Good Documentation Practice (GDP) is a term in the pharmaceutical industry to describe standards by which documents are created and maintained. This practice is important where the FDA and other health authority regulations impose a special recordkeeping burden. In these industries, documentation serves both the scientific and compliance needs, and Good Documentation Practices (GDPs) are the set of activities that enable you to record your data and hand-written entries in a legible, traceable and reproducible manner.
Good Documentation Practices is a course that will provide valuable assistance for the following personnel:
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Authors, reviewers, and auditors of documents within FDA-regulated industries (i.e. pharmaceutical, medical device manufacturers, or biotech)
- Laboratory staff (generating data and maintaining lab notebooks)
- Clinical research associates (monitoring sites and resolving CRF queries)
- Engineering staff (keeping notebooks and executing batch records)
- Quality staff (reviewing raw data, lab notebooks, batch records, etc.)
- Regulatory affairs staff (verifying source materials)
After completing Good Documentation Practices, students will be equipped with a basic understanding of the following:
- what is good documentation practices (GDP)
- how and when to apply GDP
- the various types of documents
- how to complete appropriate documents
- how to correct for errors
- how to comply with FDA guidelines
No prior experience or coursework required.
Students will be assigned 5 homework assignments, and 1 final exam.
Module 1
What are Good Documentation Practices?
Module 2
How and when to apply Good Documentation Practices
Module 3
Document types
- Commitment documents (i.e. new drug applications, new drug master files)
- Directive documents (i.e. specifications, STPs, SOPs, MPRs)
- Record documents (i.e. protocols, BPRs, log books, calibration records)
Module 4
Good documentation requirements
- Approval
- Clarity
- Regular review and update
- Formal presentation
- Records
Module 5
How to complete documentation such as data collection forms and batch records
Module 6
How to attach raw data to forms and lab notebooks
Module 7
Commonplace errors
Module 8
How to correct errors and omissions in data entry
Module 9
How to sign, date and label data and records
This course is Instructor-led and delivered through our award-winning online Learning Management System.