Design Of Experiments: Building Design Space
Date : 11 February 2019
Time : 01 : 00 PM EST
Duration : 90 Minutes

Emil W. Ciurczak has over 45 years’ experience in the pharmaceutical industry, performing method development. He has worked on pre-formulation studies, pilot plant scale-up, as well as final product and stability indicating assay development.

In 1983, he introduced NIR spectroscopy to Pharma applications, primarily for (EMA mandated) raw materials qualification. He was the first to report on polymorphism, optical isomer purity, blend uniformity, and particle size measured by NIR, with more than a dozen patents. He has consulted for several NIR instrument companies, has published over 100 articles in refereed journals, written over 350 magazine columns, and presented nearly 300 technical papers.

He is Contributing Editor for Pharmaceutical Manufacturing and Contract Pharma magazines, has written several texts and chapters on NIR applications to life sciences: “Handbook of NIR Analysis” (1st, 2nd, 3rd, and 4th editions), “Pharmaceutical and Medical Applications of NIRS”, “Molecular Spectroscopy Workbench.”

Emil consults with pharmaceutical companies, instrument manufacturers, and the FDA (PAT sub-committee, Validation), and works with the USP spectroscopy group. He has advanced degrees from Rutgers and Seton Hall Universities and taught college and short courses since 1980.

The course will cover how the new concept of Design of Experiments (DoE) is different from the approach taught in school, years ago. We now use multivariate designs to find “Design Space,” what good is it, and how to best determine it through DoE

Some approaches will be variation on selecting statistically significant (representative) samples instead of all combinations, saving time and money. A number of examples of commercial software will be shown and how to determine which parameters should be tested. (The concept of risk analysis will be shown as the key to determining what and where to test.)

Some thoughts on Data Mining, when it is useful and when not will be discussed. As will the difference between “data” and “information”. Some instrumentation suited to PAT/QbD testing of processes will also be discussed with brief application examples.

With the growth of PAT/QbD, the need to understand and perform DoE has become imperative. DoE is based on the ICH and FDA Guidances and Risk Management.

Areas Covered

  • Definition of DoE
  • How to “populate” the design (choosing parameters to test)
  • Definition and construction of Design Space

Course Level - Basic through intermediate

Who Should Attend

  • R&D Director
  • Director of Production
  • AR&D Manager/supervisor/analyst

Why Should Attend

In order to implement a successful PAT/QbD program, the need to perform modern, the multivariate design of experiments. The cost of producing quality products by traditional batch methodology is rising, but competition from multiple sources is cutting profits. Further pressure from governments to reduce prices is also squeezing profitability.

The clearest path to both profitability and quality products is QbD (and eventually, continuous manufacturing). But to control the process, the process needs to be understood to be controlled. The control comes knowing allowable parameters in production; gleaned from DoE.

  • $179.00