16 FEB 2016 ASQ St. Louis Dinner Meeting at Favazza


Sandy Hatten, Senior Vice President of Quality and Regulatory Affairs at Flamel Technologies.

Sandy Hatten: The History of Quality or How “Quality” has Changed

Sandy Hatten has worked in the pharmaceutical industry for 35 years, primarily in Quality and Regulatory leadership roles.   She is currently the Senior Vice President of Quality and Regulatory Affairs with Flamel Technologies, a specialty pharmaceutical company with offices in the US and Europe.   In her role with Flamel, she has responsibility for all Flamel Quality and Regulatory Affairs functions in France, Ireland and the US.  Prior to joining Flamel, Sandy served as Senior Vice President of Quality with Mallinckrodt Pharmaceuticals.   In that role, she was responsible for all Global Quality functions, which included 12 manufacturing plants (US, Canada, The Netherlands, and Ireland) in addition to all corporate Quality functions.  Prior to joining Mallinckrodt, Sandy held Quality leadership positions with KV Pharmaceuticals, Cardinal Health, Perrigo, Bausch&Lomb, and Watson Pharmaceuticals (now Actavis).

During her 35 years in the pharmaceutical industry, she has had the opportunity to work with brand as well as generic companies.  She also worked as a consultant for several years and in that role provided Quality and Regulatory advice and support to a variety of companies, both large and small.    Her background includes, in addition to QA/QC and Regulatory, experience in Clinical Operations, R&D, Commercial Operations and Supply Chain.


Steven Lembark

Steven Lembark, principal consultant with Workhorse Computing.

Steven Lembark: Using Non-Parametric Statistical Analysis

Real data is often messy. Non-parametric statistical analysis offers a variety of ways to analyze the data that really happens. This talk provides a brief introduction to non-parametrics with examples from safety and QA analysis.

What is Non-parametric statistical analysis?

It’s statistics that is not based on parameterized probability distributions, instead parameters are determined by the training data, not the model. Nonparametric statistics make no assumptions about the probability distributions of the variables being assessed. The difference between parametric models and non-parametric models is that the former has a fixed number of parameters, while the latter grows the number of parameters with the amount of training data.

He has ver 30 years experience installing, managing, supporting, and programming systems from CAD/CAM to data warehouses on platforms from VMS to Solaris and Linux. He has worked on startup and refactoring projects in aerospace, telecom, financial, health-care, bioinformatics, web services, and manufacturing.

ASQ St. Louis Section Monthly Dinner Meeting

Tuesday, Feb 16, 2016
05:30 PM – 09:00 PM Central


Favazza St. Louis

5201 Southwest Avenue
St Louis, MO 63139

ASQ St. Louis Feb 2014

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