UPLC-MS/MS Method for Givinostat in Rat Plasma: Development, Validation, in vivo Pharmacokinetics Study and in vitro Metabolic Stability Research

Givinostat was rapidly absorbed and cleared slowly in vivo, and it was confirmed by in vitro experiments. This study provides a potential reference for givinostat in clinical studies.

Authors

Institutions

Publication Details

Journal
Drug Design Development and Therapy
Published
2025-01-01
DOI
https://doi.org/10.2147/dddt.s497308
Primary Topic
Biochemical and Molecular Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

UPLC-MS/MS Method for Givinostat in Rat Plasma: Development, Validation, in vivo Pharmacokinetics Study and in vitro Metabolic Stability Research

Ruanjuan Zhan, Xiaocheng Chen, Yanan Liu, Yuxin Shen et al.
Drug Design Development and Therapy
Biochemical and Molecular Research
article

UPLC-MS/MS Method for Givinostat in Rat Plasma: Development, Validation, in vivo Pharmacokinetics Study and in vitro Metabolic Stability Research

Ruanjuan Zhan, Xiaocheng Chen, Yanan Liu, Yuxin Shen, Jun Wu, Xinhao Xu, Guanyang Lin
article en

Abstract

Givinostat was rapidly absorbed and cleared slowly in vivo, and it was confirmed by in vitro experiments. This study provides a potential reference for givinostat in clinical studies.

Drug Design Development and TherapyVol. Volume 19
Wenzhou Medical University (CN), First Affiliated Hospital of Wenzhou Medical University (CN)
Clean water and sanitation
Openalex Percentile: Top 100%
Biochemical and Molecular Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.