Development of a Robust and Highly Sensitive UHPLC-MS Method for the Quality Control of Desidustat Formulations

AbstractPurpose: The study aimed at developing and validating an effective UHPLC-MS method thatmeasures Desidustat. The designed method was very sensitive and reproducible, and theexact analysis of this HIF-PH inhibitor could be done in both raw chemical form andcommercial tablet formulations.

Authors

Institutions

Publication Details

Journal
Degrés
Published
2026-08-28
DOI
https://doi.org/10.5281/zenodo.22137765
Primary Topic
Analytical Methods in Pharmaceuticals
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Development of a Robust and Highly Sensitive UHPLC-MS Method for the Quality Control of Desidustat Formulations

Buggana Siva Jyothi, Nerella Indira Rani, P. Ravi Kumar, Diddikadi Likitha, Anem Nnawyaa, Bhavani Singh Subedar
Degrés
Analytical Methods in Pharmaceuticals
article

Development of a Robust and Highly Sensitive UHPLC-MS Method for the Quality Control of Desidustat Formulations

Buggana Siva Jyothi, Nerella Indira Rani, P. Ravi Kumar, Diddikadi Likitha, Anem Nnawyaa, Bhavani Singh Subedar
article en

Abstract

AbstractPurpose: The study aimed at developing and validating an effective UHPLC-MS method thatmeasures Desidustat. The designed method was very sensitive and reproducible, and theexact analysis of this HIF-PH inhibitor could be done in both raw chemical form andcommercial tablet formulations.

Degrés
Kanya Maha Vidyalaya (IN)
Openalex Percentile: Top 14%
Analytical Methods in Pharmaceuticals
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.