JOURNAL ARTICLE

Assessment of the surface contamination of the primary packaging of oral antineoplastic drugs and secondary packaging of chemotherapy preparations at a Swiss hospital.

  • Published In: Journal of Oncology Pharmacy Practice, 2025, v. 31, n. 4. P. 551 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nguyen, Nathalie; Vallet, Virginie; Bouchoud, Lucie; Falaschi, Ludivine; Rudaz, Serge; Bonnabry, Pascal; Fleury-Souverain, Sandrine 3 of 3

Abstract

This article focuses on assessing the chemical contamination of packaging surfaces of oral and injectable antineoplastic drugs handled in a Swiss hospital setting. Using a validated wipe sampling method combined with ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC–MS/MS), the study analyzed 36 primary packages of oral formulations and 60 leak-proof secondary packages of injectable preparations, along with carriers used for transport. Results showed that 58% of oral primary packaging and 90% of injectable secondary packaging were contaminated with trace levels (nanograms) of antineoplastic drugs, predominantly methotrexate, gemcitabine, and cyclophosphamide. The study highlights that contamination likely arises from handling processes and packaging materials, emphasizing the necessity of appropriate personal protective equipment for healthcare professionals and suggesting improvements in chemical decontamination protocols to reduce occupational exposure risks.

Additional Information

  • Source:Journal of Oncology Pharmacy Practice. 2025/06, Vol. 31, Issue 4, p551
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:1078-1552
  • DOI:10.1177/10781552241250010
  • Accession Number:186080869
  • Copyright Statement:Copyright of Journal of Oncology Pharmacy Practice is the property of Sage Publications Inc. 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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