This one day in-house course is aimed at scientists, engineers and technical managers in the pharamceutical industry. The course will provide the background to allow attendees to better appreciate what their colleagues, the FDA, and presenters at conferences are discussing regarding multivariate methods.
This 1-day course is intended for the pharmaceutical industry to raise awareness about using data and multivariate methods.
Objective
This course is an in-house course. It is intended for the pharmaceutical industry so that staff become aware of what their colleagues, the FDA, and presenters at conferences are talking about when discussing data, multivariate methods, and the Process and Analytical Technology, PAT initiative.
Course outline
A typical course outline is provided below. The course is run over a half-day up to a full day, depending on your company's requirements. The outline given here is for a full-day course.
| Objectives |
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| About the PAT initiative |
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| Basic principles of multivariate data analysis (MVDA) | |
| What can MVDA achieve? | |
| Areas where MVDA should be applied | |
| Overview of the two main multivariate methods |
|
| Principal Component Analysis (PCA) |
|
| Projection to Latent Structures (PLS) |
|
| Design spaces for raw materials |
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| Pharmaceutical example |
|
| Process monitoring (SPC) |
|
| Basic concepts |
|
| Pharmaceutical example |
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| Analysis of manufacturing data |
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| Using data to better understand and improve processes |
|
| Batch data analysis |
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| Control of batch processes |
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| Endpoint detection example 1 |
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| Endpoint detection example 2 |
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| Product design |
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| Pharmaceutical example |
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| Product scale-up and product transfer between sites |
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| Overview of the technology |
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| Multivariate design of experiments |
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| Application to drug formulation |
