Design of Experiments in Biotechnology Analytical Development April 4, 2013

This webinar on optimizing bioassays will help you learn how to use Design of Experiments, then apply the techniques to biotechnology analytical development.

Why Should You Attend:

Within the broad field of biotechnology, there is a constant need to evaluate and optimize assays for all sorts of uses. However, there are a huge number of factors that may impact an assay, and it’s difficult to evaluate them one at a time. In addition, a number of factors may have a clear relationship with each other, and optimizing assays one condition at a time may hide these key relationships. Using Design of Experiments, you can look at a broad number of assay conditions at once, find out the conditions that are key to the assay, then optimize those conditions to whatever specifications you are looking for.
This training will teach you the principles of Design of Experiments, a powerful set of statistical techniques that will allow you to analyze a multitude of factors with a given set of conditions. Then you will be able to learn how to use these statistical techniques to analyze data in order to optimize biotechnology assays, learning the strengths and weaknesses of the technique, and how to optimize assays for a given set of conditions.

Areas Covered in the Webinar:

1. How does Design of Experiments work?
2. How to generate a Design of Experiments model?
3. What kind of factors should be used to generate a model?
4. What is a two-level model, a three-level model and the difference between the two?
5. How to use a two-level model to generate a three-level model?
6. How to input, read and interpret the data generated in a Design of Experiments model?
7. How to use the results from a Design of Experiments model in refining a biotechnology assay?