Data Quality, Management and Validation through the Eyes of a LIMS
Oral Presentation
Prepared by R. Benz
Khemia Software, 1459 Stuart Engals Blvd., Suite 304, Mt. Pleasant, SC, 29464, United States
Contact Information: rbenz@khemia.com; 734-513-9940
ABSTRACT
At its very heart, every good laboratory strives to produce quality data that is reproducible and defensible. No laboratory should aim for anything less. Anything less than perfect is simply not good enough. We are all human. Hence, we all make mistakes. An analyst can and has made a mistake that a department manager has not caught, and that mistake has made it all the way to the final report after being reviewed by the project manager. This has not just happened once but many times. The goal is to mitigate the human error in our processes.
As the regulatory environment becomes more stringent, and as analytical techniques become more complex, taking the human nature out of humans becomes ever more important. Modern LIMS have expanded over the years to cover field data and sample login as well as data acquisition from instrumentation to complex reporting and EDD generation. Complete data validation checkers are an integral feature of almost every modern LIMS on the market.
This talk will step through the outlines of data quality setup within LIMS, the validation of data quality through functionality and the overall management of laboratory data.
Oral Presentation
Prepared by R. Benz
Khemia Software, 1459 Stuart Engals Blvd., Suite 304, Mt. Pleasant, SC, 29464, United States
Contact Information: rbenz@khemia.com; 734-513-9940
ABSTRACT
At its very heart, every good laboratory strives to produce quality data that is reproducible and defensible. No laboratory should aim for anything less. Anything less than perfect is simply not good enough. We are all human. Hence, we all make mistakes. An analyst can and has made a mistake that a department manager has not caught, and that mistake has made it all the way to the final report after being reviewed by the project manager. This has not just happened once but many times. The goal is to mitigate the human error in our processes.
As the regulatory environment becomes more stringent, and as analytical techniques become more complex, taking the human nature out of humans becomes ever more important. Modern LIMS have expanded over the years to cover field data and sample login as well as data acquisition from instrumentation to complex reporting and EDD generation. Complete data validation checkers are an integral feature of almost every modern LIMS on the market.
This talk will step through the outlines of data quality setup within LIMS, the validation of data quality through functionality and the overall management of laboratory data.
