UROP Project

Parameter estimation and optimal experimental design towards a predictive model for monoclonal antibodies production

Contact

Name

Daniel Holder

Program Director UROP

Telephone

workPhone
+49 241 80-90695

E-Mail

Key Info

Basic Information

Project Offer-Number:
984
Category:
Keine eindeutige Zuordnung
Field:
Chemical Engineering
Faculty:
4
Organisation unit:
AVT.SVT
Language Skills:
fluency in English or German
Computer Skills:
Some programming experience (e.g. MATLAB or C++)
Professor:
Alexander Mitsos

Monoclonal antibodies (mAbs) represent the fastest growing product of the biopharmaceutical industry with both diagnostic and therapeutic purposes (e.g. cancer treatment). As an alternative to expensive and time-demanding experimentation, model-based approaches for optimization and control purposes of mAbs are gaining increasing attention. In this direction parameter estimation and optimal experimental design are powerful tools towards creating high fidelity and predictive models.

Task

In this work, the student will have the opportunity to apply parameter estimation methods optimal design of experiment to a model for mAb production. -Short literature review on monoclonal antibodies and their production methods -Gain basic knowledge on parameter estimation and optimal design of experiments -Perform parameter estimation to a model for mAb production -Use of optimal experimental design to maximize the information gain obtained from each experiment and minimize the resources required -Optimal experimental design for parameter precision -Interpret the results and prepare a short report with the main outcomes of the project

Requirements

The ideal candidate should be motivated, with some basic knowledge on model development, biological processes and programming, and with high interest in applied mathematics and biochemical engineering.