) has been granted authorization or approval in several countries for the treatment of patients with mild to moderate COVID‐19 at high risk of progression to severe disease
C. Marzolini +11 more
semanticscholar +1 more source
Pharmacokinetic Drug–Drug Interactions and Herb–Drug Interactions
Pharmaceutics, 2021 Due to the growing use of herbal supplementation—ease of taking herbal supplements with therapeutics drugs (i [...]
Min-Koo Choi, Im-Sook Song
doaj +1 more source
A Review of Approaches for Predicting Drug–Drug Interactions Based on Machine Learning
Frontiers in Pharmacology, 2022 Drug–drug interactions play a vital role in drug research. However, they may also cause adverse reactions in patients, with serious consequences. Manual detection of drug–drug interactions is time-consuming and expensive, so it is urgent to use computer ...
Ke Han +9 more
semanticscholar +1 more source
Drug–drug interactions with warfarin: A systematic review and meta‐analysis
British Journal of Clinical Pharmacology, 2021 The objective of this paper is to systematically review the literature on drug–drug interactions with warfarin, with a focus on patient‐important clinical outcomes.
Mei Wang +12 more
semanticscholar +1 more source
Predicting drug-target interactions using drug-drug interactions. [PDF]
PLoS ONE, 2013 Computational methods for predicting drug-target interactions have become important in drug research because they can help to reduce the time, cost, and failure rates for developing new drugs.
Shinhyuk Kim, Daeyong Jin, Hyunju Lee
doaj +1 more source
Crystal structure correlations with the intrinsic thermodynamics of human carbonic anhydrase inhibitor binding [PDF]
PeerJ, 2018 The structure-thermodynamics correlation analysis was performed for a series of fluorine- and chlorine-substituted benzenesulfonamide inhibitors binding to several human carbonic anhydrase (CA) isoforms.
Alexey Smirnov +4 more
doaj +2 more sources
A machine learning framework for predicting drug–drug interactions
Scientific Reports, 2021 Understanding drug–drug interactions is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods, commonly integrating heterogeneous data to increase model performance, often suffer from a high ...
Suyu Mei, Kun Zhang
semanticscholar +1 more source
Pharmaceutics, 2020 In an ageing society, polypharmacy has become a major public health and economic issue. Overuse of medications, especially in patients with chronic diseases, carries major health risks. One common consequence of polypharmacy is the increased emergence of
M. Deodhar +6 more
semanticscholar +1 more source
Pharmaceutics, 2021 Background: Drug interactions represent a major issue in clinical settings, especially for critically ill patients such as those with cardiovascular disease (CVD) who require cardiothoracic surgery (CTS) and receive a high number of different medications.
Marios Spanakis +4 more
doaj +1 more source