Master of Medical Technology Innovation

BioDesign Innovation Needs Discovery introduces students to identifying and prioritising unmet healthcare needs as the foundation for innovation. Students will analyse clinical practice and scientific literature, gather qualitative and quantitative data, and apply these insights to define opportunities.

Through lectures and practical training in BioDesign principles, students will conduct background research, observe clinical practice, and screen identified needs. They will also consider market potential, regulatory pathways, reimbursement, and intellectual property. Working with clinicians, students will complete a guided project culminating in a need specification that addresses clinical impact, feasibility, and market viability. Assessment tasks directly reflect these activities, ensuring students gain practical experience and demonstrate key innovation skills.

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This subject will cover key aspects of engineering management to help students prepare for working in the biomedical engineering industry including the processes and regulations of therapeutic goods.

It will focus on Biomedical Engineering Management, including the engineer and professional practice, the functions of professional societies; systems engineering and management processes of planning, organisation, leadership and control of human, physical and financial resources, biomedical engineering and quality management systems including ISO 9000 series requirements. This subject will also cover regulations, including risk management and international and Australian regulatory guidelines focusing on medical device regulations, classifications and standards. Also taught in this subject will be human clinical trials, regulation and ethics, design and evaluation of human clinical trials, requirements for post market monitoring, and medical device registries.

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Students will explore the fundamental concepts of medical technologies, including safety and risk management, biocompatibility, and systems integration between devices and the human body. Through case studies of devices, such as the cochlear implant, cardiac pacemaker, and deep brain stimulation, students will learn how these technologies are developed to restore or enhance function.

Students will also engage with the principles of Quality Management Systems (QMS) for medical devices, applying the ISO13485 standard to understand how the industry manages design, production, and regulatory compliance across the device life cycle. By the end of the subject, students will be able to explain how medical technologies are developed and evaluated, and apply key principles of quality and safety that underpin professional practice in the medtech field.

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BioDesign Innovation Concept Development is a “real world” subject in creating successful healthcare solutions. The first step in creating a successful solution is to ensure that it solves an unmet health need. After finding and validating an unmet need, concepts are generated and screened for that need, followed by concept development and business implementation.

The subject is composed of frontal lectures, practical training, and a guided project, focusing on brainstorming and concept creation and development based on a predetermined unmet health need. Teams of students will conceive and design an innovative medical device, taking it as far as possible through the steps of development. The students in the teams will complete assessment items together. The teams will create an engineering prototype of their invention and compose a detailed business plan, considering intellectual property, research & development, clinical, regulatory, quality management, reimbursement, and business strategies.

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AIMS

This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. The subject builds upon signals and systems modelling approaches to demonstrate the application of mathematical and computation modelling to understanding and simulating neural systems. Aspects of neural modelling that are introduced include: membrane potential, action potentials, neural coding, neural models and neural learning. The application of neural information processing is demonstrated in areas such as: electrophysiology, and neuroprostheses. Material is reinforced through MATLAB and/or NEURON based laboratories.

INDICATIVE CONTENT

Topics include:

Neural information processing analysed using information theoretic measures; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); neural models (binary, rate based, integrate & fire, Hodgkin-Huxley, and multicompartmental); synaptic plasticity and learning in biological neural systems (synaptic basis of learning, short term, medium term and long term, and rate based Hebbian learning models); spike-timing dependent plasticity (STDP) of synapses; higher order neural pathways and systems (cortical structure and circuits).

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AIMS

Students studying Tissue Engineering and Stem Cells will become familiar with the history, scope and potential of tissue engineering, and the potential role of stem cells in this field. This subject will address the use of biomaterials in tissue engineering; major scaffold materials and fabrication methods, scaffold strength and degradation; cell sources, selection, challenges and potential manipulation; cell-surface interactions, biocompatibility and the foreign body reaction; the role and delivery of growth factors for tissue engineering applications; in vitro and in vivo tissue engineering strategies, challenges, cell culture, scale-up issues and transport modelling; ethical and regulatory issues; clinical applications of tissue engineering, such as bone regeneration, breast reconstruction, cardiac and corneal tissue engineering, and organogenesis (e.g. pancreas).

This subject provides students with exposure to and understanding of a range of new and emerging applications of biomedical engineering. It includes research-led learning with opportunities to interact with experts and active researchers in the fields of stem cells and tissue engineering. The subject covers aspects of biology, materials engineering and process engineering which underpin tissue engineering and provides examples of the applications of this evolving area of technology.

INDICATIVE CONTENT

Topics covered include tissue organization & tissue dynamics, stem cells, cellular fate processes & signalling, the ECM as scaffold material, natural and synthetic polymers for tissue engineering, bioceramics, scaffold design and fabrication, tailoring biomaterials, cell culture and cell nutrition, bioreactors for tissue engineering, risk management in tissue engineering, ethics in tissue engineering.

Please view this video for further information: Tissue Engineering and Stem Cells

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AIMS

This subject introduces students to the engineering, physics and physiology of medical imaging, including the history and progression of medical imaging modalities as well as emerging imaging technologies in clinical and research practise. Topics covered include: x-ray, computed tomography, positron emission tomography, magnetic resonance imaging and ultrasound.

INDICATIVE CONTENT

Topics include:

Image metrics including signal-to-noise and contrast-to-noise ratios, image resolution, image operations including convolution, filtering and edge detection;

Biophysical principles of X-ray, CT, PET, SPECT, MRI and ultrasound, and the mathematics of image reconstruction for each modality, including filtered backprojection and fourier reconstruction methods;

This material is complemented by the use of software tools (e.g. MATLAB) for data simulation, modelling, image manipulation and reconstruction techniques.

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AIMS and INDICATIVE CONTENT

In this subject students should gain an understanding of the structure and function of the skeletal, muscular, and sensory systems of the human body.

Students should also be able to formulate simple, integrative models of the human neuromusculoskeletal system; and to use computational models of the human body to analyse muscle function during activities like standing, walking, running and jumping.

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AIMS:

This subject introduces mathematical and computational modelling, simulation and analysis of biological systems. The emphasis is on developing models, with examples, using MATLAB.

INDICATIVE CONTENT:

Topics include:

Modelling biochemical reactions. Law of mass action. Enzymes and regulation of enzyme reactions. Thermodynamics of reversible biochemical reactions. Cellular homeostasis. Application of ordinary differential equations to these problems.

Modelling large reaction networks. Flux balance analysis and constraint-based methods. Genome-scale models. Regulation of gene expression. Gene regulatory networks in systems and synthetic biology. Network inference and statistical modelling of –omic data. Knowledge-based modelling in systems biology.

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AIMS

This subject introduces students to the analysis of soft tissue and cellular biomechanics.

The human body is mostly composed of soft tissues. These tissues and their cells respond to or generate mechanical forces to sustain human health. For example:

• Heart muscle cells generate forces to pump blood.

• The stomach generates pulsatile forces that help food digestion.

• Cancer cells move and spread through the body by generating mechanical forces.

Soft tissue mechanical properties change in cardiovascular disease, gastrointestinal dysfunction and cancer. Therefore, studying the biomechanics of soft tissues and cells is essential to health and disease management.

Soft tissues experience forces drastically differently to bones and engineering materials due to their soft nature. Standard engineering analysis methods that are adopted for bone biomechanics are not useful. This subject will introduce students to the right theoretical and experimental mechanical analysis framework to study soft tissue and cellular biomechanics. Students will learn the computational methods underlying finite element modeling, which is needed to perform accurate biomechanical analyses of soft tissues and cells.

By the end of this subject, students will be proficient in advanced biomechanics concepts, which are essential to study soft tissues and cells. The subject will routinely expose students to applications of the subject concepts through case studies in cardiovascular biomechanics, cancer and tissue engineering. Guest lectures will be provided by industry, clinical and research experts who work in or apply principles of soft tissue and cellular biomechanics.

INDICATIVE CONTENT

• Cell and tissue biomechanics
• Finite element modeling
• Mechanical characterisation of soft tissue and biomaterials
• Applications of biomechanics in industry and healthcare.

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This subject teaches the fundamental theory, design and operational principles of biomedical instrumentation and measurement systems for the design of electronics for measurement and analysis of physiological parameters of the body and organs. The subject provides theory and practical exposure to understanding the basis of physiological signals and analysing biomedical signals, including hands-on experience in designing and building bioinstrumentation systems that can measure biological signals. Students will be introduced to medical devices, design principles, biomedical signals, biomedical instrumentation circuits and electrical safety and systems. These topics will be complemented by exposure to software tools for electronic circuit simulation and design. The subject is taught in a flipped classroom format and comprises: pre-tutorial reading, tutorials requiring student participation, guided workshops on using biosensors and transducers and individual self-paced project work.

Please view this video for further information: Bioinstrumentation

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This subject teaches the fundamentals of signal processing in a biomedical engineering context. Students will be introduced to digital sampling of analog signals, frequency domain analysis, design of digital filters, parameter estimation techniques and Wiener and Kalman filtering. The subject includes analysis and design for biomedical engineering applications.

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This subject will cover the physics of fluids, with a special focus on biologically relevant fluid flows. This includes the flow of bodily fluids in biomedical testing devices and in therapeutic systems. Students will study fundamental fluids mechanics principles and develop an understanding of the mathematics that describe them. These principles will then be employed using computational approaches in real-world applications for fluid mechanics, including pipe flow, microfluidics, pumps and rheology.

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This subject teaches fundamentals of data analysis as relevant to modern biomedical engineering, in an integrated approach that combines theory with highly contextualised, project-based learning. Students are introduced to the foundations of probability and random variables, statistical hypothesis testing, linear and nonlinear regression, data classification and dimensionality reduction techniques. Each topic is explicated via case studies from clinical, industrial and research applications of biomedical engineering, covering topics in biomechanics, biosensors, bioinformatics, biomedical imaging and biomaterials.

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Biomechanics, which relates structure and function in biological systems, is important in the understanding of human movement, and in the treatment of conditions affecting the musculoskeletal and neuromuscular systems. This subject introduces students to musculoskeletal biomechanics of the human body, with applications to the behaviour of biological tissues such as bone, cartilage, ligament and muscle during human movement.

The subject will provide theory and practical exposure to human motion measurement and modelling of the joint forces and moments that actuate human movement. This subject will introduce biomechanics in sport and implant systems, including ageing, injury and associated musculoskeletal disorders. It will provide an overview of orthopaedics strategies for the treatment of end-stage bone and joint conditions and relate this to relevant mechanics for designing implant systems.

Please view this video for further information: Biomechanics

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Process engineering applies scientific principles to convert raw materials and energy into useful products, and it is critical to a variety of biomedical technologies including production of pharmaceuticals, dialysis, tissue engineering, etc. Core to process engineering is an understanding of how energy and mass move through systems – and how these can be controlled – to achieve a desired goal.

In this subject you will learn the fundamental laws that describe how heat and mass move through systems and develop mathematical models that describe this movement. We will then look at how this movement of energy and mass is applicable to the biomedical engineering discipline. Some of the topics covered are listed below:

• How oxygen and nutrients travel through the human body to maintain homeostasis,
• How cell culture and tissue engineering systems can be designed to provide sufficient nutrients and oxygen to maintain cell viability,
• How dialysis can be used to remove contaminants from blood of patients suffering kidney failure,
• How the presence of a bacterial biofilm limits the ability to treat biomedical device-related infections, and
• How processes can be designed to produce products like pharmaceuticals.

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In this subject, students will actively engage in an interdisciplinary, collaborative and project-based learning environment, offering insights into the professional nature of engineering work. Through a real-world project, students will gain hands-on design experience addressing a complex challenge. The project will require students to integrate discipline knowledge and apply professional skills like teamwork and communication.

Students will experience the entire engineering design process, covering problem definition, ideation, concept development, analysis, prototyping, testing and iteration. The project provides practical experience, equipping students with tools and methods to address complex challenges. Students are expected to integrate diverse perspectives, considering factors like stakeholders, sustainability (including environmental and social issues), safety, feasibility, and technical and ethical considerations.

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Successful commercialisation of scientific discoveries and new technologies occurs in a unique business environment where scientific and business interests and personalities must productively interact.

The subject will develop a critical understanding of the context in which the commercialisation of science occurs, and the opportunities and challenges encountered. Topics covered within the subject will include the nature and types of intellectual property (IP), how it can be protected, valued, managed and strengthened, its use as a commercial tool, exploration of the barriers to commercialisation, what strategies can be used to exploit IP, how to develop a commercial plan and leverage finance for the commercialisation of IP.

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What does it take to develop something innovative and then move it from the laboratory out into the real world? Scientists must negotiate a labyrinth of hurdles, ranging from conducting bullet-proof data analysis, designing clinical trials, developing and managing intellectual property, assessing contracts, and setting up Total Quality Management systems in a biotech setting. Students will learn how to navigate these hurdles as applied to a range of possible inventions, such as therapeutics, diagnostics, medical devices, GMOs and other bio-science-related creations.

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Excellent scientific leadership is not only required in academic research groups, but also in technological industries and many areas of government. This subject will examine the nature and styles and consequences of leadership and decision making in academia, industry and government.

Students will examine, through a series of lectures, seminars and workshops, the roles of leadership in: motivation, ethics, risk and the development of a productive organisational culture drawing upon case studies, personal accounts from scientific leaders and their own personal experiences.

In addition, students will learn strategies to deal with staff and clients, build teams, make decisions, think strategically, develop self awareness, identify and manage conflict of interest, identify opportunity and value diversity.

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This subject aims to provide students with the necessary tools to: identify social and ethical issues of digital technology particularly artificial intelligence and reason about these issues; communicate concerns, or discuss ideas, from differing points of view; and ultimately build technology with awareness of, and respect for, inclusion and the responsibility that comes with building powerful tools. Not contemplating ethical or social implications of AI and other technological tools may open up unintended consequences and risks. Ethical dilemmas can also cause additional personal stress for individuals who lack the skills to think about them reflectively. For these reasons, the growing societal and ethical problems raised by artificial intelligence and other technologies have become a major focus of many organisations, including for start-ups, government, defence, and many corporations.

Topics include:

• the history of artificial intelligence
• established ethical theories and concepts and their relation to artificial intelligence and technology
• fairness, equity, and discrimination in automated decision making
• accountability, explainability, and transparency of AI
• practical approaches and ethical frameworks for designing, developing and deploying technology responsibly

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AIMS

The subject will introduce the basics of computer networks to students through a study of layered models of computer networks and applications. The first half of the subject deals with data communication protocols in the lower layers of OSI and TCP/IP reference models. The students will be exposed to the working of various fundamental networking technologies such as wireless, LAN, RFID and sensor networks. The second half of the subject deals with the upper layers of the TCP/IP reference model through a study of several Internet applications.

INDICATIVE CONTENT

Topics covered include: Introduction to Internet, OSI reference model layers, protocols and services, data transmission basics, interface standards, network topologies, data link protocols, message routing, LANs, WANs, TCP/IP suite, detailed study of common network applications (e.g., email, news, FTP, Web), network management, and current and future developments in network hardware and protocols.

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AIMS

Machine Learning is the study of making accurate, computationally efficient, interpretable and robust inferences from data, often drawing on principles from statistics. This subject aims to introduce students to the intellectual foundations of machine learning, including the mathematical principles of learning from data, algorithms and data structures for machine learning, and practical skills of data analysis.

INDICATIVE CONTENT

Indicative content includes: cleaning and normalising data, supervised learning (classification, regression, linear & non-linear models), and unsupervised learning (clustering), and mathematical foundations for a career in machine learning.

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