ISO 11040-7:2024
International Standard
Current Edition
·
Approved on
03 June 2024
Prefilled syringes — Part 7: Packaging systems for sterilized subassembled syringes ready for filling
ISO 11040-7:2024 Files
English
25 Pages
Current Edition
USD
169.57
ISO 11040-7:2024 Scope
This document specifies a packaging system that is used to deliver sterilized subassembled syringes ready for filling in tubs and nests.
Downstream processes (processes after filling such as in house/outside transport, reprocessing) can result in specific requirements on the packaging system used to deliver sterilized subassembled syringes ready for filling. However, these requirements are not within the scope of this document.
NOTE 1 Glass barrels and sterilized subassembled syringes ready for filling, plunger stoppers, and plastic barrels for injectables are specified in ISO 11040-4, ISO 11040-5 and ISO 11040-6.
NOTE 2 ISO 11607-2 addresses validation requirements of sealing and packaging processes for medical devices.
Best Sellers
GSO 150-2:2013
Gulf Standard
Expiration dates for food products - Part 2 :
Voluntary expiration dates
YSMO GSO 150-2:2020
GSO 150-2:2013
Yemeni Technical Regulation
Expiration dates for food products - Part 2 :
Voluntary expiration dates
GSO 9:2022
Gulf Technical Regulation
Labeling of prepackaged food stuffs
YSMO GSO 2055-1:2020
GSO 2055-1:2015
Yemeni Standard
HALAL FOOD - Part 1 : General Requirements
Recently Published
ISO/TS 4966:2026
International Standard
Nanotechnologies — Silica nanomaterials — Specification of characteristics and measurement methods for nanoporous silica microparticles applied in liquid chromatography
ISO/TS 44005:2026
International Standard
Collaborative business relationship management system — Guidance on leadership for collaborative working
ISO 10325:2026
International Standard
Fibre ropes — High modulus polyethylene — 8-strand braided ropes, 12-strand braided ropes and covered ropes
ISO/IEC TS 42112:2026
International Standard
Information technology — Artificial intelligence — Guidance on machine learning model training efficiency optimization
