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< Umsetzung der GLP-Richtlinien mit dem mbl book
08.11.2016 12:01 Age: 140 Days

Implementation of the GLP guidelines with the mbl book

How can I correctly comply the GLP requirements for research documentation with the mbl book?


What is the target of the Good Laboratory Practice (GLP)?

GLP is used for quality assurance in non-clinical safety tests. These GLP guidelines are intended to make all steps of a laboratory process (such as an experiment, a safety test, etc.) comprehensible. This means that it must be recorded, who has what, when, how and with what carried out. Not only the purely experimental process in the laboratory but also the planning and the requirements are to be documented. The prerequisites include the persons involved, the spatial conditions, the existing technical infrastructure (devices together with IT) including their settings and their calibration status, the necessary materials and reagents, required documents and information. Standard operating procedures (SOPs) are also required to describe the implementation of experiments and the use of equipment.

How does this go in mbl book?

1.) You describe your project planning in this way

Create experiments for project planning. Describe all the experiment underlying plans,
 thoughts and conclusions step by step.

In the header data of the experiments, you can refer to the sources of your research and
previews. This can be done by document or by (Intranet) link.

 

2.) Create methods for representation your SOPs

To do this, add the following information (as text or document) to the method steps:
- the task,
- information on the occupational safety requirements, the technical handling of the equipment and the materials (e.g., kits).
- a list of required materials,
- the process description (the planned procedure in the experiment).

Please release these methods after entering all information for use.

 

3.) Recording of laboratory procedures (experiments)

You can point to specific safety requirements, material properties, device settings or
process requirements in the experiment header data. This may be e.g. as a intranet link or as an upload link to a document.

You describe your performed laboratory processes in the experiment steps as free experiment text or by inserting a method template with a SOP.

Materials that have been used are to be recorded as an experiment step by text or by database reference.

Raw data and results are usually found in the experimental process. In the experiment steps, insert large data (for example, raw data) by intranet link.

Result data (e.g. graphic files to the result illustration) must be inserted as a document step. Each document in the mbl book automatically gets a unique ID and a time stamp.

It is practical if you before loading the document in the experiment does the following:
Rename the document with the meta data such as title (subject/content), time of creation etc. This metadata can also be edited alternatively in a text step before or after the document step in more detail.

Write a result analysis.

Confirm in a timely manner all experiment steps and release the experiment. By confirming the experiment steps, these experiment steps appear in the daily logs of the confirming user and the confirmed data can not be changed with the mbl book.

 

4.) Documentation of the general conditions

The maximum biological and genetic security levels as well as the project managers are recorded in the projects. These data are valid across the project. Changes to the project manager are automatically written by the mbl book.

The maximum biological and genetic security levels as well as the section managere must also be recorded in the sections. This cross section data is valid for all the experiments of this section.

You can enter information about the genetic engineering facility in the Master Data / Properties module. In the cumulative comments of the projects or the sections one can enter other general laboratory conditions.

Only the divergent and additional conditions are to be recorded in the respective subordinate experiments. This can be done in the comment field of the header data or as a text step in the experiment.