Good Documentation Practice (GDP) is a fundamental regulatory requirement for a pharmaceutical industry. Without GDP practice a pharma company can't achieve the product quality consistently.
GDP is the practice of ALCOA+ principles through a product lifecycle.
These principles require that documentation has the characteristics of being attributable, legible, contemporaneously recorded, original and accurate (sometimes referred to as ALCOA). These essential characteristics apply equally for both paper and electronic records.
Good Documentation Practices Examples
- Enter the original information in correct form
- Use blue ink for writing any data/record
- All record should be clear, legible and indelible
- Do not use any fade paper
- Do not use corrective fluid
- Always sign with date
Common GDP Error
- Missing signature and dates at the time of activity performed
- Different date format
- The write-over
- Non-uniform date and signature entry
- Writing a note that activity was performed on one day and signed for on other day
- Blank spaces
- Illegible writing
- Too many corrections
Benefits of GDP
- Create structures so that staff can systematically coordinate to conduct business
- Always meet the customers and stakeholders’ requirements in same manner
- Build confidence in the company Quality System
- Easy to review and investigate
- Ensure all documents are in a clear manner with data that is reliable and accurate
As per WHO Guidelines,
Personnel should follow GDP/GDocP for both paper records and electronic records in order to assure data integrity.
Related: Good Documentation Practice in Commissioning and Qualification
Types of documents require following Good Documentation Practices
- Laboratory Notebooks
- Logbooks
- Analytical Methods
- Batch Records
- Bills of Materials (BOMs)
- Certificate of Analyses (CoA)
- Certificate of Compliance (CoC)
- Protocols
- CAPAs
- Change control
- Standard Operating Procedures
- Test Methods
- Training Documentation
- Validation Documents (IQs, OQs and PQs)
- Product and Sample Labels etc.
Read also: Data Integrity by Design
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