Free seminar
Bioprocess data analytics & data management
Sheraton Boston Hotel, Boston, MA
Highlights of the free seminar
Best practices for bioprocess data management and analytics along the product life cycle
- Efficient Bioprocess development
- Scale-up and scale down
- Manufacturing Science
- Process Validation
Location: Sheraton Boston Hotel, 39 Dalton Street, Boston, MA 02199
Instructor: Christoph Herwig
Full Professor for Biochemical Engineering, Vienna University of Technology, Austria
Guest Professor @ MIT
Prof. Christoph Herwig was appointed full professor in biochemical engineering in 2008 returning from a top management position in the biopharmaceutical industry. His research areas include data science driven methods for fermentation technology, bioprocess development, facility design and biotechnological production.
Course Objective
Hands-on learning of basic principles and best practices performing data analytics and data management for integrated bioprocesses. Designed for the biopharmaceutical and industrial biotech industry.
The course topics include
- best bioprocess data analytics principles
- design of experiments
- data management and contextualization of data sources of different origin
- basic statistics for root cause analysis, scale-up, scale-down and comparability studies
- and much more.
Primary Audience
This course is designed for all individuals who are involved in bioprocess development & manufacturing as well as process validation. This includes bioprocess development scientists, engineers, manufacturing and quality supervisors, and management. No statistical or mathematical background is required.
Interactive seminar
Bring your own laptop. You will perform exercises on bioprocess data management and analytics using the web-based educational software tool inCyght®.
Course Outline
PM 13:30 – 18:00
- Digital Bioprocess Lab/ Plant: Data Management Workflows
- Monitoring & Trending, raw data visualization
- Inspecting your data for outliers
- Setting process phases
- Networking break
- Bioprocess data analytics: Best practices
- Conversion of raw data to reliable feature based information
- Design of Experiments (DoE)
- Root Cause Analysis of process variability
- Comparability studies: Scale-up & Scale-Down and process validation tasks
No Prerequisites
registration closes 16-07-2018 0:00