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This online course consists of six modules as described and illustrated below. For managers and executives we recommend modules 430, 431 and 440 for a big-picture path.
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Course 4 Overview
430: Demystifying modeling (45 mins)
Module: 430
This module aims to introduce you to models and modeling. You will cover questions such as:
- What is a model?
- What is the power of models?
- What pitfalls should you avoid when using models?
- What is the vision of a model-based enterprise?
The learning objectives of this module are that you will be able to:
- Describe some of the drivers for modeling
- Define key performance indicators that can be improved using models
- Explain some of the key pitfalls to avoid when using models
- Describe the vision of a model-based enterprise
431: Digital twins for biomanufacturing (45 mins)
Module: 431
This module aims to introduce you to the concept of digital twins and the different types of digital twins used for biomanufacturing. You will cover questions such as:
- What are the benefits of model-based biomanufacturing?
- What are the 4Ps of modeling for Life Sciences manufacturing?
- What is a digital twin?
- What is the difference between a digital model and a digital twin?
The learning objectives of this module are that you will be able to:
- Explain key examples of the benefits of model-based biomanufacturing
- Describe the 4Ps of biopharmaceutical manufacturing
- Describe what a digital twin is
- Explain the key differences between a digital model and a digital twin
432: Overview of modeling of pharmaceutical processes (45 mins)
Module: 432
This module aims to introduce you in more detail to modeling of pharmaceutical processes. You will cover questions such as:
- How can modeling and simulation support Quality by Design workflows?
- How does Process Analytical Technology (PAT) rely on modeling?
- What are the most common objectives of modeling?
- What are some of the different applications of modeling for biomanufacturing?
- What are the three main types of modeling approaches?
- What do you need to be aware of if your objective changes?
- Which models are most suited to batch or continuous processes?
- What are typical examples of models used in the biopharmaceutical industry?
The learning objectives of this module are that you will be able to:
- Describe different types of models that can be used for different objectives and applications
- Explain how Process Analytical Technology relies on modeling
- List which type of modeling and which models are suited to various stages of product development of manufacturing (e.g. batch or continuous processes)
433: Overview of modeling packages and platforms (30 min)
Module: 433
This module aims to introduce you to some of the packages and platforms used in the Life Sciences industry for model-based biomanufacturing. You will
cover questions such as:
- What are some of the main statistical and modelling packages used to perform data analysis or create models?
The learning objectives of this module are that you will be able to:
- List a number of packages that are used for modeling
- Define the manufacturing stage and context models are most suitable for
434: Introduction to a modeling lifecycle framework (30 mins)
Module: 434
This module aims to introduce you to managing models using a lifecycle framework. You will cover questions such as:
- Why is model life-cycle management so important?
- How are models assessed differently in an industrial context?
- What are the main steps in a model lifecycle framework?
The learning objectives of this module are that you will be able to:
- Explain why lifecycle management of models is important
- Describe the main steps in a model lifecycle framework
- Describe a modeling portfolio management process
440: Investment considerations for model based biomanufacturing (45 mins)
Module: 440
This module aims to introduce you the factors that impact investment in model-based technologies. You will cover questions such as:
- What are the business drivers and economics of model based biomanufacturing?
- What are the technology investment considerations?
- What are the personnel investment considerations?
- What is the future of model-based biomanufacturing?
The learning objectives of this module are that you will be able to:
- State key business drivers for model-based biomanufacturing
- Outline factors relating to technology investment
- Outline personnel investment considerations
- Describe the impact on tech transfers of products
from one site to another - Explain some of the key equations that support data-driven economic decisions
WHAT SOME OF OUR ACADEMIC PARTNERS SAY ABOUT THIS COURSE
“A path to model based manufacturing is a collection of modules that help explain the modeling concepts which are so frequently mentioned in the biomanufacturing industry. This course not only provides context to how these modeling tools can be utilized, but also delves into the business drivers that should be considered for implementing a modeling culture, as well as the considerations around the management of a modeling project and its lifecycle framework.
This course is beneficial for individuals that are looking for a more fundamental understanding of what is meant by all the buzzwords surrounding modeling, and would like to learn what considerations go into the creation and management of a modeling project.
This course comes at a critical time in the biomanufacturing industry where there is a lot of focus on the digital transformation of manufacturing sites, so that more complete and rich sources of data are available to operators, analysts, and management in order to make critical decisions in a more timely manner. For the industry as a whole to be successful in this transition, there needs to be a better understanding of what is meant by the terminology surrounding modeling, and an understanding of what considerations need to be made before embarking on this journey towards a modeling culture.”
- Ryan Barton, Ph.D., Automation/Data Scientist at NC State BTEC
“The IAAE online course called A path to model-based biomanufacturing introduces this complex and important field in very understandable manner. It helps faculty like me to see where the industry is headed, and, encourage students to think along these lines of gaining data analysis and modeling skills. It is great for faculty professional development in computer science, engineering, and biotech for both four-year as well as other community college programs.”
- Savita Prabhakar, Assistant Professor and Program Manager Biotechnology at Frederick Community College, MD, USA
Our audacious goal
IAAE seeks to credential 10,000 learners globally, and to engage 10 of the top 20 companies in each regulated health industry, by the end of 2035.
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