Typically, expert staff in a lab will be responsible, along with Quality Assurance, to design and document a standard operating procedure (SOP) for other analysts to follow for routine sample preparation tasks. These procedures are key for repeatability and accuracy… Read more >
Bringing increased confidence to sample preparation workflows using automation, smart laboratory tools and electronic documentation for recording analyst activities Laboratory employees appreciate the importance of traceability in their analytical work, whether to simply check for quality, or for… Read more >
When a crisis occurs, hindsight is a great teacher. Any company developing or manufacturing products that impact human health can learn from the recent nitrosamine impurity contamination of angiotensin II receptor blockers (ARBs) by reviewing… Read more >
In an earlier blog, I discussed the concerns about extraneous peaks that might appear in LC separations. While there can be many sources for peaks unrelated to the test substances, how do you decide which… Read more >
Suppressing Peak Integration Being able to optimize peak integration and identification, whether by resetting the method RT settings, manually identifying peaks or suppressing integration of specific known peaks are certainly tools which, in the wrong… Read more >
How do data integration and reintegration affect data integrity?
What procedures can an analyst use to ensure that a chromatography system is ready to begin analyzing samples, without the fear that the system suitability tests would immediately fail?
Halting a chromatographic analysis where the system is not performing correctly or when another error is evident in the separation is a valuable and scientific way to avoid creating unusable data that needs to be subsequently invalidated following a defined analytical lab error/result SOP. But what do you do with that orphan data?
Removing the ability for individual users to either delete data or to disable audit trails is expected to be both implemented and validated for data integrity. But when changes are required, what editing tools should be accessible to an analyst?
Orphan data may exist for any number of scientific or operational reasons, but in today’s environment – until the regulators trust the companies again – each piece of orphan data is suspect and may contain evidence of data tampering. So can you delete it?