The objective of this course is to provide students with regulatory body and ethics considerations by which they engineer safe medical device products intended for use as implantable devices or in contact with body tissue and fluids. A top down approach will be taken where the regulatory path for product approval and associated costs with product development and validation are reviewed for different biomaterials and devices. This path is then assessed in the context of product specific reimbursement, ethics, safety, competitive positioning, and regulatory concerns.

Students will be required to use their existing knowledge of biomaterials and devices, and their biocompatibility to frame the questions, challenges and opportunities with a mind to re-engineering products in order to capitalize on niche regulatory pathways. The resulting regulatory path gives a good idea of the kind of trial design the product must prevail in and ultimately the design characteristics of the device itself. Decision making will be made with ethical considerations. The discussion model will focus mostly on the United States regulatory office with some comments on Canada and Europe.

Lastly, quantitative product development risks estimates are considered in choosing a product path strategy for proof of concept and approval of safe products. Ethical issues can also impact design since in biomedical engineering they are currently studied in the fields of bioethics, medical ethics, and engineering ethics. Yet, professional ethical issues in biomedical engineering are often different from the ones traditionally discussed in these fields as they need to align with the engineering profession.

Biomedical engineers differ from medical practitioners, and are similar to other engineers, in that they are involved in research for and development of new technology, and do not engage in the study, diagnosis, and treatment of patients. Biomedical engineers differ from other engineers, and are similar to medical practitioners, in that they aim to contribute to good patient care and healthcare. The ethical responsibilities of biomedical engineers thus combine those of engineers and medical professionals, including a responsibility to adhere to general ethical standards in research and development of technology and to do R&D that adheres to the specific standards set forth by medical ethics and bioethics. This course focuses on products currently for sale as case studies, or may be approved for sale within the next two years consistent with its practical commercial focus.

This course will apply human factors engineering principles to the design of medical devices. Testing medical devices in a health care setting, with realistic users, will be emphasized to understand why devices fail to perform adequately. Students in this course will work in teams to complete an evaluation of a medical device design, existing prototype, or commercial product by conducting usability studies, with realistic users, to uncover use errors. Human factors engineering analysis will be used to propose and make design changes to improve the design and validation testing will be used to prove that design modifications yield a reduction in use-related errors. Throughout the course, topics will be covered as they relate to applicable medical device industry standards (e.g., quality and risk management of medical devices and usability and human factors engineering of medical devices) through lecture activities, examples, case studies, and the overarching design project.

A Practical Experience in Applied Research course in biomedical device development. The placement must be in at least one of the following biomedical engineering research fields: 1) Biomaterials, Tissue Engineering and Regenerative Medicine; 2) Engineering in a Clinical Setting; 3) Nanotechnology, Molecular Imaging and Systems Biology; or 4) Neural/Sensory Systems and Rehabilitation. The practical experience course can be taken in academic research and teaching laboratories, government institutions, health-care facilities, in the industry, or in health-care consulting firms.

A Practical Experience in Applied Research course in biomedical device development, usually over one session for a full-time placement. The placement must be in at least one of the following biomedical engineering research fields: 1) Biomaterials, Tissue Engineering and Regenerative Medicine; 2) Engineering in a Clinical Setting; 3) Nanotechnology, Molecular Imaging and Systems Biology; or 4) Neural/Sensory Systems and Rehabilitation. The practical experience course can be taken in academic research and teaching laboratories, government institutions, health-care facilities, in the industry, or in health-care consulting firms.

The final evaluation of the performance of the student will be conducted by an Evaluation Committee based on a formal Intern evaluation, the Summary report of the student's experiences for each internship period, and an oral presentation of the Summary report. Clinical Engineering Practice is the management of modern health care technology. This course provides practical experience in the practice of clinical engineering. Topics to be covered include in-service education, departmental management, equipment acquisition, equipment control, equipment design, facility planning, information systems, regulatory affairs, safety program, system analysis, and technology assessment/evaluation.

The 'Biopartnering' seminar series is a program require­ment for all MBiotech students — in both the BioPh and DHT streams. BTC1600H and BTC1610H are held in conjunction with one another, meaning all students (regardless of year or program stream) attend the seminar on the same date and time. The seminar is held once per week during the Fall semester, on Tuesday evenings for approximately two hours. It is comprised of both presentations by select speakers from industry as well as student presentations. The course challenges students to provide insights into industry issues that would be seen as a valuable contribution by experts in the area. Each student will participate in a formal group presentation, in their first year, and will complete other academic requirements such as critiques, team mentoring and an individual report in their senior year. The topics presented in this course will range from scientific (latest technologies and research, analysis of pre-clinical and clinical data) to business-oriented issues (e.g., market strategies for pharma and biotechnology products, government regulations, intellectual property, finance, ethics, etc.)

The 'Biopartnering' seminar series is a program require­ment for all MBiotech students — in both the BioPh and DHT streams. BTC1600H and BTC1610H are held in conjunction with one another, meaning all students (regardless of year or program stream) attend the seminar on the same date and time. The seminar is held once per week during the Fall semester, on Tuesday evenings for approximately two hours. It is comprised of both presentations by select speakers from industry as well as student presentations. The course challenges students to provide insights into industry issues that would be seen as a valuable contribution by experts in the area. Each student will participate in a formal group presentation, in their first year, and will complete other academic requirements such as critiques, team mentoring and an individual report in their senior year. The topics presented in this course will range from scientific (latest technologies and research, analysis of pre-clinical and clinical data) to business-oriented issues (e.g., market strategies for pharma and biotechnology products, government regulations, intellectual property, finance, ethics, etc.)

This laboratory-based course introduces fundamental experimental techniques commonly used in biomedical research and provides 'hands-on' experience working with nucleic acids and proteins over an intensive six-week schedule. Students receive a practical overview of key protocols over the first week and are provided with same-day, interactive technical demonstrations in a fully equipped 'wet' laboratory. This is followed by an extended research assignment in which students work in teams towards expressing and isolating a biomedically relevant, recombinant protein. Teams must design an appropriate research strategy, conduct experiments, collect and analyze data, and submit their product with a final report to meet a tight deadline. The course concludes with a final presentation seminar day.

This course is designed to enable students to gain a more in-depth appreciation and understanding of the application of materials science and protein chemistry to the field of biotechnology. We delve into advanced drug delivery and therapeutic strategies, biomaterials in medicine, pharmacology, and drug discovery. We also consider new disruptive technologies as case studies for life science biotechnology students.

Biological, disease, and drug mechanisms are all determined by the three-dimensional arrangement of atoms within biological macromolecules. Therefore, knowledge of molecular structure is fundamental to protein engineering and the development of new therapeutics and vaccines. This course will cover the application of structural biology methods to drug development and biotechnology. Students will be introduced to the modern tools of protein structure determination including Cryo electron microscopy, X-ray crystallography, and NMR through lectures and tutorials. Lectures will focus on theory, techniques, and the advantages and limitations of each method. The applications of these methods to the pharmaceutical and biotechnology industries including protein engineering, target selection and drugability, lead identification and optimization, rational drug design, and drug mechanism of action will be explored through student presentations and discussions. Analytical tools are also a mainstay of drug screening and development. Students will be introduced to some of these tools (PyMol, Autodock), in addition to basic statistical and modelling tools.

This course will introduce students to the development of a wide range of product categories. While the focus will be on drugs, the course will also touch upon medical devices, digital health, big data in health, medical apps, biomarkers, medical marketing, treatment guidelines, screening tools and diagnostics. Understanding clinical trial design and the regulatory pathway through the US FDA is a major focus of the course. Reimbursement is introduced for both drugs and medical devices. Each year, this course is usually able to negotiate some major project opportunities from teaching hospitals students can tackle, to expose them to the clinical world, an important target customer environment of pharmaceutical companies.

This is a half-credit course that introduces students to some of the key aspects of the biopharmaceutical process, with special emphasis on the biotech sector. The course focuses on the fundamental role played by corporate entities in the development of new therapeutic drugs in a highly regulated business environment. Topics covered include biopharmaceutical manufacturing, regulatory approval for drug products and medical devices, setting regulatory standards, quality-by-design, cGMP compliance, risk management, and root cause analysis.

This course will focus on the exploration and understanding of biotechnology as applied to agriculture, natural products, biocontrols, and associated industrial biotechnology. Students will work in teams and each team will present their assigned topics as oral presentations and written assignments. A number of written individual assignments plus an exam will also be evaluated. In the agriculture area, lecture topics include modern approaches to plant breeding, genetically modified organisms (GMOs) and the controversy surrounding them; genomics and its importance in agribiotechnology; nutraceuticals; the use of natural and engineered products for pest and herbicide control; and the use of plants as bioreactors. In the natural products/­​biocontrols/­​industrial biotechnology areas, topics include the use of natural plant products for medicinal purposes; bioremediation of contaminated soils and the applications of biocatalysts as part of the green chemistry movement.

Medical device reimbursement for medical devices is critical for successful product commercialisation. This course discusses the regulatory and reimbursement landscape in Canada and presents a medical device reimbursement framework that can be applied when seeking medical device reimbursement. The framework focuses on the medical device and the reimbursement environment where payment is being sought. The course involves lectures and reimbursement challenges. Teams of students will conduct reimbursement assessments and develop and present reimbursement plans for real-world medical device reimbursement. At the conclusion of the course, students will have the knowledge and tools to build a medical device reimbursement plan.

This course teaches basic programming skills to non-programmers and introduces them to the value of those skills. Students will learn about the various capabilities of the R programming language and participate in discussions about the purpose of programming including task automation and interactive web design. Students will be introduced to elementary data types, control flow and functions as well as functional and object oriented programming. Students will practice approaches to problem solving with computer programs and learn debugging strategies. By the end of the course, students are expected to create a program that helps them solve a problem or perform a task (either self-chosen or assigned) in the context of data science.

This course will introduce students to biostatistics and data science. This course is intended for both students new to the area and those with prior training.

Statistical and data analysis methods covered will start with descriptive statistics and basic univariate tests and continue to more advanced regression models and other topics. The sessions will include lectures and hands-on tutorials that include real-time exercises. It is key that students are able to identify which methods to apply to what kind of data set, the assumptions of the model and how to interpret the output. Special emphasis in the course will be placed on critical thinking around analytical methods to be used.

Problem sets will be focused on the application of statistical modelling to the biological and health sciences. This may include laboratory or clinical data sets. Your defence of your analysis, as well as critiquing the work of others, will require you to draw upon some of your knowledge of biology and the health sciences.

A key component of the course will involve programming in R in order to conduct statistical analysis. Students will have both individual and team assignments to provide practice coding in R, one of the main languages used today in performing statistical analysis. Comfort with R will be helpful in learning other languages in the future in a statistical context. Off-the-shelf software, while more convenient, may not be available in the work environment you find yourself in and certain tests you may need, may not be available in any such software. Thus, learning to code is the best path forward for future practitioners of data science.

In this course, we focus exclusively on the dominant role of biologic therapies in modern medicine. In 2020, six of the top ten drugs by revenue were molecules of biologic origin, namely those manufactured primarily by biosynthetic rather than chemical means, with sales of the top selling therapy, the anti-TNF-alpha monoclonal antibody adalimumab, falling just shy of the US$20 billion mark. The lucrative preeminence of biologics is set to continue, bolstered by the introduction of innovative molecular delivery strategies, such as antibody-targeted conjugates, fragments and fusions, as well as by the robust staying power of market leaders. The latter phenomenon is an inevitable consequence of the higher-than-usual regulatory hurdles faced by conventional generic manufacturers seeking to make biosimilars: intended copies of off-patent biologics that, having undergone a strict comparability exercise, are approved by regulatory agencies such as the EMA and the FDA.

This course will survey this changing landscape within an historical framework and will highlight critical scientific and process parameters unique to biologics, that set them aside from conventional small-molecule medicines, including their molecular architecture and mechanisms of action, manufacturing considerations, analytical and functional lot release assays and clinical trial design. We will explore some of the pitfalls by examining a roster of clinical case studies. The capacity of payers to afford these increasingly high-cost therapies in the face of current economic trends will be discussed.

The broad goals of the course are as follows: a detailed understanding of the complexities associated with biologic drugs; a broad familiarity with biologics manufacturing and its inherent variability; a critical understanding of the aspects of biosimilarity; and a familiarity with the clinical implications emerging from the use of biologics.

This graduate course takes students with a basic background in statistics and equips them to tackle massive data sets in health. The focus will be on advanced statistical tests in machine learning and assemble such tests by accessing and validating publicly available code in the R programming language and creating their own code as needed. Students will also learn additional techniques pertaining web scraping, working with unstructured data, data cleaning and data governance building upon the course Data Science in Health I. The course will emphasise creative approaches to analyzing data and how to be critical of misleading analysis. Each class will involve both lecture and weekly tutorial assignments. The major project for the course will involve a large health data set that teams will compete to analyze.

In this course, we discuss data analytics and visualizations using Tableau Desktop and Tableau Prep software. We survey methods in data cleaning and prepping through ETL (Extract, Transform, Loading). We examine best practises in developing dashboards and understand how to tell a story with health and biological data. Our overall goal is to provide a foundation for using Tableau in data-driven decision making in the life sciences. Visualization with Tableau will be supplemented with R coding techniques students have learned from previous courses.

Upon completion of this course, students will be able to frame various classes of healthcare problems as analytics problems using Tableau, to appropriately identify data sources and build visualizations from them. Students will get practice in planning and developing interactive dashboards that help answer analytical problems and provide data accessibility to a non-technical audience.

This course will introduce students to the development of a wide range of product categories and topics pertaining to the commercialisation of health­care products. The course will touch upon medical devices, wearable technology, clinical trial design, biopharmaceuticals, digital health, big data in health, medical apps, biomarkers, medical marketing, treatment guidelines, screening tools, diagnostics, and social listening. Understanding clinical trial design and the regulatory pathway through the US FDA is a major focus of the course. There will be an emphasis on digital health regulation. The course will also introduce students to 3D printing and its applications in health care. Students will be required to get familiar with the digital modelling tool Blender. Students will explore segmentation of physicians based on their clinical practices, drawing upon some of their data science training. The major project for the course will focus on the use of social listening for a product to derive insights into different issues based on the expressed interests of an industry partner. Students will be required to develop a strong level of mastery with the social listening tool Brandwatch and combine that with their foundational knowledge in the course, along with their data science training, to derive insights.

This is an advanced course in machine learning that is focused on the application of neural networks in a health context. The course assumes a strong foundation to create machine learning models in the coding language R. Basic foundations of neural networks are reviewed. Students will learn about the limitations and the appropriate use of neural networks by working on health and biological related data sets.

This course builds on the foundational programming skills acquired in the introductory course ("Coding in the R Language"; BTC1855H), focusing on advanced techniques for data handling and analysis in the context of digital health using Python-based programming tools. Students will learn how to create interactive dashboards, handle missing data, perform advanced data censoring techniques, and work with real-world biometric and clinical datasets. There will be an emphasis on making sure the data sets used are "dirty" ( i.e., contain errors, inaccuracies, or inconsistencies that can negatively affect the quality and reliability of analysis, processing, or decision-making) to reflect common clinical trial situations. Applications will focus on healthcare related information disseminated from a website related to digital health, product information in healthcare, website design and data collection, regulatory compliance, and social listening in health as a data gathering tool from web traffic.

This new elective course looks at modern developments in neuroscience and cognitive psychology, that point to new uses of technology to enhance brain function. The course builds its foundation with a neuroanatomy primer, as well as an introduction to the cognitive neuroscience of daydreaming. How can technology be used to aid attention to avoid critical errors? How can better sleep and acts of creativity be supported from emerging technologies? In what way can video games be an aid and a burden to brain function? The major project for the course will explore digital biomarkers for cognitive performance.

This course has two parts that challenge students to think about the commercialisation of digital health products. In the first half of the course students will build upon their training in digital health regulation by doing a reverse engineering assignment on a technology (e.g., health software). Students will also be introduced to detecting hype around a health technology and to distinguish this activity from more meaningful indicators of validation. Human factor engineering will be introduced in the context of basic psychology and its application to usability analysis and product design. The first half of the course involves individual student presentations that forecast the future of a digital health product and provide a critical analysis of the technology. The second half of the course challenges the students to think about creating their own digital technology. Special emphasis will be placed upon developing a compelling use case, regulatory strategy, and market analysis. The second half of the course shifts to independent study by student teams that is supervised by the instructor.

This series of centrepiece courses is designed to grant our students a more in-depth appreciation and understanding of the biotechnology and biopharmaceutical industry in a corporate and/or industrial setting, and to apply their knowledge and skills in a real-world context. Students are required to complete two 4-month full-time Work Term placements that are arranged by the course coordinator to ensure that the role, responsibilities, and activities are at a graduate level. Credit-granting responsibilities reside with the course instructor, based on assignments and feedback from students' Work Term supervisors.

Required preparatory exercises and assignments must be completed in the Summer and Fall sessions, leading up to the start of the placement in Winter/Spring, in order for students to qualify for Work Term I. These preparatory requirements can involve résumé workshops, one-on-one meetings with members of the MBiotech team, attendance at the annual Career Day, and more.

Students in Work Term II may continue with the same employer from Work Term I, or alternatively with a new employer or department. Students' performance and their work experiences is evaluated in a manner similar to that for Work Term I.

Note: BTC1920Y Work Term III is an optional elective course that extends the placement experience to a full 12 months' duration. Students taking Work Term III share their experiences by means of a mandatory Networking Night component in late November.

Students receive credit/no credit grades for all three courses.

This series of centrepiece courses is designed to grant our students a more in-depth appreciation and understanding of the biotech­nology and biopharma­ceutical industry in a corporate and/or industrial setting, and to apply their knowledge and skills in a real-world context. Students are required to complete two 4-month full-time Work Term placements that are arranged by the course coordinator to ensure that the role, responsibilities and activities are at a graduate level. Credit-granting responsibilities reside with the course instructor, based on assignments and feedback from students’ Work Term supervisors.

Required preparatory exercises and assignments must be completed in the Summer and Fall sessions, leading up to the start of the placement in Winter/Spring, in order for students to qualify for Work Term I. These preparatory requirements can involve résumé work­shops, one-on-one meetings with members of the MBiotech team, attendance at the annual Career Day, and more.

Students in Work Term II may continue with the same employer from Work Term I, or alternatively with a new employer or department. Students’ performance and their work experiences is evaluated in a manner similar to that for Work Term I.

Note: BTC1920Y Work Term III is an optional elective course that extends the placement experience to a full 12 months' duration. Students taking Work Term III share their experiences by means of a mandatory Networking Night component in late November.

Students receive credit/no credit grades for all three courses.

This series of centrepiece courses is designed to grant our students a more in-depth appreciation and understanding of the biotechnology and biopharmaceutical industry in a corporate and/or industrial setting, and to apply their knowledge and skills in a real-world context. Students are required to complete two 4-month full-time Work Term placements that are arranged by the course coordinator to ensure that the role, responsibilities and activities are at a graduate level. Credit-granting responsibilities reside with the course instructor, based on assignments and feedback from students' Work Term supervisors.

Required preparatory exercises and assignments must be completed in the Summer and Fall sessions, leading up to the start of the placement in Winter/Spring, in order for students to qualify for Work Term I. These preparatory requirements can involve résumé work­shops, one-on-one meetings with members of the MBiotech team, attendance at the annual Career Day, and more.

Students in Work Term II may continue with the same employer from Work Term I, or alternatively with a new employer or department. Students' performance and their work experiences is evaluated in a manner similar to that for Work Term I.

Note: BTC1920Y, Work Term III is an optional elective course that extends the placement experience to a full 12 months' duration. Students taking Work Term III share their experiences by means of a mandatory Networking Night component in late November.

Students receive credit/no credit grades for all three courses.

This course introduces students to the basic skills and concepts needed to become an effective member of an organization. It focuses on (1) team working skills, (2) fundamental managerial skills, and (3) career management skills. The course is participative in its design and requires students to apply the material in the course. It provides the first opportunity for a team approach to problem solving and will provide a realistic preview of the workplace.

This course will be used to define and organize groups of students who will work in teams to complete the subsequent laboratory modules.

This foundational course introduces students to a broad range of the critical managerial concepts that are required to operate sucessfully in today's biotechnologically focused organizations. Topics covered include forms of business ownership, an introduction to financial statements, auditor reports, financial statement analysis, ratio analysis, time value of money, net present value, internal rate of return, projected statements, marketing math, market segmentation, product positioning, the marketing mix, pricing decisions, channel strategies, customer value propositions, competitive strategies, marketing in the age of artificial intelligence, as well as some aspects of strategic manage­ment and organis­ational alignment. Theory and application are combined through the use of readings, case studies, in-class discussions and presentations, as well as a team project.

This course introduces students to the fundamentals of economics and strategic management. Throughout the course, we will attempt to answer a fundamental question posed by management scholars: how is it that some firms are able to repeatedly and consistently achieve great results, while others fail and crash out of the market? In search of an answer, we'll explore a variety of decisions firms make, including pricing, product variety and scope, motivation of employees, and interaction with competitors. The course features a combination of lecture and case discussion; course readings include textbook excerpts, business press, and academic articles.