Clinic 1 – “Quality” in GMP for Biologics – 0.5 RU
Clinic 2 – Statistics Made Easy Using Minitab – 0.5 RU
Dinner Presentation – Introduction to Business Process and Queuing Modeling for Everybody – 0.5 RU


When : Tuesday, April 9, 2019 5:15 PM  –  9:00 PM
Where :
Wyndham Hotel Irvine 17941 Von Karman Ave. Irvine, California 92614 USA

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Clinic 1 – “Quality” in GMP for Biologics – 0.5 RU
Mihali Pandya

This presentation will cover a brief introduction to what is Biologics, the manufacturing of Biologics and address the importance of Quality Control and Risk Management for Biologics.

Main takeaways are:
– Each molecule is different and processes for one do not apply to another.
– Costs of failed runs are prohibitive.
– It is difficult to for a new manufacturer to enter the field without collaborating.

Clinic 2 – Statistics Made Easy Using Minitab – 0.5 RU
Ned Schneider

Statistical methods are commonly used to determine if a hypothesis regarding the data is true. One-Way ANOVA is a statistical method used to compare 3 or more means. One-Way ANOVA is equivalent to a multi-level one factor Design of Experiments (DOE). At this clinic, we will perform a One-Way ANOVA test on 3 sets of data using hand calculations and then using Minitab.

By attending this clinic presentation, you will…

• Understand why “Statistics” is considered a Core Competency for Technical Professionals.
• Learn why we can use the F-Test, a test used to compare variances, to compare means.
• Learn how to use the ANOVA formula instead of using the SUM-of-the-Squares Method to determine if the means are statistically significant.
• Learn how to solve the ANOVA example using Minitab and discover some additional features Minitab has to verify method assumptions and to identify which means are statistically different from the other means.
• Hear about an exciting opportunity to take a new awesome Statistics Course Online.

Dinner Presentation – Introduction to Business Process and Queuing Modeling for Everybody – 0.5 RU
Dr. Joe DeSimone

Business process modeling is the act of creating a visual display of your enterprise’s processes. This includes activities and the people or groups responsible for carrying them out. Data generated from the process, and the documents produced are also components. With this information, managers and process owners can identify less-productive areas and develop a plan to improve their performance. Peter Drucker stated that “you can’t manage what you don’t measure.”

The concept of Process Modelling goes back to early Juran, Deming and even during the time of the Japanese Union of Scientists and Engineers (JUSE).  Pioneers like Taiichi Ohno and Shigeo Shingo used BPM to understand and improve their business processes.

There are several types of process modeling tools that can be used to map any workflow with the goal of process improvement. SIPOC Diagrams, IPO Models, Value Steam Maps, Process Flow Diagrams, etc.. Lean simulations are often developed using such tools.

A typical Value Steam Map for instance, would analyze a process for such items as cycle time, change over time, VA Vs. NVA activities etc.…This common approach is often a qualitative approach and assumes that activity times and demand are deterministic, constant and are known with certainty.  If the variability in a certain task or demand for service is small,
the typical analytic tools are fine.   However, in situations with more accentuated variability, these models will not suffice.

In fact, variability is often of utmost importance in improving a process from a productivity standpoint alone.  From a Risk Management standpoint, quantitative methods should be used for critical process analysis and improvement.

In this presentation, Joe will incorporate variability into modelling of a business process.  True Lean and Six Sigma will be melded.  Joe will introduce the concept of an Analytical Queuing Model and demonstrate analysis of both variability and costs.  Joe will model some typical queuing processes and analyze them using this approach. A live simulation and model will be demonstrated using participants from the audience. Finally, strategies for mitigating the effects of long queues will be presented.