Ensuring the Regulatory Compliance of Laboratory Data
Guaranteeing data integrity is a prerequisite for regulated laboratories, which must provide fully documented evidence of all activities on request for audit purposes, to demonstrate compliance with national and industry regulations. Experimental results alone are not adequate; each dataset must be complete and contain all relevant metadata.
Working in a regulated environment carries with it a responsibility to ensure ongoing compliance for all procedures. Failure to do so exposes the company to huge risks, such as import bans, product recalls and even closure of production plants.
Data integrity is crucial to regulatory compliance; 65 % of all FDA warning letters issued in 2017 were due to data integrity issues, most of them because the data was incomplete. It is critical to maintain records or documented evidence of all relevant analyses, which can be checked by a second person and made available for auditing, especially in laboratories governed by GLP, GMP and GAMP regulations. Simply storing results is not enough; all raw data, relevant process information and metadata must be stored securely and be readily available.
One key tool to help regulated laboratories ensure compliance is the use of standard operating procedures (SOPs), essential documents that detail exactly how a specific activity or analysis should be performed, including processing and storage of all relevant data and results. Laboratory information management systems (LIMS) and electronic laboratory notebooks (ELNs) are now commonplace, helping the collation of data from an array of analytical tests. However, they may not necessarily capture the metadata – such as instrument service status, user ID and method of analysis – required for full regulatory compliance.
This guide offers practical advice on the best way to reduce errors, simplify processes and reinforce compliance to achieve comprehensive laboratory data integrity and security, as well as examples of how to design analytical workflows to ensure robust data capture, and potential risks to this process.