Effects of ions and detergents in drug partition chromatography on liposomes.

J Chromatogr A

Department of Biochemistry, Biomedical Center, Uppsala University, Box 576, SE-75123 Uppsala, Sweden.

Published: March 2004

We have determined drug partitioning into phospholipid bilayers by immobilized-liposome chromatography (ILC). Electrostatic effects on the drug partitioning were observed on neutral bilayers at low ionic strength. The size of the counterions affected the partitioning. When liposomes were supplemented with ionic detergents the partitioning of charged drugs was strongly affected, allowing complete separation of drugs of different charges which showed similar retention on neutral bilayers. Partial separation was obtained on bilayers containing fatty acid. Detergent ions or fatty acid inserted into phospholipid bilayers affected the partitioning of drugs much more than did free ions or phospholipid head group charges.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.chroma.2003.11.060DOI Listing

Publication Analysis

Top Keywords

drug partitioning
8
phospholipid bilayers
8
neutral bilayers
8
fatty acid
8
partitioning
5
bilayers
5
effects ions
4
ions detergents
4
detergents drug
4
drug partition
4

Similar Publications

This study was aimed to evaluate the cost-effectiveness of pembrolizumab with chemotherapy (pembrolizumab combination therapy) and compare it with standard-of-care platinum-based chemotherapy (chemotherapy alone) as a first-line treatment for metastatic nonsquamous NSCLC from the perspective of Taiwan's third-party-payer public health-care system. We used a partitioned survival model with an estimated time horizon of 10 years. The partitioned survival model uses Kaplan-Meier estimates of progression-free and overall survival from the KEYNOTE-189 clinical trial.

View Article and Find Full Text PDF

Cost Effectiveness of Exclusionary EGFR Testing for Taiwanese Patients Newly Diagnosed with Advanced Lung Adenocarcinoma.

Pharmacoeconomics

January 2025

Division of Pulmonology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, 138 Shengli Road, Tainan, 704, Taiwan.

Background And Objective: Approximately half of lung adenocarcinomas in East Asia harbor epidermal growth factor receptor (EGFR) mutations. EGFR testing followed by tissue-based next-generation sequencing (NGS), upfront tissue-based NGS, and complementary NGS approaches have emerged on the front line to guide personalized therapy. We study the cost effectiveness of exclusionary EGFR testing for Taiwanese patients newly diagnosed with advanced lung adenocarcinoma.

View Article and Find Full Text PDF

We compared the cost-effectiveness of gemcitabine plus nab-paclitaxel (GnP) and modified FOLFIRINOX (mFFX)-standard first-line treatments for metastatic pancreatic cancer in Japan. This retrospective cohort study included patients with metastatic pancreatic cancer treated at the National Cancer Center Hospital East in Japan between December 2013 and February 2017. A partitioned survival model, featuring five mutually exclusive health states, was developed.

View Article and Find Full Text PDF

Accurate prediction of drug-target binding affinity remains a fundamental challenge in contemporary drug discovery. Despite significant advances in computational methods for protein-ligand binding affinity prediction, current approaches still face substantial limitations in prediction accuracy. Moreover, the prevalent methodologies often overlook critical three-dimensional (3D) structural information, thereby constraining their practical utility in computer-aided drug design (CADD).

View Article and Find Full Text PDF

A cross-species assessment of in silico prediction methods of steady-state volume of distribution using Simcyp simulators.

J Pharm Sci

December 2024

Certara UK Ltd., Certara Predictive Technologies Division, 1 Concourse Way, Level 2-Acero, Sheffield S1 2BJ, United Kingdom. Electronic address:

Predicting steady-state volume of distribution (V) is a key component of pharmacokinetic predictions and often guided using preclinical data. However, when bottom-up prediction from physiologically-based pharmacokinetic (PBPK) models and observed V misalign in preclinical species, or predicted V from different models varies significantly, no consensus exists for selecting models or preclinical species to improve the prediction. Through systematic analysis of V prediction across rat, dog, monkey, and human, using common methods, a practical strategy for predicting human V, with or without integration of preclinical PK information is warranted.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!