Understanding Variation and the Metrics of Process Monitoring

Bethesda, MD
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Duration: 2 days
Time: 8:30 a.m. - 4:00 p.m.

There has been an increasing awareness of the importance of statistical process monitoring within the pharmaceutical and biopharmaceutical industries. Statistical methods provide objective evidence in meeting goals of compliance and performance, and are fundamental for understanding the process.

Within, between and total variation are not only the key to compliance with the 2011 Process Validation Guidance and multiple ICH documents but also the foundation of everything from alpha risk to beta risk to confidence, coverage, and control charts...to Z-tables.

As statistics is the "Science of Variation", this two day course presents basic concepts within a cGMP framework using the analytical and manufacturing tools of our environment. This applied course examines specific ideas and approaches necessary to carry out basic statistical analysis for evaluation of process capability during validation and ties it to lot release, process monitoring, as well as the leading indicator of everything from recalls to the likelihood of an audit under FDASIA 705 - the probability of OOS.

Hands-on experience using a syringe filler will generate data to measure, quantify and compare sources of variation. This course will provide guidance to help attendees identify and use statistical process monitoring methods to calibrate, validate, maintain and troubleshoot. The course will convey the appropriate use of statistical methods at a level and in a way that will be easily understood. The various methods will be described, typical applications will be identified, and pros and cons of each method will be examined. Examples of each method will also be described to show how they can be used in a real-world setting.

This course will utilize PDA Technical Report No. 59, Utilization of Statistical Methods for Production Monitoring as a resource. Attendees will each receive a complimentary copy of this technical report.

Who Should Attend

Persons involved in the following functions and disciplines will find this course of value: manufacturing engineering, process engineering, process improvement, process validation, project analysis, quality assurance, quality control, quality systems, and risk assessment.

Event Location
PDA Training and Research Institute
4350 East West Highway, Bethesda, MD Get Directions

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Day 1

Upon completion of this course, you will be able to:

  • Cite the regulatory references relevant to understanding, controlling and reducing process variation
  • Cite the regulatory references linking variation and process validation
  • Calculate within, between and total variation
  • Apply the different types of variation to validate, monitor and improve a pharmaceutical manufacturing process
  • Evaluate various statistical tools for their appropriate use
  • Calculate the probability of OOS within a single lot and series of lots for reporting under FDASIA 705 & 706 to comply with the Agency's request for metrics
  • Differentiate between the regulatory implications of compliance to specifications and the business realities of performance against specifications

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PDA Training and Research Institute

4350 East West Highway
Bethesda, MD ,

Jason Orloff, Principal Statistical Consultant, PharmStat
Jason J. Orloff, Ch.E. & M.S. Applied Statistics, is a Principal Statistical Consultant at PharmStat and a proud colleague of Lynn Torbeck. He is an international consultant specializing in applied statistics and experimental design for pharmaceutical and biopharmaceutical development, quality assurance, quality control, validation and production under the cGXP's. Current activities include an author of ISPE's Baseline Guide for Q10 chapter "Process Performance and Product Quality Monitoring", contributing authorship of PDA Technical Report No. 59, Utilization of Statistical Methods for Production Monitoring, DoE trainer at CBER, and publications in the Journal of Pharmaceutical Technology.

Mr. Orloff brings over fifteen years of experience in manufacturing, quality, and regulatory affairs in the pharmaceutical industry. Areas of expertise include PAT, OOS, SQC, SPC, assay validation and setting specification criteria. A chemical engineer with real-life expertise at applying statistics in a highly regulated environment, Mr. Orloff is able to work effectively across all levels of an organization as well as make high level concepts accessible to a variety of audiences. He has worked with a wide variety of companies including pharmaceuticals, parenterals, biotechnology, fine chemicals, medical devices, food and nanotechnology. He holds a B.S. in Chemical Engineering from UW-Madison and a M.S. in Applied Statistics from DePaul University.