AIMC Topic: Factor Xa

Clear Filters Showing 1 to 6 of 6 articles

Application of Deep Neural Network Models in Drug Discovery Programs.

ChemMedChem Oct 18, 2021
In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a ...
Deep Learning Dose-Response Relationship, Drug Structure-Activity Relationship Humans Drug Discovery Factor Xa Inhibitors Cytochrome P-450 CYP3A Cytochrome P-450 CYP3A Inhibitors Molecular Structure Factor Xa
View on PubMed DOI

Factor Xa inhibitors in clinical practice: Comparison of pharmacokinetic profiles.

Drug metabolism and pharmacokinetics Oct 25, 2019
BACKGROUND: The anticoagulant actions of oral direct factor Xa (FXa) inhibitors can be inferred from their observed plasma concentrations; however, the steady-state pharmacokinetics (PK) of different FXa inhibitors have not been compared in clinicall...
Male Venous Thromboembolism Female Thiazoles Chromatography, Liquid Aged Humans Pyridines Pyrazoles Blood Coagulation Tests Tandem Mass Spectrometry Anticoagulants Factor Xa Prospective Studies Rivaroxaban Pyridones Atrial Fibrillation Factor Xa Inhibitors
View on PubMed DOI

Practical High-Quality Electrostatic Potential Surfaces for Drug Discovery Using a Graph-Convolutional Deep Neural Network.

Journal of medicinal chemistry Sep 25, 2019
Inspecting protein and ligand electrostatic potential (ESP) surfaces in order to optimize electrostatic complementarity is a key activity in drug design. These ESP surfaces need to reflect the true electrostatic nature of the molecules, which typical...
Drug Discovery Datasets as Topic Factor Xa Organic Chemicals Static Electricity Deep Learning Quantum Theory X-Linked Inhibitor of Apoptosis Protein Hydrogen Bonding Protein Binding Ligands
View on PubMed DOI

Edoxaban vs warfarin in patients with nonvalvular atrial fibrillation in the US Food and Drug Administration approval population: An analysis from the Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48 (ENGAGE AF-TIMI 48) trial.

American heart journal Dec 1, 2015
BACKGROUND: Edoxaban is a specific anti-Xa inhibitor that, in comparison to warfarin, has been found to be noninferior for the prevention of stroke or systemic embolism (SSE) and to reduce bleeding significantly in patients with nonvalvular atrial fi...
Pyridines Thrombolytic Therapy Blood Coagulation Double-Blind Method Anticoagulants Male Humans Thiazoles Female Myocardial Infarction Drug Approval United States Factor Xa Inhibitors Factor Xa Warfarin Aged Dose-Response Relationship, Drug Atrial Fibrillation Stroke United States Food and Drug Administration
View on PubMed DOI

Non-weight-based enoxaparin dosing subtherapeutic in trauma patients.

The Journal of surgical research Oct 21, 2015
BACKGROUND: We report our experience dosing and monitoring enoxaparin with anti-factor Xa activity (anti-FXaA) levels for venous thromboembolism prophylaxis in trauma patients (TP).
Anticoagulants Drug Monitoring Enoxaparin Factor Xa Venous Thromboembolism Adult Male Middle Aged Retrospective Studies Female Humans
View on PubMed DOI

Three-Dimensional Classification Structure-Activity Relationship Analysis Using Convolutional Neural Network.

Chemical & pharmaceutical bulletin Jan 1, 2019
Quantitative structure-activity relationship (QSAR) techniques, especially those that possess three-dimensional attributes, such as the comparative molecular field analysis (CoMFA), are frequently used in modern-day drug design and other related rese...
Algorithms Deep Learning Protein Binding Humans Neural Networks, Computer Factor Xa Quantitative Structure-Activity Relationship Models, Molecular Ligands
View on PubMed DOI
Popular Topics
Recent Journals