JOURNAL ARTICLE

Eco-Friendly Stability-Indicating HPLC Method for Related Compounds in Pemetrexed Ditromethamine (Antineoplastic Agent) for Injection.

  • Published In: Journal of AOAC International, 2024, v. 107, n. 3. P. 415 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nekkalapudi, Arjuna Rao; Navuluri, Srinivasu; Pippalla, Sreenivas 3 of 3

Abstract

This article focuses on the development and validation of a novel eco-friendly, stability-indicating reverse-phase high-performance liquid chromatography (RP-HPLC) method for quantifying impurities in pemetrexed ditromethamine (PDT), an active pharmaceutical ingredient (API) used in injection formulations for cancer treatment. The method employs green chemistry principles, using a Zorbax SB C18 column with perchlorate buffer and acetonitrile as mobile phases, and was validated according to International Conference on Harmonization (ICH) guidelines for accuracy, precision, linearity, specificity, and robustness. Forced degradation studies demonstrated the method’s ability to separate degradation and process impurities, while greenness assessments using AGREE and GAPI tools confirmed its environmental sustainability. Additionally, a detoxification procedure using sodium hypochlorite was developed to safely treat cytotoxic waste from PDT manufacturing and testing. This method addresses limitations of existing United States Pharmacopeia (USP) monograph methods by providing a single, QC-friendly approach for both PDT API and drug product impurity analysis.

Additional Information

  • Source:Journal of AOAC International. 2024/05, Vol. 107, Issue 3, p415
  • Document Type:Article
  • Subject Area:Politics and Government
  • Publication Date:2024
  • ISSN:1060-3271
  • DOI:10.1093/jaoacint/qsae008
  • Accession Number:177044232
  • Copyright Statement:Copyright of Journal of AOAC International is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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