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Statistical Methods Across the Product/ Process Lifecycle
Statistical Methods Across the Product/ Process Lifecycle

Course Description

The use of statistical methods across the product lifecycle has steadily increased since the adoption of ICH Q8 and publication of regulatory guidance’s for lifecycle process validation. This increase does not simply meet regulatory expectation; these methods are good business practice no matter what the product. In this 3 day course participants will learn the typical sampling and statistical methods to use across the product lifecycle to: identify optimal operating regions and inform the control strategy (enable QbD), determine acceptance criteria, demonstrate the process is capable of reproducible commercial manufacture, provide evidence of ongoing process control and respond proactively to process changes.
  • Integrating data analytics to accelerate development, improve processes and reduce risk
  • Ensure Quality by Design and Optimal Control Strategy
  • Sampling and Acceptance Criteria
  • Establishing comparability with equivalence testing
  • Identifying Relative contribution of sources of variability
  • Data visualization
  • Ensuring ongoing quality
  • The most common and powerful statistical methods and their primary sue across the product lifecycle
  • The relationship of statistical methods and Quality Risk Management (QRM)
  • Key reasons to use Deign of Experiments (DOE) for process development
  • Modelling populations to assure quality
  • Difference between hypothesis testing and equivalence testing for comparability
  • Understanding the components of a sampling plan and associated acceptance criteria for Process Validation batches
  • Distinguish between intra- and inter- batch variability and methods to assess each
  • Elements and nuances of an Ongoing Process Verification (OPV) Program
  • Combination of root cause analysis with data visualization to speed root cause identification

Statistical Methods Across the Product/ Process Lifecycle

19 - 21 June 2023, Live Online Training
Regular price €1.850,00
Unit price
per 
Tara Scherder

Tara Scherder has over 20 years’ experience in the pharmaceutical and biopharmaceutical industries as a statistician, engineer, and master black belt. Her passion is the powerful combination of science and statistics to increase knowledge, optimize both manufacturing and business processes, and reduce risk.

Training dates will be announced soon. In meantime, feel free to request an agenda.

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Course Description

The use of statistical methods across the product lifecycle has steadily increased since the adoption of ICH Q8 and publication of regulatory guidance’s for lifecycle process validation. This increase does not simply meet regulatory expectation; these methods are good business practice no matter what the product. In this 3 day course participants will learn the typical sampling and statistical methods to use across the product lifecycle to: identify optimal operating regions and inform the control strategy (enable QbD), determine acceptance criteria, demonstrate the process is capable of reproducible commercial manufacture, provide evidence of ongoing process control and respond proactively to process changes.
  • Integrating data analytics to accelerate development, improve processes and reduce risk
  • Ensure Quality by Design and Optimal Control Strategy
  • Sampling and Acceptance Criteria
  • Establishing comparability with equivalence testing
  • Identifying Relative contribution of sources of variability
  • Data visualization
  • Ensuring ongoing quality
  • The most common and powerful statistical methods and their primary sue across the product lifecycle
  • The relationship of statistical methods and Quality Risk Management (QRM)
  • Key reasons to use Deign of Experiments (DOE) for process development
  • Modelling populations to assure quality
  • Difference between hypothesis testing and equivalence testing for comparability
  • Understanding the components of a sampling plan and associated acceptance criteria for Process Validation batches
  • Distinguish between intra- and inter- batch variability and methods to assess each
  • Elements and nuances of an Ongoing Process Verification (OPV) Program
  • Combination of root cause analysis with data visualization to speed root cause identification

"Trainer is very competent and has the complete knowledge of the matter."

– Senior Process Expert, B. Braun

"It is not at all frequent to find this grade of preparation and reaction to specific cases such as the ones presented. I'm enthusiastic! Thanks really."

– Tech Transfer Lead, Novartis

"Thank you for sharing all the links and informative material. Very professional organization and execution."

– Manufacturing Manager, Thermo Fisher Scientific

"The trainer was very knowledgeable about the topics and was able to answer all questions."

– Drug Product Subject Matter Expert, Pfizer

"Excellent work of the lecturer, good materials, clear explanations."

– Clinical Pharmacologist, Boehringer Ingelheim

Statistical Methods Across the Product/ Process Lifecycle

Download the full training agenda to reveal complete session details, training takeaways, case studies, daily schedule, special features and full trainer bio.

Medical-Devices-Certificate-Course

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