This document from the United States Army Medical Research Institute of Chemical Defense provides guidance on Good Documentation Practices (GDP) for ensuring reliable, consistent documentation in research. It outlines specifics of GDP such as making legible data entries immediately, using indelible ink and explaining abbreviations. It also describes how to properly make and document corrections to records as well as how to maintain accuracy, clarity and traceability. Examples of bad documentation practices that should be avoided are given at the end.
This presentation is contain information about Documentation System of Pharmaceuticals. This presentation is prepared for training on documentation in Drug International Limited (Herbal Division) Depending on WHO and ICH guideline.
Good documentation practice (commonly abbreviated GDP, recommended to abbreviate as GDocP to distinguish from "good distribution practice" also abbreviated GDP) is a term in the pharmaceutical industry to describe standards by which documents are created and maintained. While some GDocP standards are codified by various competent authorities, others are not but are considered cGMP (with emphasis on the "c", or "current"). Some competent authorities release or adopt guidelines, and they may include non-codified GDocP expectations. While authorities will inspect against these guidelines and cGMP expectations in addition to the legal requirements and make comments or observations if departures are seen. In the past years, the application of GDocP is also expanding to cosmetic industry, excipient and ingredient manufacturers.
In Pharma and Biotech, Weightage of the Documentation is around 70 % because as per FDA "If you do not have Document, You dint have do it."
So Good Documentation Practice is of tremendous importance for the Industry to comply any regulation like FDA, GMP or ISO.
This slide is related to Good documentation Practice in Pharmaceutical Industries. It was presented in the pharmaceutical industry (Chemidrug Industry Private Ltd.) during the training session.
This presentation is contain information about Documentation System of Pharmaceuticals. This presentation is prepared for training on documentation in Drug International Limited (Herbal Division) Depending on WHO and ICH guideline.
Good documentation practice (commonly abbreviated GDP, recommended to abbreviate as GDocP to distinguish from "good distribution practice" also abbreviated GDP) is a term in the pharmaceutical industry to describe standards by which documents are created and maintained. While some GDocP standards are codified by various competent authorities, others are not but are considered cGMP (with emphasis on the "c", or "current"). Some competent authorities release or adopt guidelines, and they may include non-codified GDocP expectations. While authorities will inspect against these guidelines and cGMP expectations in addition to the legal requirements and make comments or observations if departures are seen. In the past years, the application of GDocP is also expanding to cosmetic industry, excipient and ingredient manufacturers.
In Pharma and Biotech, Weightage of the Documentation is around 70 % because as per FDA "If you do not have Document, You dint have do it."
So Good Documentation Practice is of tremendous importance for the Industry to comply any regulation like FDA, GMP or ISO.
This slide is related to Good documentation Practice in Pharmaceutical Industries. It was presented in the pharmaceutical industry (Chemidrug Industry Private Ltd.) during the training session.
ENSURING DATA INTEGRTY THROUGH "ALCOA" : BASIC DATA INTEGRITY PRINCIPLES APPL...Abhijeet Waghare
Data Integrity refers to the completeness, consistency and accuracy of the data. Complete, consistent and accurate data should be attributable, legible, contemporaneously recorded, original or true copy and accurate across. The acronym ALCOA has been around since the 1990’s, is used by regulated industries as a framework for ensuring data integrity, and is a key to Good Documentation Practice (GDP).
Good Documentation Practice (GDocP) is an essential part of the quality assurance and such, related to all aspects of GMP” this definition is based on WHO. It is a systematic procedure of preparation, reviewing, approving, issuing, recording, storing and archival of document.
Good Documentation Practice (GDocP — or GRK for Good Recordkeeping) is an essential component of your overall pharmaceutical quality system (PQS) and quality risk management strategies (QRM).
new guidance on good data management was discussed and its development
recommended. The participants included national inspectors and specialists
in the various agenda topics, as well as staff of the Prequalification Team
(PQT)–Inspections
CCK Discussion Forum held at ICCBS, University of Karachi, attended by over hundred of registered experienced pharmaceutical professionals participants belonging from dozen of pharmaceutical manufacturing facilities
Good documentation practice
Introduction
What types of documents require to follow Good Documentation Practices?
Meaning of signature
Purpose of documentation
Basic requirements of GDP
Preparation of documents
Cancellation of GMP records
reference
• Analytical Methods
• Policies
• Batch Records
• Protocols
• Bills of Materials (BOMs)
• Test Methods
• Certificate of Analyses (CoA)
• Training
Documentation
• Certificate of Compliance (CoC)
• Logbooks
• Laboratory Notebooks
• Calibration records
• Quality records - non-conformances
- CAPAs
- internal inspection reports
- change control
Basic Principle of GDocP, Good Documentation Practices, ALCOA, ALCOA+, MHRA and Eudralex Guidlines, Effective GDocP, Common GDocP errors, Benefits of GDocP, GDocP Improvement, GMP, Pharmaceutical
Trends changed from Non compliance to RR --> Gap to RR --> Data Integrity --> DIB --> Smart Audit & Smart Data.
RR = Regulatory Requirements
DIB = Data Integrity Breach
Take a serious Note for Data Integrity whether you are small or big organization. Your Data is the Heart of your business. Regulatory bodies are highly conscious about such issues. For beginners in this path, my small note can help you a lot.
ENSURING DATA INTEGRTY THROUGH "ALCOA" : BASIC DATA INTEGRITY PRINCIPLES APPL...Abhijeet Waghare
Data Integrity refers to the completeness, consistency and accuracy of the data. Complete, consistent and accurate data should be attributable, legible, contemporaneously recorded, original or true copy and accurate across. The acronym ALCOA has been around since the 1990’s, is used by regulated industries as a framework for ensuring data integrity, and is a key to Good Documentation Practice (GDP).
Good Documentation Practice (GDocP) is an essential part of the quality assurance and such, related to all aspects of GMP” this definition is based on WHO. It is a systematic procedure of preparation, reviewing, approving, issuing, recording, storing and archival of document.
Good Documentation Practice (GDocP — or GRK for Good Recordkeeping) is an essential component of your overall pharmaceutical quality system (PQS) and quality risk management strategies (QRM).
new guidance on good data management was discussed and its development
recommended. The participants included national inspectors and specialists
in the various agenda topics, as well as staff of the Prequalification Team
(PQT)–Inspections
CCK Discussion Forum held at ICCBS, University of Karachi, attended by over hundred of registered experienced pharmaceutical professionals participants belonging from dozen of pharmaceutical manufacturing facilities
Good documentation practice
Introduction
What types of documents require to follow Good Documentation Practices?
Meaning of signature
Purpose of documentation
Basic requirements of GDP
Preparation of documents
Cancellation of GMP records
reference
• Analytical Methods
• Policies
• Batch Records
• Protocols
• Bills of Materials (BOMs)
• Test Methods
• Certificate of Analyses (CoA)
• Training
Documentation
• Certificate of Compliance (CoC)
• Logbooks
• Laboratory Notebooks
• Calibration records
• Quality records - non-conformances
- CAPAs
- internal inspection reports
- change control
Basic Principle of GDocP, Good Documentation Practices, ALCOA, ALCOA+, MHRA and Eudralex Guidlines, Effective GDocP, Common GDocP errors, Benefits of GDocP, GDocP Improvement, GMP, Pharmaceutical
Trends changed from Non compliance to RR --> Gap to RR --> Data Integrity --> DIB --> Smart Audit & Smart Data.
RR = Regulatory Requirements
DIB = Data Integrity Breach
Take a serious Note for Data Integrity whether you are small or big organization. Your Data is the Heart of your business. Regulatory bodies are highly conscious about such issues. For beginners in this path, my small note can help you a lot.
Asia Pesticide Residue Mitigation through the Promotion of Biopesticides and ...apaari
Asia Pesticide Residue Mitigation through the Promotion of Biopesticides and Enhancement of Trade Opportunities (APRMP), Virtual lab meeting
14 August 2020
1)Data integrity refers to the accuracy and consistency (validity) of data over its lifecycle. Compromised data, after all, is of little use to enterprises, not to mention the dangers presented by sensitive data loss. For this reason, maintaining data integrity is a core focus of many enterprise security solutions.
2) The term data integrity refers to the accuracy and consistency of data. When creating databases, attention needs to be given to data integrity and how to maintain it. A good database will enforce data integrity whenever possible. For example, a user could accidentally try to enter a phone number into a date field.
3) The Technopedia.com definition of Data Integrity linked here focuses on three key attributes: completeness, accuracy and consistency.
4) 8 Ways to Ensure Data Integrity
Perform Risk-Based Validation.
Select Appropriate System and Service Providers.
Audit your Audit Trails.
Change Control.
Qualify IT & Validate Systems.
Plan for Business Continuity.
Be Accurate.
Archive Regularly.
5) Maintaining data integrity requires an understanding of the two types of data integrity: physical integrity and logical integrity. Both are collections of processes and methods that enforce data integrity in both hierarchical and relational databases.
6) Data Integrity (DI) in the pharmaceutical manufacturing industry is the state where data are Attributable, Legible, Contemporaneous, Original, Accurate, Complete, Consistent, Enduring, and Available (ALCOA+)
7) Data integrity helps in building trust between regulatory agencies and the industry as a whole. It eliminates the need for inspecting each and every process involved in the production and supply of drugs and other pharmaceutical products.
8) 21 CFR Rules are a set of rules which govern or regulate the management and usage of electronic records in pharmaceuticals and medical devices.
9) Data Integrity is. defined as “the extent to which all data are complete, consistent and accurate, throughout the. data lifecycle” and is fundamental in a pharmaceutical quality system which ensures that. medicines are of the required quality .
10) For example, a user could accidentally try to enter a phone number into a date field. If the system enforces data integrity, it will prevent the user from making these mistakes. Maintaining data integrity means making sure the data remains intact and unchanged throughout its entire life cycle.
Principles of data collection include principles, types, sources, and methods of data collection, which will help medical students to make their tools for data collection.
1. United States Army Medical Research and Materiel Command
United States Army Medical Research Institute of Chemical Defense
GOOD
DOCUMENTATION PRACTICE
Office of Regulated Studies
11 February 2009
USAMRICD
2. What is the purpose of GDP?
• Ensures reliable, consistent transfer of
information
• Fulfills the basic premise that good science is
reproducible
• Helps preclude dishonesty and fraud
• Essential for producing quality results
• Helps maintain:
– Accuracy
– Clarity
– Traceability
USAMRICD
5. Making data entries
• All handmade entries are written in indelible ink,
preferably blue or black
• If it can’t be read, it is not legible
• All data are reported
• Don’t “scrunch” data
– Avoid writing in borders or margins – use
additional paper
USAMRICD
6. Making data entries
• All abbreviations are explained
• Unusual responses noted and reported
• Record what is meaningful; leave off the rest
• Entries are made immediately or as soon as
possible after they occur
The FDA considers “immediately” to mean
“within 24 hours” (Q & A with the FDA, 2003)
USAMRICD
7.
8. Making corrections
• Any changes to GLP records are done in a
manner that does not render the original entry
illegible
• Do not write over a number or letter to correct it
– Do not try to make a 5 into a 6 or a 6 into an 8
The use of pencils, White Out®, Post-It® Notes
or correction tape is unacceptable
USAMRICD
9.
10. Making corrections
• The error maker should be the one to correct
the error
– If that person cannot be found, then
management approval is required for the
correction
• If you’re sloppy, slow down and print
• Don’t recopy data just to make it look “nice”
USAMRICD
11. Making corrections
• Draw a single line through item to be corrected
• Place your initials next to the corrected item
• Add date of correction
• State reason for correction
RE: recording error SE: spelling error
TE: technical error LE: late entry
DE: dosing error WD: wrong date
CE: calculation error TRE: transcription error
MI: malfunctioning instrument
USAMRICD
12.
13. Maintaining accuracy
• Balance values recorded as displayed and
rounded later
• No documentation by exception
• Numbers recorded to the appropriate
significance
• If estimating, so designate
• If multiple measuring devices are employed,
use the significance of the least critical device
USAMRICD
14. Maintaining clarity
• No filling out data sheets at the end of the
day/week/month or “when time allows”
• Don’t leave blank or “white” spaces in forms
and documentation
– Mark through with a line or use “N/A”
– Blank spaces need clarification so no one can
come back and insert data “after the fact”
• Document corrective actions
• Don’t use arrows or “ditto” marks
USAMRICD
15.
16. Maintaining traceability
• Data recorded onto appropriate forms or into
appropriate logs
• Place extraneous observations in notes or on a
supplemental form
• If data is transcribed, so state
– Reference the original source
– Include photocopy of original or source
whenever possible
– Photocopy must be audited and verified
USAMRICD
17. Maintaining traceability
• All data sheets contain protocol # or unique
identifier
• Don’t forget to sign and/or initial and date
where requested
– If data is recorded by a different individual
than the one performing the procedure or task,
identify both persons on the data form(s)
USAMRICD
21. Statistics and calculations
• Describe all calculations and formulas
• Describe statistical methods
– Test them and document such testing
• Distinguish between raw and corrected data
• Rejection or reanalysis of data points
– Accompanied by scientifically valid reasons
– Outlier tests conducted
– Reported but excluded from analysis
• Values averaged or otherwise identified
USAMRICD
22.
23. Computer software
If raw data are collected and manipulated by a
software program, so state
– Explain how the software manipulates data
– Reference software validation records
• The use of computer software in GLP research
comes with its own set of requirements
– The “Electronic Rule,” 21 CFR 11
Don’t allow for assumptions!
USAMRICD
24. Significant figures
• What is a “significant figure”?
• How does one go about deciding which figure
is significant?
• Significant figures in complex calculations and
formulas
• Significant figures in calculators and
spreadsheets
USAMRICD
25.
26. Bad documentation practice
• Entering data results when testing has not been
performed
– Example: “I never see sick animals during
observation periods. I will just write down that
all animals appeared normal.”
USAMRICD
27. Bad documentation practice
• Entering data results which are not reflective of
the actual observation
– Example: “Gee, the body weight is supposed to
be between 120 and 145 grams, but its’ 148
grams. I’ll write 145 grams. That’s close
enough.”
USAMRICD
28. Bad documentation practice
• Signing for work prior to that work being
performed
– Example: “I am going on break at 10 AM and
have an observation check due. So, I will just
write the 10 AM check in on my documentation
now (9:40 AM), and therefore I can still have a
break at 10 AM.”
USAMRICD
29. Bad documentation practice
• Entering a date other than the current date
when documenting completion of a task or
comment
– Example: “Oops, I forgot to write in that date for
the results I took 3 weeks ago. I know I did it,
but just forgot to put the darn date. I will just
backdate it.”
USAMRICD
30. Bad documentation practice
• Destroying original data or voiding original data
without supporting documentation and proper
approval
– Example: “These lab results really look funky.
They can’t be right. I will just get a clean sheet
and start over. No need to keep that original
data.”
USAMRICD
31. Bad documentation practice
• Verifying a step, task, calculation or other entry
without individual observation
– Example: “Gee whiz, Mike left me alone to add
these ingredients to the blender. It calls for him
to verify me doing this. Oh well, I have been
doing this for 3 months and never made a
mistake. I will just initial for Mike. I know it’s
okay.”
USAMRICD
33. Where to go when you have questions
• ICD Intranet
– OrganizationOffice of Regulated
StudiesAnalytical Procedures
– OrganizationOffice of Regulated StudiesGeneral
Laboratory Procedures
– OrganizationOffice of Regulated StudiesQuality
Assurance Procedures
– OrganizationOffice of Regulated StudiesGLP
Forms
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34.
35. Where to go when you have questions
• Office of Regulated Studies, E3100 room 11
– CPT Jennifer Evans, GLP Compliance Officer
Phone: 5-1727; E-mail: jennifer.evans1@us.army.mil
– Connie Clark, Quality Assurance Specialist
Phone: 5-1830; E-mail: connie.clark1@us.army.mil
USAMRICD