CHEM ENG 7065 - Batch and Continuous Biomanufacturing

North Terrace Campus - Semester 1 - 2023

The objective of the course will be to teach the advantages of continuous manufacturing over batch manufacturing within the pharmaceutical sector. The quality, economic and operational benefits will be covered. The course will teach how batch manufacturing unit operations can be adapted to continuous operations. It will also cover the need to develop new bespoke continuous clarification and purification operations. Finally the quality management and regulatory affairs implications of continuous manufacturing will be assessed. By the end of the course, students will be able to

  • General Course Information
    Course Details
    Course Code CHEM ENG 7065
    Course Batch and Continuous Biomanufacturing
    Coordinating Unit School of Chemical Eng and Advanced Materials(Ina)
    Term Semester 1
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Course Staff

    Course Coordinator: Lukas Gerstweiler

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    1 Gain in depth understanding of different approaches of batch and continuous biomanufacturing
    2 Understand the principles of in-silico modelling of chromatographic systems and can conduct chromatography modelling based on mechanistic models.
    3 Can optimise continuous multi column chromatography systems using model commercial mechanistic model software in combination with data anlayisis.
    4 Understand different mutli-column chromatography set-ups such as simulated moving bed, periodic counter current chromatography and multi-column solvent gradient purification.
    5 Understand the influence of continuous processing on product quality, plant footprint and utilities consumption.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.

    1-5

    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.

    2-4

    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

    3

    Attribute 7: Digital capabilities

    Graduates are well prepared for living, learning and working in a digital society.

    2-3

    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

    2
  • Learning Resources
    Required Resources
    Access to a computer with Windows (Linux, Mac is currently not supported) to install modelling software
    Online Learning
    All course materials can be accessed through MyUni
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Lectures will be pre recorded and accessible through MyUni. Students are expected to watch the lectures before attending tutorials/workshops.
    Tutorials/Workshops will reinforce and discuss the main aspects of the lectures.
    Also group work on mechanistic modelling will be conducted in the tutorials/workshops
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    This course has an assumed workload of around 150 hours for the semester. 
    Face-to-face activities account for 2 hours per week. Additionally pre-recorded lectures, excersises and practice should require 4-6 hours per week.
    The design and model project will reequire approximatley 50 hours of work.

    Activity In-class hours Out-class hours Expected total student workload
    Lectures 0 24 24
    Tutorial 24 24 48
    Practice 0 24 24
    Design project 0 50 50
    Total 24 122 146
    Learning Activities Summary
    weekly tutorial/lectures
    Online videos and quizzes
    weekly modelling exercise
    Preparation
    Design project

    Week Topic Summary
    1 Introduction Biologics manufacturing Introduction of current state of the art manufacturing. Quality attributes and challenges
    2 Fundamentals chromatography 1 Theroetical fundamentals of chromatographic purifiaction of biopharmaceuticals
    3 Fundamentals chromatograph 2 Theroetical fundamentals of chromatographic purifiaction of biopharmaceuticals
    4 Mechanistic modeling 1 Mathematical description of chromatographic purification. Including mass transfer and binding kinetics. Intrduction of different simplified transport models such as the gernal rate model and the lumped rate model, as well as binding models such as steric mass action model.
    5 Mechanistic modeling 2 Mathematical description of chromatographic purification. Including mass transfer and binding kinetics. Intrduction of different simplified transport models such as the gernal rate model and the lumped rate model, as well as binding models such as steric mass action model.
    6 Bioreactors Introduction of continuous bioreactors and differences to batch bioreactors. Residence time distribution and kinetics
    7 Simulated moving bed Introduction of simulated moving bed chromatography and main deisgn principles
    8 Periodic counter current chromatography Introduction of periodic counter current chromatography and main deisgn principles. Productivity and resin utilization
    9 Polishing 1 Futher continuous approaches for final purification of bipharmaceuticals such as multi-column solvent gradient purificationm flow through chromatography, single-pass tangential flow filtration, etc.
    10 Polishing 2 Futher continuous approaches for final purification of bipharmaceuticals such as multi-column solvent gradient purificationm flow through chromatography, single-pass tangential flow filtration, etc.
    11 Process digitalization Introduction to process digitalization and control, challenges caused by column fouling. 
    12 Recap and preparation for final exam


  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Task Type Due Weighting Learning Outcome
    Mid semester quiz Quiz

    Week 6

    20% 1-4
    End of semester quiz Quiz End of week 12 40 % 1-4
    Modelling Project Individual report, Data generation in groups End of week 12 40 % 1-4
    Assessment Detail
    Mid semester quiz:

    Before the mid semester break a small quiz will be conducted. The quiz will be a combination of multiple choice and short answer questions on the course content of the prior weeks. The quiz will be taken in class as a cloased book exam of 60 minutes.

    End of semester quiz:

    At the end of the semester a final exam will be conducted. The exam will comprimise of a comination of multiple choice, short and long answer questions as well as basic calculation, covering the content of the entire course. The exam will be taken in class as a closed book nexam of 120 minutes.

    Modelling project:
    A final report of the modelling has to be submitted by the end of the semester. The report has to be written in style of an academic publication and shall include the generated and analysed data, as well as a discussion, intrododuction and conclusion.
    Submission
    Quizzes will be taken in class.
    The mid semester quiz will be undertaken after the last lecture before the mid semester break.

    The final exam will be undertaken after the last lecture.

    The modelling report will be submitted in myUni by the end of the semester. 

    Feedback on assignments will be returned approximatley 2 weeks after submission and students will have the chance to double check the assessment. 
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

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    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

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