Background

The Institute of Process and Particle Engineering is a world leader in the development of pharmaceutical products and processes.

In this context, we are offering a paid master thesis where the student is employed at an external company.

The goal of the master thesis is to create the basis for product development, focusing on a novel drug delivery system where the medicine is contained in a flavored gel, either as solution, emulsion or suspension. Drug delivery occurs via breaking a seal of a snap-package and sucking out the flavored gel. Target patient populations includes:

• Geriatric patients (frail & old patients)
• Pediatric patients (kids)
• Emergency applications

Tasks

• Literature study on competitor products and patent situation
• List of the 20-30 most important medicines for the three target populations and corresponding biopharmaceutical classification
• Research on formulation strategies (solutions, emulsions, suspension) with sufficient stability
• Selection of 3 model APIs (different categories) and formulation of the gels
• Stability testing under stress conditions

Requirements

• Background in pharmaceutical sciences, pharmaceutical engineering or medicines
• Student in pharmacy, pharmaceutical engineering, chemical engineering or related

What we offer:

• Integration in an internationally leading team
• Opportunity to be part of a commercialization project
• Paid thesis

Start: Spring 2021

Contact: Univ.-Prof. Dr. Johannes Khinast, khinastnoSpam@tugraz.at

Background

Continuous flow synthesis has recently emerged as the new paradigm for the manufacturing of active pharmaceutical ingredients (APIs). Many benefits come with implementing continuous processes, such as increased throughput, constant product quality, the possibility of controlling and automating the process, increased safety and waste reduction. Continuous flow processes are also widely considered a valid platform where to implement and test new technologies that can change  the way fine chemicals are traditionally manufactured. Lately, there has been increasing interest in the application of biocatalysts as a tool for synthetic chemistry, since it is considered a very promising  and greener alternative to conventional catalysts, which are mostly metal-based. Enzymes have many advantages, such as low toxicity and environmental impact, high activity in mild conditions, and high selectivity. Therefore, the possibility of exploiting the advantages of continuous flow synthesis as well as biocatalysis is very attractive for both researchers and industry. However, still a lot of work needs to be done to increase the feasibility of biocatalysts and to design continuous flow biocatalytic processes that can be industrially competitive.

Figure 1 – Generic scheme of a multistep (bio)catalytic process

The aim of this project is to develop a process for multistep (bio)catalytic cascade reactions for the production of APIs in continuous flow. The process can be flexible and feature different modules: reaction modules that can host packed bed reactors filled with the immobilized enzymes or catalyst, as well as modules for other unit operations (e.g. heating/cooling, mixing, extraction). A great part of the work will be dedicated to identify an optimal immobilization strategy onto innovative supports (e.g. 3D printed, see Figure 2).  The possible challenges include: finding an optimum immobilization protocol that minimizes leaching and optimizes the stability of the enzymes; the choice of an optimal solvent compatible with multiple reaction steps; the possible interaction of by-products within the system. To increase process understanding and efficiency, the possibility of implementing process analytical tools, such as inline sensors for real-time analyses, will be explored as well.

Figure 2 -  CAD design of a honeycomb type of  support structure

Tasks

• Literature study on industrial biocatalysis in continuous flow and enzyme immobilization
• Study of the enzymatic reaction kinetics in batch
• Design of an adequate continuous process
• Optimization of the reaction/process conditions
• Implementation of real-time analytics (e.g. UV-vis probes)

Requirements

• Background in chemical engineering, chemistry or biotechnology
• Interest in the above mentioned fields
• Basic lab work experience

What we offer:

• Integration in an internationally leading institute (IPPT) of TU Graz
• Support from the CoSy Pro Team
• Paid thesis (in case of the Masters’ thesis)

Start
At any time

Contact:
Dipl. Ing. Dott.ssa Alessia Valotta
valottanoSpam@tugraz.at - +43 316 873 - 30428

Assoc. Prof. Dipl.-Ing. Dr.techn. Heidrun Gruber-Wölfler
woelflernoSpam@tugraz.at

Biopharmaceuticals steadily increase in market share on the pharmaceutical market. New and innovative formulations for biopharmaceuticals such as protein-based drugs are of high interest for the future. Currently biopharmaceutical drugs are either formulated liquid based or freeze-dried.

Our research group focuses on alternatives to freeze drying such es e.g. spray drying (SD, Figure 1 right). The drying of a droplet to a solid particle encompasses three main steps; i) atomization of the feed formulation into micron sized droplets, ii) drying in several drying stages to a solid particle and iii) collection of the produced protein powder. The process parameters (e.g. inlet temperature, volumetric drying air rate, spray rate) and process configuration (e.g. type of nozzle, residence time) strongly interplay with the formulation properties such as viscosity, surface tension or protein concentration (Figure 1). In depth knowledge and sound understanding of the process and formulation correlations with regard to the product should be developed throughout this study.

This work includes literature research on excipient candidates and design of experiments (DoE), followed by setting up a DoE and the classification of excipient properties and performing of drying experiments. We offer you high scientific and industrial relevant work in the emerging field of drying biopharmaceuticals. You will be supported from the IPPE project team and obtain desk and office space. In case of a Masters’ thesis monetary compensation is possible.

Sparked interest?

Contact: Daniela Fiedler,
daniela.fiedlernoSpam@tugraz.at, +43 316 873 30418

Start: as soon as possible

The fact that human beings differ from each other, regarding their physiology, pathology and environment suggests, that not everyone can be treated using the same medication. Therefore, a trend towards personalized medicine is observable. This trend brings up some challenges, as it comes to the production of tablets. The dose of the Active Pharmaceutical Ingredient (API) as well as the amount of any excipient needs to be dosed accurately, for each individual tablet.

The development of a device being capable to do so, is the goal of this thesis. As the dosing shall be done gravimetrically, the dosing unit will contain a feeder and a weighing cell. A scheme of the set-up and its features can be seen below.

Your work will include the following points:
•    Picking a development environment (LabView, Arduino/Raspberry Pi, …)
•    Picking a weighing cell with sufficient accuracy and fitting dynamic properties
•    Integration of weighing cell and feeder in an environment for control and data acquisition
•    Investigation of the feeding/dosing characteristics of the set-up
•    Development of a self-adjusting dose algorithm

We offer
•    High scientific and industrial relevance (the approach involving this dosing process could speed up the development in pharmaceutical industry and allow to produce personalized medicine)
•    Support from the IPPE project team and Prof. Horn from IRT
•    Desk and office space

Contact:
Andreas Kottlan, andreas.kottlannoSpam@tugraz.at, 0316-873-30419
Starting date: as soon as possible 2020

Sonic mixing is a relatively new approach for mixing various systems. The process is used to some extend in pharmaceutical industry to produce powder mixtures and pastes. To achieve a satisfying mixing quality, the system is exposed to vibration with high acceleration and high amplitudes in means of travel. This is commercially realized by using a system working at resonance frequency to minimize the power input.

We aim for a much smaller system size, i.e. the mass of single tablet. This allows us to get rid of the need for a system operated at resonance. Therefore, the frequency can be varied to achieve the most effective mixing process. A schematic sketch of the setup can be seen in figure 1.

This thesis shall bring insight to some specific points:
•    How do the operating parameters, i.e. frequency and amplitude affect the flow pattern within the mixing vessel?
•    How does the “flow regime” within the mixing chamber affect the mixing performance?
•    How do different powders react to different operating parameters?
•    Is it possible to find a robust mode of operation which provides satisfying results for various powder systems?
•    Can coating or granulation processes be done using this setup?

The investigation on these topics shall be done using an existing experimental setup, which can be modified to meet arising requirements. The student shall elaborate a design of experiments which covers the relevant operating range of the used vibration generator and accounts for different powder blends. Once defined, the mixing experiments are to be carried out. The blends, produced in this way, need to be analysed. The search for meaningful analysis methods is part of this work.

We offer
•    High scientific and industrial relevance (the approach involving this mixing process could speed up the development in pharmaceutical industry and allow to produce personalized medicine)
•    Support from the IPPE project team
•    Desk and office space

Contact:
Andreas Kottlan, andreas.kottlannoSpam@tugraz.at, 0316-873-30419
Starting date: as soon as possible

Current trends in advanced multiphase flow prediction aim at the usage of machine learning algorithms and deep neural networks to improve the accuracy and to speed-up numerical simulations. Overall, it can be expected that these tools (and artificial intelligence, AI, in a wider context) will become an important part of numerical modelling used in chemical engineering applications.

The overarching goal of this Master Thesis project is to increase the speed of gas-particle flow simulations (see the right panel in the Figure below) by using an AI-powered prediction algorithm.

Your tasks will include (i) a literature review on the usage of deep learning in numerical simulations, (ii) an investigation related to key parameters of a neural net structure to speed up a widely-used gas-particle flow simulator, and (iii) application of the improved simulator to a use case. The machine learning and deep neural nets will be based on existing open source AI platforms (e.g., Tensorflow), for which expert knowledge is already available at our institute.

Qualification

• Interest in Computational Fluid Dynamics (CFD), Discrete Element Method (DEM)
• Basics programming skills (Matlab/octave, Python, C/C++ or other), and interest to refine your programming skills during the Master Thesis project

We offer

• Extremely high scientific and industrial relevance
• Introduction to the leading open-source gas-particle simulation tools OpenFOAM® and CFDEM®. Support with the AI platform, as well as with respect to programming.
• Computer power, desk and office space
• Possibility to publish the results and findings in a scientific journal

Contact

Josef Tausendschön: josef.tausendschoennoSpam@tugraz.at, Stefan Radl: radlnoSpam@tugraz.at