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This course focuses on one of the most significant and at the same time overlooked aspects of cleaning validation: recovery. During the course we shall discuss about the main design aspects of a recovery study by following a practical approach.
A case study will be presented including a recovery study with the participation of three analysts, of different experience level in recovery studies. We will present a methodology based on the simple linear regression model and we will show how it can be applied to create a simple linear model per analyst. In addition, we shall demonstrate how the analysts can be assessed in terms of their qualification for participating in sampling. Finally, we will demonstrate how the attendees can utilize the template in order to estimate residues on equipment at the end of cleaning operations.
The methodology will be demonstrated in python, a free development software via a template with step by step instructions for the user. Instructions shall be provided to the users not familiar with python and the template will be made available to attendees at the end of the course. We will demonstrate how the attendees can import their results in a “ready-to-use” python template in order to create a simple linear model which shall describe the recovery results.
Note that the methodology that will be presented can be used by practicioners in any type of statistical software (Excel, Minitab, R).
This course has been designed for entry-level as well as experienced professionals in cleaning validation and recovery.
#5827
This course is available as an In-House Training course. Let us know if you wish to customize a course or if you are a large group with the same requirements.
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