The Influence of Pharmacogenetics on the Clinical Relevance of Pharmacokinetic Drug–Drug Interactions: Drug–Gene, Drug–Gene–Gene and Drug–Drug–Gene Interactions [PDF]
Drug interactions are a well-known cause of adverse drug events, and drug interaction databases can help the clinician to recognize and avoid such interactions and their adverse events. However, not every interaction leads to an adverse drug event.
Martina Hahn, Sibylle C. Roll
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The Prevalence of Potential Drug-Drug-Gene Interactions: A Descriptive Study Using Swiss Claims Data [PDF]
Nina L Wittwer,1,2 Christoph R Meier,1– 3 Carola A Huber,4 Julie D Moser,1 Henriette E Meyer zu Schwabedissen,5 Samuel S Allemann,6,* Cornelia Schneider1,2,* 1Basel Pharmacoepidemiology Unit, Division of Clinical Pharmacy and Epidemiology,
Wittwer NL +6 more
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Drug Repurposing Using Modularity Clustering in Drug-Drug Similarity Networks Based on Drug–Gene Interactions [PDF]
Drug repurposing is a valuable alternative to traditional drug design based on the assumption that medicines have multiple functions. Computer-based techniques use ever-growing drug databases to uncover new drug repurposing hints, which require further ...
Vlad Groza +3 more
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Exploratory Evaluation of Solanidine as an Endogenous Marker for CYP2D6‐Mediated Drug–Drug–Gene Interactions of Venlafaxine in Koreans [PDF]
CYP2D6‐mediated drug–drug–gene interactions (DDGIs) are known to influence the pharmacokinetics of venlafaxine and its metabolism to O‐desmethylvenlafaxine.
Sungyeun Bae +8 more
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Pharmacogenomic Drug-Gene Interactions in Geriatric Emergency Department Patients Who Sustained Falls: A Pilot Study [PDF]
Introduction: Pharmacogenomic-assisted prescribing of medications uses individual genetic information to identify drug-gene interactions. We aimed to assess potential pharmacogenomic drug-gene interactions in geriatric emergency department (ED) patients ...
Richard D. Shih +13 more
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A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug–Drug–Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine [PDF]
Physiologically-based pharmacokinetic (PBPK) modeling is a well-recognized method for quantitatively predicting the effect of intrinsic/extrinsic factors on drug exposure.
Tobias Kanacher +7 more
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An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph [PDF]
Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training ...
Jian He +6 more
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Drug-gene interactions in older patients with coronary artery disease [PDF]
Background Older patients with coronary artery disease (CAD) are particularly vulnerable to the efficacy and adverse drug reactions, and may therefore particularly benefit from personalized medication.
Shizhao Zhang +4 more
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Estimating the incidence of actionable drug-gene interactions in Japanese patients with major depressive disorder [PDF]
BackgroundAlthough several guidelines provide dosing recommendations for antidepressants based on patients’ genetic information, pharmacogenetic testing for antidepressant use is rarely routinely performed in Japan.
Masakazu Hatano +5 more
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Primary Care Prescription Drug Use and Related Actionable Drug‐Gene Interactions in the Danish Population [PDF]
Pharmacogenetics (PGx) aims to improve drug therapy using the individual patients’ genetic make‐up. Little is known about the potential impact of PGx on the population level, possibly hindering implementation of PGx in clinical care.
Carin Adriana Theodora Catharina Lunenburg +3 more
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