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Good Laboratory Practice (GLP)
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One of the fundamental purposes of the Principles of Good Laboratory Practice (GLP) is to ensure the quality and integrity of test data related to non-clinical safety studies. The way in which study data, supporting human, animal and environmental safety assessment, is generated, handled, reported, retained and archived has continued to evolve in line with the introduction and ongoing development of supporting technologies. However, the main purpose of the requirements of the Principles of GLP remains the same in having confidence in the quality, the integrity of the data and being able to reconstruct activities performed during the conduct of non-clinical safety studies. This 蜂鸟电竞在线入口 Advisory Document on GLP Data Integrity provides guidance for test facilities or test sites that conduct GLP studies and aims to promote a risk-based approach to the management of data.
Countries' response to address t he challenges posed by COVID-19 to GLP test facilities
The Mutual Acceptance of Data (MAD) system
The 蜂鸟电竞在线入口 Principles of Good Laboratory Practice (GLP) ensure the generation of high quality and reliable test data related to the safety of industrial chemical substances and preparations. The principles have been created in the context of harmonising testing procedures for the Mutual Acceptance of Data (MAD).
Mutual Acceptance of Data
The MAD system helps to avoid conflicting or duplicative national requirements, provides a common basis for co-operation among national authorities and avoids creating non-tariff barriers to trade. 蜂鸟电竞在线入口 countries and full adherents have agreed that a safety test carried out in accordance with the 蜂鸟电竞在线入口 Test Guidelines and Principles of Good Laboratory Practice in one 蜂鸟电竞在线入口 country
must
be accepted by other 蜂鸟电竞在线入口 countries for assessment purposes. This is the concept of “tested once, accepted for assessment everywhere*”.
This saves the chemicals industry the expense of duplicate testing for products which are marketed in more than one country.
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Did you know?By reducing duplication, and creating a framework for the sharing of work, the MAD system saves governments and industry around € 309 million each year, as well as reduces the number of animals used in such testing. |
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