Enrolment options

Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After completing the course students will be able to:
1. build kinetic simulation models of the cell growth and product formation
2. connect different models together to build a bioprocess model
3. define parameters for kinetic and static bioprocess models
4. create experimental designs for bioprocess screening and optimization tests
5. create response surface models and define optimum variable values thereof
6. create multivariate models from various data sources including e.g. raw materials, cultivation conditions, product properties, expression data
7. utilize certain chemometric modelling approaches for bioprocess estimation and simulation simulations
8. arrange simple experiments to find out certain kinetic and optimization parameters of a bioprocess
9. estimate the model validity in various cases

Credits: 5

Schedule: 15.09.2021 - 28.10.2021

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Tero Eerikäinen, Jenny Thors

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    Bioprocess behavior in different modes and modeling principles combined to experimental works. Computer-aided bioprocess modeling and simulation. Creating bioprocess models in MATLAB and Simulink environment. Linear and non-linear estimation of the kinetic parameters for types and models. Multivariate modeling possibilities and limitations. Response surface modeling, principal component analysis, neural networks. Use of models as a part of Quality control as process analytical technique. Creating a bioprocess simulation model and validating parameter values from experimental data.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Lectures, computer exercises, experimental work, assignments and independent studying

Workload
  • valid for whole curriculum period:

    Total 135 h = 5cr
    Lectures and exercises 24 h, 2x2 h per week
    Experimental work 35 h
    Assignments 12 h
    Independent studying 60 h
    Exam 4 h

DETAILS

Study Material
  • valid for whole curriculum period:

    Material to be announced

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    6 Clean Water and Sanitation

    7 Affordable and Clean Energy

    9 Industry, Innovation and Infrastructure

    13 Climate Action

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Only available for students majoring in Biotechnology.

    Teaching Period:

    2020-2021 Autumn I

    2021-2022 Autumn I

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=CHEM-E3205

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    Sisu

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