High-throughput and modeling technologies for process development in antibody purification

This cumulative thesis evaluates opportunities, to integrate high-throughput and model-based technologies in biopharmaceutical protein purification

Simulation-based surface roughness modelling in end milling

The surface topography often is an important quality criterion for the manufacturing of milled workpieces as it often defines their functional behaviour. In machining both, the kinematics of the process and the stochastic influences deriving from the machine tool, workpiece and the surrounding environment affect the workpiece's surface roughness. This paper presents a simulation-based method for flank milling, which considers kinematic and stochastic influences including run-out errors and tooth length variations. The simulation results are used in combination to predict the surface roughness depending on the chosen process parameters. Hence, also making in possible to choose appropriate process parameters to achieve a defined surface roughness

Chromatographic parameter determination for complex biological feedstocks

The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 μL can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks.BT/Bioprocess EngineeringBT/Design and Engineering EducationApplied Science