Data Integrity

Data Integrity-Presented by Paris Suru (15mph808)

Drashti Patel (15mph803)

Contents

• Introduction• DI-ALCOA• Why is it a hot topic• Challenges noted by agencies• Why it arises?• Regulatory perspective• Change in regulatory focus

• Impact of absence of DI• DI CASE• Inspection focus• AIP• Breach of DI• USFDA inspection• How to prevent DI issues

Introduction

• Data Integrity refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle and is a critical aspect to the design, implementation and usage of any system which stores, processes or retrieves data.

• Data integrity is a prerequisite for the regulated healthcare industry as decisions and assumptions on product quality are made based on data.

Data Integrity - ALCOA• FDA uses the acronym ALCOA to define its expectations of

electronic data. The “L” originally stood for legible, which dates back to the time when FDA was dealing with scanned documents. It has been updated to “long lasting.”

AttributableLong-lasting (legible)ContemporaneousOriginalAccurate

Why is it a hot topic now ?

Agencies expects that pharmaceutical companies should retain complete and accurate records and all raw data and to make that available to inspectors .The integrity of data generated by a regulated pharmaceutical companies and laboratories matters most, because properly recorded information is the basis for manufacturers to assure product identity, strength, purity, and safety and non-compliances found in the integrity of data leads warning letters and a regulatory action from the agencies.

Challenges noted by the agencies

• Non contemporaneous Recording: Failure to record activities at the time when activity was performed. There is evidence that the records were signed by company personnel when the person was actually absent on that day.

• Document back-dating: Backdating stability test results to meet the required commitments.

• Copy of existing data as new information: Test results from previous batches were used to substitute testing for another batch or acceptable test results were created without performing the test.

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Continue…..

• Re-running samples to obtain better results: Multiple analyses of assay were done with the same sample without adequate justification and in some cases samples were tested unofficially or as a trial analysis until desired test results obtained.

• Data fabrication and data discarding: Original raw data and records were altered for e.g., by using of correction fluid or Manipulation of a poorly defined analytical procedure and associated data analysis in order to obtain passing results• • Not reporting stability failures appears to be common.

Why it arises?

• Feel embarrassed after making a mistake • Admission of error – harmful• Covering up- Why admit when nobody is watching• This is not related to training or understanding a particular

technical or quality concept but mainly related to honesty and ethical issues. Further what is more disturbing is that senior management and company owners appear to either support such practices covertly or overtly and in many instances encourage them.

Why is so hard for the companies to get it right?

Root causesPerformance and business

pressure

Lack of awareness

or capabilities

Inadequate process and technology

Regulatory Perspective

• For authorities the integrity of data is an essential quality attribute in the manufacture of pharmaceutical products. After some serious deviations international authorities have moved the topic into the centre of their interest. In particular the US FDA issued serious violations in Warning Letters to the companies concerned.• Data integrity issues pose such a high risk and are not

always easily detectable. As electronic data recording and management systems are implemented instead of paper systems, the detectability of data manipulation becomes more complex.

FDA and other health authority agencies have recently expanded efforts to target

manufacturers and laboratories with potentially questionable data. A MHRA

guidance places the responsibility on senior management to ensure systems and

procedures are implemented utilizing the principles in ICH Q9, Quality Risk

Management to minimize the potential risk to data integrity.

Data integrity

directives

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Change in Regulatory Focus

• The integrity of the data collected and recorded by pharmaceutical manufacturers is critical to ensuring that high quality and safe medicines are produced. • International Regulatory focus has shifted to DI issues and

between 2010 & 2013 US FDA, WHO & UK MHRA inspectors have undergone training to better detect signs of data problems. • Regulatory authorities are looking more closely at international

facilities for signs of altered and doctored records.

Impact of absence of data integrityIn many cases, Pharma Companies have been impacted by: • Consent Decrees • FDA Warning Letters • EU statements of non-compliance (SNC), • Importation Ban(s) • Loss of consumer confidence • Product applications review suspended • Market & share price reduction.

-DI Issue (case)• The inspector and the authority criticised multiple aspects with regard to "failure to

prevent unauthorized access or change to data and to provide controls preventing data omissions“ to the API manufacturer VUAB Pharma.

• The inspector revealed the firm did not properly maintain a back-up of HPLC chromatograms that form the basis of the product release decisions. The inspector revealed as well discrepancies between the printed chromatograms and the OQ protocol for the HPLC system, which is intended to demonstrate correct operation of the system (e.g. injection sequences and values to calculate relative standard deviation‘

• 'The quality unit was unable to retrieve the original electronic raw data because back-up discs were unreadable. The quality unit stated that back-up discs have been unreadable since at least 2013'

• 'The inspector criticised that the firm does not have proper controls in place to prevent unauthorized manipulation of labs raw electronic data. The HPLC systems did not have access controls to prevent alteration or deletion of data. The HPLC software lacked an audit trail recording any changes to the data, including: previous entries, who made changes, and when changes were made'

Case continue..

• 'The laboratory employees shared a common log-in and password to access the system'

• 'The firm failed to review historical data to ensure the quality of the products distributed to the US market'

• In response to this list of deficiencies the FDA now expects the affected company to provide a comprehensive corrective action plan to the following points within 15 working days:

1. 'Information regarding changes in the reliability of the IT infrastructure, including improved IT systems, systems  validation, revised  procedures and retraining of employees' 

2. 'Procedures regarding passwords used to access the analytical instruments. All access levels for  computerised systems should be clearly defined and documented in a written procedure'

3. 'A detailed summary of the steps  taken to train the personnel on the proper use of computerised  systems'

Inspection Focus

• Company understanding of computerised system capabilities and transfer of data between systems

• Up to date listing of all relevant systems and GMP functionality

• Control of networked & standalone instruments

• Policies and procedures detailing processing and control of data

Inspection focus - data

• Data processing and review

• Accuracy checks

• Potential for data manipulation and deletion

• Repeat testing / replicate data

• Date / time stamp manipulation

• Criteria used to invalidate data

• Data transfer to systems - Checks that data are not altered in value and/or meaning (primary and meta data). Level of checking should be statistically sound.

Application Integrity Policy (AIP)• The Application Integrity Policy is what FDA pulls

up when it has questions about a manufacturer’s electronic data. • Electronic information includes everything, such as

emails, adverse events reports, complaints, batch records, and quality control records—everything that’s stored electronically.

Breach of DI• Breach of Data Integrity is , a violation of the integrity of Data.

Which means, the actions performed and the documents/records written do not reflect the truth and the reality which has taken place. • It is not about Lab Data alone “Data Integrity is not only about

the QC, it applies to compliance with GMPs: Relates to: • - Research & Development • - Clinical Trials • - Manufacturing & Testing • - Inspection • - Post Inspection Activities

US FDA Surprise Inspections …

• Until now, FDA’s inspections of Indian pharma plants have always been with prior notice. • The surprise checks and aggressive surveillance are being considered because of “instances of fabrication of documents and human errors”.• India’s growing importance as a hub of Generic producers and rising compliance problems prompt regulator to consider the plan• FDA expanded its inspection team in India from 12 to 19.

Ensuring Data Integrity• Records should be created contemporaneously• Retained, reliable• Changes should be noted, reasoned and non repudiated• Computer system should be trust-worthy• -validated to intended use.• No resultant decrease in product quality, process control or

product assurance• Evidence should be available to prove the above

Ensuring DI

Ensuring data integrity in regulated labs.

CGMP21 CFR PART 211

GALPEPA DIRECTIVE

2185

GLP21 CFR PART

58

GAMP5 (ISPE) GUIDE

GCP21 CFR PART 312 SUBPART

D

So what can be done to prevent data integrity problems?

• • Encourage Co. to establish a “Data Integrity policy” to show that you are serious about falsification of data and that it is a cause for termination. Train on this policy.• • Establish a general standard for GDP so that even the most innocent

recording issues cannot be perceived as fraudulent. Train on this standard.• • Establish a specific procedure on sampling/testing requirements and

laboratory data recording to be clear about incoming, in process, and final testing requirements. Train on these procedures.• • Provide specific training for secondary reviewers/approvers to ensure GDP are

followed and suspicious results and trends are investigated.• • The QCU must be able to demonstrate that it has established and trained on

policies and procedures that are designed to take data integrity seriously.

Other primary solutions to DI Issue

• Put errors to good use • Share with others • Analyse and find Root Cause • Correct errors through QMS • Anticipate that errors will be made in the learning

process • Risk acceptance: It needs to be understood that errors

may occur

REFERENCES:• http://www.pharmamanufacturing.com/articles/2011/087/• http://www.drugregulations.org • http://www.gmpregulations.dataintegrityissues.com• http://www.gmp-compliance.org/enews_04898_FDA-Warning-

Letter-on-Data-Integrity.html

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INTEGRITY IS DOING THE RIGHT THING EVEN WHEN NO ONE IS WATCHING!

- C.S. LEWIS

THANKYOU!!