Masterarbeit
Assuring data integrity for CMC regulatory submissions using custom digital tools ***
Dr. Bernhard Richard (2023)
Summary
Language: English
The term 'data
integrity' describes the expectation that communicated data for
regulatory submissions are reliable, as they are the basis for manifold
decisions of manufacturers and regulators that may affect pharmaceutical
product quality, safety and efficacy. Potential data integrity breaches
do therefore pose considerable risks for patients and have to be
appropriately addressed by anyone concerned with pharmaceutical
development and manufacturing.
Data integrity has to be maintained
with appropriate measures, such as data integrity checks. Various tasks
in the pharmaceutical industry, for instance in CMC management, do
commonly deal with large and complex data of potentially heterogenous
origin, which increases data integrity risks when data are manually and
repeatedly prepared for regulatory communication. This issue can be
addressed with programmed solutions, employing languages such as R.
In
this work, the validation of R and custom digital (R) tools for data
cleaning and analysis is discussed. The 'Custom R Tool Validation
Framework' is proposed, which allows for assurance of data integrity,
while rendering post-hoc integrity tests obsolete. Specific tools and
templates provided in this work pair up with the Custom R Tool
Validation Framework to jointly provide significant benefits in terms of
maintaining data integrity, documentation and work efficiency. Their
use is demonstrated and the underlying reasoning is discussed, along
with their fit to the Pharmaceutical Quality System and the
international pharmaceutical regulatory environment.
Pages: 95
Appendices: 2, pages: 20