Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rate...
Se pu = Chinese journal of chromatography
Aug 8, 2020
A method based on liquid chromatography coupled with high-resolution quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) was developed for the simultaneous screening and determination of fentanyl and its 26 analogs in liquid and solid powder dru...
MOTIVATION: Drug-drug interactions (DDIs) are one of the major concerns in pharmaceutical research. Many machine learning based methods have been proposed for the DDI prediction, but most of them predict whether two drugs interact or not. The studies...
Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ing...
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2020
OBJECTIVE: We developed medExtractR, a natural language processing system to extract medication information from clinical notes. Using a targeted approach, medExtractR focuses on individual drugs to facilitate creation of medication-specific research...
INTRODUCTION: The research and development of drugs, related to the central nervous system (CNS) diseases is a long and arduous process with high cost, long cycle and low success rate. Identification of key features based on available CNS drugs is of...
Protein-related interaction prediction is critical to understanding life processes, biological functions, and mechanisms of drug action. Experimental methods used to determine proteinrelated interactions have always been costly and inefficient. In re...
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2020
OBJECTIVE: This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 National NLP Clinical Challenges (n2c2) shared task.