Ensuring Data Integrity means taking various measures to confirm that a dataset is valid, complete, consistent, accurate and maintained within their original context, as required by applicable regulations. Data reliability refers to the trustworthiness of data for decision-making, including derived insights.
The abundance raw data produced by a laboratory makes data integrity a challenging aspect in maintaining high quality standards. The primary focus of a Laboratory Automation System is to minimize human errors, ensuring the accuracy and reliability of data by optimizing workflows and processes in the lab.
Characteristics of Data Integrity: The ALOCOA+ requirements
The FDA (Food and Drug Administration) implementation of the cGMP (Current Goods and Manufacturing Practice) compliance guidance for the data integrity and the World Health Organization (WHO) guidance related to data integrity highlight the importance of ALCOA+ principles. These principles ensure data is:
- Attributable: Identify the person responsible for conducting and recording the measurement. The reasons of any modifications must be recorded.
- Legible: Data must be archived and readable indefinitely, not just for the project duration.
- Contemporaneous: In real time, the data is documented and logged for accurate and up-to-date records.
- Original: The RAW data should be available in its original form and verified. All analysis should be traceable to the original data.
- Accurate: There should be no loss/modification of the original data and the system must have built-in accuracy checks.
- Complete: No data has been removed from original records and audit trails for any modifications need to be maintained.
- Consistent: Timestamp the data for easy access to conclusive results and to eliminate doubt about the presence of up-to-date records.
- Enduring: The data is stored safely and securely for availability on a later date. Robust mechanisms for data backups, disaster recovery, cybersecurity and uninterrupted power supply need to be ensured.
- Available: Data can be readily accessed when it is requested by an authorized user.
Advantages of Data Integrity and Reliability with the DirectorTM Scheduling Software
The integration of Automation Software in a process enables the digitalization of documentation and automation processes, including mapping all measuring devices in the laboratory.
Laboratory staff is given accurate descriptions of every operation stage, allowing them to simulate procedures, track plate inventory in real-time, receive remote error notifications, and utilize advanced data logging. The increased focus on data integrity and data reliability help achieve:
- Scientific Efficacy: Lab Automation guarantees efficient data collection and incorporates necessary safeguards to ensure impartial and secure data, free from unintentional manipulation. These advantages significantly contribute to data reproducibility and trusted results.
- Legal Protection:. Laboratories that fail compliance audits receive warning letters from regulatory agencies like the FDA in the US. Failure to uphold data integrity exposes laboratories to the risk of facing costly legal consequences that can consume time and damage a company’s reputation.
- Operational Efficiency: These systems help ensure data security by providing access controls, audit trail and encryption capabilities. It also helps in identification of bottlenecks and optimization of laboratory resources.
The adoption of laboratory automation is increasing in the 21st century and has helped laboratories focus on Quality Control, Innovation and Scientific breakthroughs.
