Data Intrigrity in Pharmaceutical Industry

Introduction of Data Integrity:

Data integrity refers to the accuracy, consistency, and reliability of data throughout its entire lifecycle. Ensuring data integrity is crucial to maintaining the trustworthiness of information and making informed decisions based on accurate data.

Definition :-

"The extent to which all data are complete, consistant and accurate through-out the data lifcycle". (MHRA) 

It works on the principal of "ALCOA" and ALCOA+. 

Data Integrity As per USFDA regulation:  

For the purposes of this guidance, data integrity refers to the completeness, consistency, and accuracy of data. Complete, consistent, and accurate data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA).

Good Documentation Practices (GDP) are methods for recording,  correcting and managing data, documents and records, to ensure the  reliability and integrity of information and data throughout all aspects of  a product's lifecycle.

Data Integrity Issue?

• Raw data record not signed, no indication of who recorded/ observed the data? 
• Sharing username and password to an electronic system used to record data?

Simply say that GDP error को छुपाना या मिटाना data integrity होता है. Example:- 7 को 9 बनाना, 3 को 8 बनाना etc.

Data Integrity: 9 Principles Of "ALCOA" stand for:-

A - Attributable

L - Legible

C - Contemporaneous

O - Original 

A - Accurate 

ALCOA++ behind the “plus” stands the acronym CCEA stand for:- 

C - Complete

C - Consistent 

E - Enduring 

A - Available 

 

Here's some content that covers the concept of data integrity:

1. Attributable:- Who performed and when. Who has done, checked, verify, review, approve, correction! (डाटा को किसने generate किया है कब और किसके द्वारा).
2. Legible:- Can it be read? Permanent record. Data should be clear, easy to read and understand data (All data साफ - सुथरा और पढ़ने लायक हो और easy to understandable हो ). Handwritten records, electronic records, and printouts should all be legible to ensure accuracy and prevent misinterpretation.
3. Contemporaneous:- Data should be recorded at the time the event or activity was performed (कोई भी activity हो उसको उसी time पर record करना).
4. Original:- Original record or certified true copy (certified true कॉपी ना की रफ पेपर). Copies of original data should be properly identified as such and maintained according to procedures.
5. Accurate:- No error or editing was performed without documented amendments to ensure the accuracy of the data and records. The data must have following characteristics. It should be complete reflective observation and Error free (जो भी last का data ओरिजनल है बिना कट किये record करें error free).
6. Complete:- All data should be complete including, test repeat or re-analysis performed on the sample (जो भी data, test या analysis report है वो complet होना चाहिए ).
7. Consistent:- Consistent in the generation of records and application of date and time stamps in the expected sequence.
8. Enduring:- Data should be recorded in a controlled worksheet in laboratory notebooks or invalidated Electronic systems.
9. Available:- Data need to be available and accessible for audit review and inspection over the lifetime of the record.

"As per FDA guidline following terms are clarify as they relate to cGMP records":-

• Metadata:- Metadata is the contextual information required to understand data. A data value is by itself meaningless without additional information about the data. Metadata is often described as data about data.For example, the number “23” is meaningless without metadata, such as an indication of the unit “mg.
• Audit trail:- Audit trail means a secure, computer-generated,  time-stamped electronic generated record that allows for reconstruction of the course of events or activity relating to the creation, modification, or deletion of an electronic record. An audit trail is a chronology of the “who, what, when, and why” .
  
• Static:- Static used to indicate a fixed-data document such as a paper record or an electronic image.
  
• Dynamic:- Dynamic means that the record  format allows interaction between the user and the record content.
• Backup:- It refers to a true copy or certified copy of the original  data that is maintained securely throughout the data lifecycle or records retention period.The backup file should contain the data (which includes associated metadata) and should be in the original formate.
• Systems” in “computer or related systems”:- Its defines systems as people,  machines, and methods organized to accomplish a set of specific functions. Computer or related systems can refer to computer hardware, software, peripheral devices, networks, cloud infrastructure, operators, and associated documents (e.g., user manuals and standard operating procedures).
  

Importance of Data Integrity:

In pharma industry data integrity are key element to ensure products meet all the quality standard parameters up to the end of products. It is the process of maintaining and assuring the promise and consistency of data over its whole life .

Concept not new, but "Data integrity has been and currently is a major concerns for all health authority (FDA, MHRA, WHO, etc.). There are 80% of FDA warning letters issued had Data Integrity deficiencies. 

Data integrity is essential for various reasons. This involves:

1. Documentation Practices: Implementing proper documentation procedures to record all activities accurately, including manufacturing, testing, and distribution.
2. Electronic Records Management: Utilizing validated electronic systems for data capture, storage, and retrieval, with robust access controls to prevent unauthorized changes.Employing encryption, access controls, and cybersecurity measures to protect data from breaches and unauthorized access.
3. Training and Awareness: Providing training to staff on data integrity principles and the importance of maintaining accurate records.
4. Audit Trails: Implementing audit trails to track changes to electronic records, ensuring accountability and transparency.
5. Version Control: Maintaining clear version control for documents and data, preventing accidental overwriting or manipulation.
6. Data Review and Approval: Implementing a review and approval process for data entries, ensuring that only authorized personnel can make changes.
7. Data Backups and Recovery: Regularly backing up data and having a robust recovery plan in place to prevent data loss in case of system failures.
8. Cross-Functional Collaboration: Promoting collaboration between different departments to ensure data consistency and accuracy across the entire supply chain.
9. Regulatory Compliance: Adhering to regulatory guidelines and requirements (such as FDA's 21 CFR Part 11) to demonstrate data integrity practices to regulatory authorities.
10. Vendor Management: Ensuring that third-party suppliers and partners also adhere to data integrity practices, as they play a role in the overall supply chain.
11. Continuous Monitoring and Auditing: Regularly conducting internal audits and assessments to identify and rectify data integrity issues promptly.
12. Quality Management Systems: Implementing robust quality management systems that include data integrity controls as an integral part.
13. Risk Assessment: Identifying potential risks to data integrity and developing mitigation strategies to address those risks.
14. Change Control Procedures: Implementing procedures to manage changes that might affect data integrity, ensuring that changes are controlled and documented.
15. Investigations and CAPAs: Implementing a process to investigate data integrity breaches and implementing Corrective and Preventive Actions (CAPAs) to prevent recurrence. 

Remember that data integrity is not only about compliance but also about ensuring patient safety and public trust in the pharmaceutical industry. It requires a holistic approach involving technology, automation, computerized system, processes, and people.

"Trust is like a paper once its crumpled its can't be perfect".