Stage 2 Planning and the Progression to Stage 3 at the PV Statistician Forum
By Tara Scherder, Managing Director, Arlenda Inc., USA
For instance, there are multiple ways to answer questions such as, “Is the process for commercial manufacture,” and “how will I monitor the process going forward?” at the end of Stage 2. The upcoming ISPE Statistician Forum on 14 – 15 April 2015, in Silver Spring, MD, will continue the dialogue statistical and risk-based approaches.
During the forum, you will hear several approaches to make the transition from Stage 2, Process Performance Qualification, to Stage 3, Continued Process Verification. In the session, “Stage 2 Planning and Progression to Stage 3 Utilizing Bayesian Statistics,” Katherine Giacoletti of Arlenda, Inc., will present an example where a Bayesian approach resulted in significantly smaller sample sizes and narrower intervals than achievable with other methods. You will learn how this is possible and also how this approach can intuitively answer the ultimate Stage 2 question, “what is the probability of success?”
Matthew Howard, RPh, PhD, of Johnson & Johnson will then describe a risk-based, knowledge driven approach to Stage 3 planning in his session, “A Pragmatic Approach to Stage 3 Planning for New and Legacy Products.”
In addition to discussing statistical methods in each stage of the PV Lifecycle, you will have the opportunity to participate in discussions with industry colleagues of the current challenges and lessons learned in the implementation of Process Validation Guidance, explain your difficulties with utilizing proposed metrics and hear the latest thinking from regulators, including:
- Karthik Iyer, Senior Policy Analyst, FDA/CDER/OMPT/CDER/OC/OMQ
- Grace McNally, Senior Policy Advisor, FDA/CDER/OC
- Daniel Peng, PhD, Sr. Product Quality Reviewer, FDA/CDER/OPQ/OPF
- Alex Viehmann, Operations Research Analyst, FDA/CDER/OMPT/OPS/SRS
For more information on the ISPE Statistician Forum or to register, please visit the conference website.
Tara Scherder, Managing Director, Arlenda Inc. has over 25 years of experience in the chemical and pharmaceutical industries as a statistician, process engineer, and master black belt. She has functioned as both an in-house and external statistical consultant to vaccine, API, and pharmaceutical manufacturing teams across the product lifecycle. Tara has extensive experience in both statistical curricula design and delivery, and is passionate about teaching others the value and application of statistical methods. As a Lean Six Sigma master black belt, she applies additional techniques to process improvement, such as change management and lean principles. Tara’s formal education includes a BS degree in Chemical Engineering from the University of Pittsburgh and a MS degree in Statistics from Carnegie Mellon University. Tara is the Managing Director of Arlenda, Inc. Arlenda partners with clients in the biopharmaceutical industry to leverage applied modeling and statistics to: Reduce Risk, Improve Process Performance and Accelerate Product Development.