Laboratory Data Integrity Guide
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Laboratory Data Integrity Guide

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The Laboratory Data Integrity Guide illustrates in various examples of analytical workflows safe ways to achieve data integrity and discusses where data integrity might be at risk. Secure your measuring processes: learn more about data handling, SOP guidance and achieving data integrity.

Laboratory Data Integrity Guide — Data Handling, SOP Guidance, Practical Examples
Laboratory Data Integrity Guide — Data Handling, SOP Guidance, Practical Examples

For laboratories that must comply with GLP, GMP and GAMP regulations it is important to have records or documented evidence of all relevant analyses that can be checked by a second person and are also readily available for audits. Storing the result is not enough, each result set has to be complete and contain all relevant metadata.


In 2016, 80% of the FDA warning letters were issued due to the lack of data integrity. The main reasons were incomplete data, an aspect that can be prevented by using the right solutions. The highest risks, when not working in a compliant manner, lie in import bans, product re-calls or even the closing of production plants.


Downaload Laboratory Data Integrity Guide — Secure your Measuring Processes with LabX Software. Learn more about proper Data Handling, SOP Guidance and Practical Examples

Laboratory analysts must often follow standard operating procedures (SOP) for each analysis and document the entire process as well as record the results. Many labs have turned toward LIMS and ELN systems which are designed primarily to aggregate result data from an array of analytical tests. Yet these systems are largely leaving out the so called metadata – like instrument service status, user ID and method applied – information that is crucial to put results from analytical instruments into a context and to achieve data integrity. Regulations and standards such as FDA (21 CFR Part 11), EU (Annex 11), GMP, and ISO (ISO 17025) have recognized both the advantages and limits of electronic data systems, and have increasingly established further controls for the use of such systems all the way down to bench top instruments. So reducing errors, simplifying processes, reinforcing compliance, and ultimately achieving data integrity with a system integration has become more challenging.

The Laboratory Data Integrity Guide illustrates in various examples of analytical workflows safe ways to achieve data integrity and discusses where data integrity might be at risk.

Downaload Laboratory Data Integrity Guide — Secure your Measuring Processes with LabX Software. Learn more about proper Data Handling, SOP Guidance and Practical Examples

Laboratory Data Integrity Guide
Secure Your Measuring Processes with LabX Software


Editorial:

One of the primary motives driving organizations to purchase a LIMS, ELN, or LES [collectively, Laboratory Informatics Systems (LIS)] is the appeal of connecting laboratory instruments to them for electronic data collection. When a laboratory instrument is directly connected for electronic data capture, the costs in time, labor, and potential error associated with manual transfer of data are essentially eliminated. However, even with the compelling advantages, many instruments and systems still remain disassociated and data entry and transfer are largely handled manually.

Manual data transcription and report creation keep the laboratory analyst from focusing on the science. Frequently, the transcribed data is missing elements and the traceability needed to satisfy internal quality management and regulatory mandates. The end result is that time and revenue are lost due to the time and effort it takes laboratory analysts to resolve the situation by gathering missing data, re-transcribing results, documenting missing controls, and preparing reports.


Table of contents:

An Enhanced Strategy for Data Integrity
1.1 The Risk of Incomplete
1.2 The Daily Challenge
1.3 Finding the Best Approach

An Example for Weighing

2.1 Finding the Best Approach
2.1.1 The Way Many Labs Work Today
2.1.2 Overview of the Weighing Processes
2.2 Process 1: Weighing and Recording by Observation
2.3 Manual Process and Multiple Transcription Error Checks
2.3.1 Transcribing Data and Transcription Error Checking are Error-prone
2.3.2 Lack of a Data Audit Trail
2.3.3 Failure to Meet GLP, GMP and GAMP Regulatory Requirements
2.4 The Way Labs Could be Processing Data
2.5 Process 2: Weighing with a Printer Attached to the Balance
2.5.1 Process Improvements
2.5.2 Process Meets Regulatory Expectations
2.6 Process 3: Weighing Using LabX Server Software
2.7 Comparison and Summary of the Three Ways of Working
2.7 Validation of an Electronic Process

An Example for BRIX Determination

3.1 The Workflow of Smart Standard Preparation
3.2 Seamless Workflow from Balance to Refractometer
3.3 The Benefits of this Workflow over Stand-alone Instruments

An Example for Titration

4.1 Efficient and Error-free Titration Workflows
4.2 Automated data transfer
4.3 Automatic Method Selection with LabX® SmartCodes
4.4 New Level of Data Integrity

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