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ALCOA+ Principles – The Backbone of Data Integrity

Data integrity is data’s accuracy, completeness, consistency, and validity throughout its lifecycle. It helps ensure that the products delivered to patients are safe and effective for consumer use.  

To ensure the data’s integrity, regulators and governing bodies have established guidelines for manufacturers to follow to protect public health. In particular, the U.S. Food and Drug Administration (FDA) has provided a set of principles in 21 CFR Part 11, known as ALCOA+, to help guide data collection practices and data integrity within the pharmaceutical and biotechnology industries. Data integrity applies to paper and electronic records and should be integrated within the entire quality management system.  

Advantages of a modern electronic system 

Electronic-based systems have numerous advantages vs traditional paper-based record systems. Many modern electronic systems include a security suite with audit trail and, electronic signature capabilities, data verification at both input and output, and backup, recovery, and data transfer processes. Traditional paper-based systems are more prone to errors, such as transcription mistakes, unsanctioned access to records, and are susceptible to loss over time. Even legacy electronic systems may utilize shared logins and contain insufficient detail for audit trail and data review, which add to the challenges of complying with data integrity practices.  

What does ALCOA+ stand for? 

  • Attributable: Data should demonstrate who observed and recorded it when it was observed and recorded, and who it is about. This principle requires manufacturers to identify and record the entity responsible for acquiring or using a given data point. This can be achieved physically by signing and dating a paper document or electronically through an electronic system.  
  • Legible: Data should be easy to understand, recorded permanently and original entries should be preserved. This requires the data to be readable and permanent. Paper-based records are more susceptible to human error and alteration, making the data more difficult to read. Modern electronic records reduce errors and make data more legible.  
  • Contemporaneous: Data should be recorded as it was observed and at the time it was executed. When gathering data, manufacturers must ensure the data is time-stamped to prevent backdating. The data should also show the time of any subsequent modifications.  
  • Original: Source data should be accessible and preserved in its original form. Original data or ‘true copy’ should always be used in the master record. Further data processing requires the original data instead of copies or secondary sources.  
  • Accurate: Data should be free from errors and conform to expectations. Good documentation practices dictate that manufacturers use correct and unedited data.
  • (+) Complete: Manufacturers must keep all generated raw data, including the metadata. Even the original data points not in use must be tracked with a complete audit trail. When data is complete, it means no deletion has taken place since the date it was recorded.  
  • (+) Consistent: Data records must be consistent and the same when accessed from anywhere within the system. If the data was analyzed or modified, one should be able to follow the steps sequentially to get a consistent result.  
  • (+) Enduring: All records and information must be stored long after data collection. Manufacturers must have data retention procedures, as the data might be referred to in the future.  
  • (+) Available: While all records and information are in long-term storage, it is also important to be able to retrieve this stored data whenever needed. Manufacturers must have the data available when regulators or authorized entities require access.  
Data displayed on a desktop - PSC Biotech

Why is data integrity important? 

Pharmaceutical and biotechnology manufacturers face intense scrutiny for their products due to their potential impact on the health and well-being of the end user. The FDA will conduct regular audits to verify that the manufacturer maintains GMP compliance. To achieve and maintain GMP compliance, manufacturers must follow the ALCOA+ principles.  

Failure to comply with data integrity requirements can result in non-validated results, which may lead to post-market issues and product recalls. These can have high business costs and require additional testing to maintain compliance.  

How does data integrity affect the entire business? 

FDA enforcement actions against manufacturers with data integrity violations can result in a wide array of consequences: facility shutdown, delayed/denied drug approval, remediation costs, product recalls, loss of customers due to lack of trust, etc.  

Manufacturers also rely on production data to guide their business decisions and drive continuous improvement. If their data is inaccurate, inaccessible, or difficult to read, making sound business decisions becomes extremely difficult. Clear and accurate data ensures the safety and traceability of processes and products and enables supervisors and managers to identify inefficient areas and issue corrective actions.  

Data Integrity is not only for manufacturers

Data integrity is now seen as an essential aspect that should be considered throughout a drug’s entire lifecycle, from discovery to manufacturing. The FDA expects scientists and researchers to prioritize data integrity from the moment they believe their research may contribute to the discovery of a drug that will be approved for use by patients. The large amount of data gathered by research and development laboratories from various sources during drug discovery and development can make maintaining data integrity challenging.  

R&D data integrity is essential for making good decisions about what target compounds should enter preclinical trials and the effective selection of candidate molecules for clinical trials. Poor records management and data integrity violations during research and development can result in an unsuccessful or delayed patent process, poor decisions on future investments in clinical trials, and even rejection of an Investigational New Drug (IND) or New Drug Agreement (NDA) by the FDA.  

Incorporating data integrity practices into research and clinical studies allows those laboratories to effectively face data integrity challenges and ensure their data is accurate, complete, and enduring. This ensures that the drugs comply with GMP regulations and that patients receive the most effective and safest therapy.  

Data written in black on a window - PSC Biotech

PSC Biotech: Your partner for all data integrity needs. 

At PSC Biotech, we understand the data integrity responsibilities and provide audit and remediation services for data integrity. Our insightful analyses and audit reports promote data integrity and record management strategies, encouraging data protection and privacy. We ensure our clients meet the standards of the FDA, the European Commission (EC), and regulatory agencies globally. Whether you do research and development, clinical trials, quality control, manufacturing, data management, or inspection, PSC Biotech can help you establish, evaluate, and improve your data integrity.  

Contact our experts today at sales@biotech.com to discover how PSC Biotech can help you achieve precision, reliability, and trust in your testing and calibration processes.