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ATP Binding Cassette Transporter, Subfamily B, Member 1

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Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.

British journal of clinical pharmacology
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...

Effect of Oregon grape root extracts on P-glycoprotein mediated transport in cell lines.

Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques
This study aims to investigate the potential of Oregon grape root extracts to modulate the activity of P-glycoprotein. We performed H-CsA or H-digoxin transport experiments in the absence or presence of two sources of Oregon grape root extracts (E1...

Physiological based pharmacokinetic modeling to estimate in vivo Ki of ketoconazole on renal P-gp using human drug-drug interaction study result of fesoterodine and ketoconazole.

Drug metabolism and pharmacokinetics
This study was conducted to estimate in vivo inhibition constant (Ki) of ketoconazole on renal P-glycoprotein (P-gp) using human drug-drug interaction (DDI) study result of fesoterodine and ketoconazole. Fesoterodine is a prodrug which is extensively...

Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients.

CPT: pharmacometrics & systems pharmacology
Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic of current research. Not only can excipients alter the disposition of coformulated drugs, but it is l...

Machine Learning Uncovers Food- and Excipient-Drug Interactions.

Cell reports
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...

Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors.

Journal of computer-aided molecular design
Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from ...

A Machine Learning-Based Prediction Platform for P-Glycoprotein Modulators and Its Validation by Molecular Docking.

Cells
P-glycoprotein (P-gp) is an important determinant of multidrug resistance (MDR) because its overexpression is associated with increased efflux of various established chemotherapy drugs in many clinically resistant and refractory tumors. This leads to...

Multiclass Classifier for P-Glycoprotein Substrates, Inhibitors, and Non-Active Compounds.

Molecules (Basel, Switzerland)
P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemically diverse compounds out of the cell. It is highly associated with the ADMET (absorption, distribution, metabolism, excretion and toxicity) properties...

Theoretical Prediction of the Complex P-Glycoprotein Substrate Efflux Based on the Novel Hierarchical Support Vector Regression Scheme.

Molecules (Basel, Switzerland)
P-glycoprotein (P-gp), a membrane-bound transporter, can eliminate xenobiotics by transporting them out of the cells or blood⁻brain barrier (BBB) at the expense of ATP hydrolysis. Thus, P-gp mediated efflux plays a pivotal role in altering the absorp...