Related to Pharma and Medicinal sector e.g. Good Laboratory Practice (GLP), Good Manufacturing Practice (GMP), Medicines and Healthcare products Regulatory Agency (MHRA), FDA 21 CFR, GXP.
Why to anonymize Spectroscopy Data?Without anonymization your are maybe limited in the use of third-party services to process your data (because GDPR, DSGVO). To create e.g. a Multivariate Model (for prediction) out of your spectral and lab-data, it only needs the X and Y matrix.
Think about that:
“without the context provided by metadata, the data have no meaning” –MHRA GXP Data Integrity Guidance and Definitions. (Medicines and Healthcare products Regulatory Agency, London, 2018).
That means, without the metadata that describes what the data is about, the data has no meaning, so no reuse is possible, the data is just a bunch of numbers without context, so it’s anonymized.
And this allows you to send your anonymized data to third-party services to build optimal prediction models for you.
How to get Anonymized Spectroscopy Data for processing by third-party?1. Export spectral and lab data from your NIR system database to JCAMP-DX file.
- All major NIR software systems are nowadays capable of this, because of data exchange with other (vendor) systems.
- Just drag&drop the JCAMP files onto the tool and you get anonymized files back with a difference view, so you can see what is anonymized in detail.
- All the information and metadata that is not needed for model-building is removed.
- Even the names of the properties like “Fat”, “API” or “Moisture” gets anonymized.
- The original files are kept unchanged and new .anon.dx files are created in the “Anonymized” subdirectory.
- Note, that this extra step is no longer needed when you trust the locally used JCAMP-Anonymizer software.
- E.g CalibrationModel.com for NIR prediction model development.
For more information see also
Anonymize your NIR spectroscopy data
Trust and Anonymization does not contradict
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