Data integrity challenges and solutions

Nandkumar Chodankar (Ph D Tech)

CEO

ASOLUTION PHARMACEUTICALS PVT. LTD.

“DATA

INTEGRITY”

The Current

Challenge

&

Solution

Data IntegrityData integrity refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle in compliance with its applicable regulatory requirements.

It is a critical aspect to the design, implementation and usage of any system which stores, processes, or retrieves data.

Data Integrity Froud: Alteration, Fabrication, Misrepresenation, Omission

Jan. 9, 20152Dr. Nandkumar Chodankar

Importance of Data

IntegrityPATIENT SAFETY

COMPLIANCE:

To ensure that the drug is not adulterated

as per 21 CFR

Failure to comply with any of the

proceeding regulations deems the drug

to be adulterated

Data should be unbiasedJan. 9, 20153Dr. Nandkumar Chodankar

Application Submitted- Accurate &

reliable

All records & Supporting documents are

accurate and true representation of

Actual tests performed & the actual test results

Quality control steps for Development & Manufacture of submission & regular batches

Any other action & conditions associated with application

Data Submission &

Application Integrity - 1


Data Submission &


Data and application integrity also

means the absence of a pattern of

unexplainable discrepancies between

data in records submitted to the FDA and

data in the original records maintained

by the applicant.


Data Submission &


UNRELIABLE:

Omission of significant data from

submission that is determined to

be material to the review process.

Data that is not submitted, but

should have been submitted.


Data Submission &


INACCURATE –

Examples:

First data that failed specs,

Retest data passes specs,

Lab investigations are inadequate or

non-existent, but retest data is

submitted to the application


Data Integrity

Data should be Generated as per

cGMP (21 CFR Requirements)

1. Reliable

2. Trustworthy

3. Traceable

4. Verifiable

5. Complete

6. Legible

7. Meaningful

&

9. Protected


DATA LIFE

CYCLE

1.

Collection2.

Processing

4.

Reporting

3.

Reviewing


Basic Questions

Who, When, What, How? 1. Collection: Who Collects the data? When the

data is Collected? What data is Collected? How data is Collected?

2. Processing: Who Processes the data? When data is Processed? What data is Processed? How data is Processed?

3. Reviewing: Who Reviews the data? When the data is Reviewed? What data is Reviewed? How data is Reviewed?

4. Reporting: Who Reports the data? When the data is Reported? What data is Reported? How data is Reported?


A Attributable Who performed the action & when? Record change, who did it and why?

Who performed?Source Data

L Legible Data must be recorded permanently in

durable medium & be readable Can you read it?

Permanent record

C Contemporan

eous

Data should be recorded at the time

work performanceWas it done in real

time?

O Original Is the information an original record or

certified true copy?Is it original or true

copy?

A Accurate No error or editing performed without

documented amendmentsIs it accurate?

Complete All data including repeat or reanalysis

performed on the sample21 CFR 211.194

Consistent Consistent application on data time

stamps in expected sequenceData/Time stamps

Enduring Recorded on controlled worksheets,

Laboratory Notebooks or mediaMedium used to

record data

Available Available /accessible for review /audit

for lifetime of the recordFor the life time of

the record

DATA - ALCOA


Fraud

Triangle

I need to

meet my

monthly

targets

Everyone

is doing it

Nobody

Really

Checks

Incentives

&

Pressures

Opportunity Attitude &

Rationalism

DATA FRAUD


What can Management do?

1. Showing transparency, accountability,

and responsibility

2. Staying involved

3. Set realistic expectations

4. Praising / Reprimanding (criticism)

5. Develop Team spirit

Continued-



6. Have regular training, Audit and

Supervision

7. Routinely investigate all incidences,

deviations and Changes

8. Review oversight practices

9. Encourage feed back mechanism

without fear of consequences

Continued-



10. Regular QA and QC data Review

11. Internal DI Audits of every department

12. Escalation & Governance

13. Technical Procedural control

14. Validation of every system

15. Risk assessment of all systems as well

operations

Continued-Jan. 9, 201515Dr. Nandkumar Chodankar


16. Quality Manual – Culture and Policies

17. Trainer’s Qualification, refresher

training, evaluation

18. Security Management

19. Recruitment Policies and procedures

– Integrity check


What can Staff do?

1. From lowest to the highest they see it

all and thus can act

2. Everyone is Responsible, Reliable,

Confident

3. Routinely report their findings

4. Everyone considers that Quality

Assurance “as essential function” and

not as an added burden

Continued-Jan. 9, 201517Dr. Nandkumar Chodankar

What can Staff do?

5. Everyone should Respect quality and

should be proactive

6. Responsive to policies and procedures

7. Should report finding without fear of

consequences

8. Should be proud to represent quality

culture


Culture of ComplianceManagement Must

Establish culture from Top to Down

Convey a commitment to compliance

Actively work with and support quality

Establish and demonstrate clear policies on

cGMP and data integrity

Establish control

Intolerant to non-compliance

Understanding

TRUST once Broken is difficult to rebuild


Create Compliance Culture

Recruitment

Built into interview guide

Job profile

Performance

Management System

Management Priorities

Reward &

Recognition System

Succession

Management

Successful Profile

People

Development tools

and measures

Communication

Quality Principles, Quality

Briefings, News Letter

Internal Website

Quality Integrity

Sustainability SOPs


How to avoid Data Integrity

Problems1. Regular QA & QC Review

2. Internal Audit system along with

supervision

3. Escalation and Governance system

4. Technical Procedure Controls

5. Validation

6. Risk Assessment


7. Quality Manual with Management

Culture, Data Integrity Policies

8. Training, Trainers Qualification &

attitude, Effectiveness & evaluation,

refresher courses, etc.

9. Starts with “Small problems” which are

not given importance and they grow

into major problems


Problems


10. Obtaining valuable peace of

information from the staff - Why he /

she has manipulated or falsified ?

11. The inability to detect and prevent

data integrity breaches the trust

12. Detection of emerging trend is

important

13. Institutionalize, reinforce & reward

vigilant culture.


Problems


REMEMBER

21 CFR –Data Control SystemValidation

Change control and revisions

Protection of records

Access limitation

Audit Trail

Control of sequence

Source of data input

Prevent unauthorized use of passwordJan. 9, 201524Dr. Nandkumar Chodankar

OATH

I am a HONEST person with

HIGHEST INTEGRITY.

I have positive attitude and integrity.

I want to improve continuously.

You are not expected to be Perfect but certainly expected to be Honest.

You may make a mistake but hiding it is a crime.


THANK YOU

Nandkumar Chodankar (Ph D Tech)

[email protected] Or

[email protected]

mailto:[email protected]

mailto:[email protected]

Health & Medicine

Data integrity challenges and solutions