Is Data Integrity an Impossible Task?

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Executive Summary Be it in the pharmaceutical or medical device industry, any minor deviation either in the processes or

in data maintenance, could easily trigger regulatory warnings and product recalls. The consequences

are huge in terms of time, money, resources, and much more. In such regulated environments, or-

ganizations must comply to industry regulations when it comes to assuring to data integrity, or risk

suffering huge, yet preventable consequences

This whitepaper helps understand why the regulated industry must ensure data accuracy, and how

data completeness allows organizations to breathe easy. It also highlights how ill-treatment of data

will disrupt organizations' chances to meet Current Good Manufacturing Practices (cGMPs) or Good

Laboratory Practices (GLP). Finally, the whitepaper discloses how technological solutions help in

implementing a holistic approach to data integrity.

Data Integrity in cGxP Guidelines Any system that captures, stores, modifies and retrieves electronic data must ensure integrity from

design, to implementation, to data usage. cGMPs or Laboratory Practices demand that organizations

build meaningful and effective data management strategies to prevent and detect data integrity

lapses. Data integrity is accomplished with good documentation practices for static and dynamic

records, therefore, organizations must build a dynamic data warehouse. This, in turn, helps maintain

complete, consistent and accurate data as per 21 CFR Part 11 during the pre-and post-market

product approval process.

To dig deeper, data integrity is not an optional requirement. It is a business imperative, which must

be tracked and maintained throughout the data lifecycle to ensure the safety, efficacy, and quality of

drugs, and of FDA's ability to protect the public health.

GMP/GLP Regulations: Irrespective of product development procedures of drugs, biologics, and

medical devices, general principles and requirements of compliance apply equally across regulated

industries.

For example, the critical studies performed during the research & development stage, impact data

integrity. Although FDA's 21 CFR 58.3 (d) does not regulate the early stages of product development,

laboratories are expected to follow certain accepted practices to ensure data reliability. Hence, good

practices for experimental design & record keeping are mandatory.

21 CFR Part 58 (GLP): During the pre-clinical development, 21 CFR Part 11 applies for the systems

used for capturing, storing and retrieving the nonclinical data where GLP principles are enforced.

Data Integrity Regulations of FDA:

• 21 CFR Part 11: Electronic Records; Electronic Signatures

• 21 CFR Part 58: Current Good Laboratory Practice for Pharmaceutical Products.

• 21 CFR Part 110: Current Good Manufacturing Practice in Manufacturing Packing orHolding of Human Food.

• 21 CFR Part 210 – Current Good Manufacturing Practice in Manufacturing, Processing,Packing, or Holding of Drugs; General.

• 21 CFR Part 211: Current Good Manufacturing Practice for Finished Pharmaceuticals.

• 21 CFR Part 212 – Current Good Manufacturing Practice for Positron EmissionTomography Drugs.

• 21 CFR Part 820: Quality System Regulation for Medical Devices

• Q7A – Active Pharmaceutical Ingredients.

Annex 11 of Europe:

• Annex 11: Electronic Records

• GMP Chapter 4 – Documentation

• Annex 4: Manufacturing of Investigational Drug Product

• OECD Guidance for the Conduct of Test Facility Inspections and Study Audits

• OECD Revised Guides for Compliance Monitoring Procedures for GLP

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The quality unit of a laboratory is entitled to adhere to protocols designed by a study director, and

is responsible for ensuring data accuracy throughout the laboratory study. Here, the quality unit

requires the support of a dynamic study management system to automate the protocol and report

writing processes. In fact, automated report generation would enable the quality unit to update the

Master Schedule without any deviations. Similarly, the data of facilities and equipment used in the

study must be validated with SOPs.

Key Functional Areas in GLP for Data Integrity

Recent Elements Highlighted in GMP Audits • Analysis of Out-Of-Specification (OOS) document developed during GMP product testing.

• Capture the details of date, time, and authentic person approving the GMP testing.

• Documentation & validation of test methods and the equipment used in GMP testing.

• CAPA documentation for OOS investigations.

What is ALCOA and Why is it Critical in Ensuring Data Integrity? Data integrity aims to maintain the purity of the data created and does not allow any unintentional

changes to its original document. Even if the change is necessary, the organizations must ensure

proper validation and authorization. The ALCOA principle helps combat unauthorized access and

support in meeting FDA's 21 CFR Part 11 compliance without any hassles.

Attributable: To be attributable, one must track the data authenticity. Here, the authenticity refers

to a person who approves data changes and the date and time where the data has been modified.

Legible: Any data which is unclear and incomprehensive builds roadblocks in the compliance

pathway. Hence, a document, either printed or electronic, must be readable and permanent.

Contemporaneous: Data is attributable and legible when its actual date and time are recorded.

Therefore, organizations must upgrade all the systems and tools to enable date and time stamp

in real-time.

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Original: To be compliant with Part 11, one must preserve the original data. Here, a user can

maintain accuracy, data completeness, content and meaning by preserving revision history with

actual date and time.

Accurate: Data accuracy depends on its validation process. Hence, enterprise tools must support

in creating a secure environment to track who conducted the study, when, where, why and how.

Consequence of Data Integrity Lapses in Regulated Industry Data is very volatile and vulnerable to unexpected changes. The regulated industry has been suffering

from uncontrollable data deviations due to lack of adequate solutions to combat conflict between

people and processes. Here are the three ‘’I’’s which hamper the content operations:

Inconsistent: Multiple sources, multiple users, multiple copies, non-contemporaneous

record-keeping, poor security, lack of version control and tracking of modifications, etc. These

inconsistencies lead to wrong decisions, wrong submissions, regulatory risks, threat of FDA

Warning Letters, etc.

Incorrect: Manual data entry, improper data migration, data purging etc., thus creating erroneous

results, slow turnaround time, unclear formatting to name a few.

Irrelevant: Huge and unwanted data stored by multiple users can create roadblocks and advance

irrelevant decisions, delayed time-to-market, product recalls and such.

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Uncover Spreadsheet Validation Myths

Data integrity lapses occur when the closed or open systems used for various workflows

fail in data validation.

Spreadsheets are pervasive and are globally accepted for data management. However,

these tools are not practical when it comes to ensure to regulatory compliance. Often

organizations have myths over spreadsheet validation. They believe that since spread-

sheets cannot be validated accurately, they need not adhere to regulatory norms.

In reality, ANY tool used in document management needs validation. In fact, validation

related FDA Form 483s and Warning Letters are high for spreadsheet usage when

compared to that of computerized programs.

How Multiple Enterprise Systems Can Help Ensure Data Integrity: Document Management: Electronic records of essential documents like Standard Operating

Procedures, SLAs, and laboratory or manufacturing procedural documents demand real-time

tracking. However, poor document management practices can undermine the regulator’s oversight

and consumer confidence in the product.

In such case, a digital workplace allows users to seamlessly upload, process, and distribute content

assets in accordance with the prescribed rules. The changes in the documents are time-stamped

and secured with digital signatures.

Similarly, data can be contemporaneous if captured in real-time and auto-filed. An effective,

automated document management system helps maintain document versioning and history and

enhances multiple document filing views in accordance with the compliance.

Additionally, storage of meta tags helps index the structured and unstructured data, which in turn,

facilitates easier data retrieval. Essentially, a cloud platform:

• Bridges the gap between people and information.

• Helps share and use the data easily, anytime, and anywhere.

• Supports in ensuring consistent effort in data completeness.

• Helps reduce unwanted risks and the costs due to structured data collection.

Enterprise Asset Management: Critical equip-

ment within laboratories and manufacturing

divisions store bundles of data. However, it is

highly difficult to maintain data consistency

across multiple instruments. The disparities in

data can be avoided by integrating lab instru-

ments with an effective asset management

system.

In addition, an asset management system

can help track data integrity throughout the

import and export process with the support

of add-on tools. Here, a real-time monitoring

system ensures that data is accurate and

traceable.

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CAPA Management: For any data integrity lapse, FDA demands a comprehensive investigation.

However, the deviations may be left unnoticed if the existing CAPA management tool fails to

integrate with the quality management system. Hence, it is better to adopt an integrated quality

management system with a comprehensive CAPA management module.

Here, the QMS should have appropriate technical controls to contain multiple user access and data

security protocols to describe user's roles and responsibilities in terms of privileges to access, change,

modify, create, and delete projects and data.

Data Migration: Technological advances enforce organizations to replace their obsolete legacy

systems with dynamic new systems. However, the data integrity will be at greater risk if data

migration is improper.

A dynamic data migration tool helps connect existing enterprise repositories, federates content,

integrates systems, replicates critical data, and migrates legacy repositories.

Laboratory Business Process Management: Often, most organizations use multiple systems, such as

Laboratory Information Management System (LIMS), Electronic Laboratory Notebooks (ELNs), Quality

Management Systems (QMS), Electronic Data Capture Systems, and Learning Management Systems

(LMS) to track typical lab operations. In this scenario, the disparities in the systems develop data

integrity lapses.

Here, a unified laboratory system would help integrate the multiple systems and would streamline

the critical business processes.

Nonclinical Laboratory Studies: The data captured, developed and stored during nonclinical

laboratory studies have significant role in GLP. From raw data to study completion document, a study

director must maintain original copies of documentation, protocols, specimens, and the final reports.

The integrity will be in high-risk when subordinates either manipulate or fail to bring any data integrity

issues, during each periodic inspection, to the notice of the director. However, the errors can be

avoided with automated audit trail capturing tools, which require minimum human intervention.

Manufacturing Practices: With regards to manufacturing practices, the quality control unit has all

the authority, for any deviations in production records, to approve or reject all the components,

in-process materials, packaging materials, labelling, and drug products. Hence, organizations must

employ well-trained quality experts who understand Part 11 compliance norms.

In the case of equipment used in the manufacturing, processing, packing, or holding of a drug

product, the data of the equipment must be scrutinized for appropriate design and calibration. Good

Manufacturing Practices expect accuracy and completeness in the records of maintenance, cleaning,

sanitizing, and inspection (Sec 211).

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As per Sec 211.180, any pro-

duction, control, or distribution

record must be maintained,

specifically associated with a

batch of drug product, at least

for a year after the expiration

date. Here, the quality control

unit must have a content

management system with 21

CFR Part 11 controls to

maintain the archives (original

and final reports).

Conclusion Data integrity is a continuous journey. The sailing would be smooth if there is a perfect harmony

between people, process, and technology. However, this can ONLY be accomplished under efficient

leadership with commitment and sense of ownership, and quality initiatives that are supported by

comprehensive quality and compliance management solutions.

Essentially data integrity is NOT an impossible task. Organizations can build the culture of data integrity

by providing constant education and communication to internal and external staff; by forecasting

and detecting possible risks through real-time monitoring systems; by defining a strategy for the

intersection of data integrity and technology; and finally, by establishing a well-defined structure for

data integrity. The success rate of meeting 21 CFR Part 11 compliance is proportional to an organiza-

tions' efficiency in meeting GLP and GMP requirements. To that end, cloud-based quality and

compliance solutions can provide the essential framework for integrating people, process, and tech-

nology and ensuring data integrity across the enterprise.

Xybion Corporation 2000 Lenox Drive Lawrenceville, NJ 08648

xybion.com(609) 512-5790

Leveraging our extensive global experience working with

companies of all sizes, we offer deep domain knowledge of

FDA regulations and have a long track record of helping clients

build effective compliance and risk mitigation strategies.

Since 1977 Xybion has provided software, services and

consulting for global corporations operating in highly regulated

industries. Our unique solutions focus on regulatory

compliance, GRC, quality management, GxP, integrated

preclinical lab management, early-stage drug discovery, content

migration and systems validation. Xybion specializes in helping

companies improve their overall compliance processes and

provides a complete view into organizational risk across global

organizational models.

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