DHT • Curriculum Overview

dhtMBiotech’s Digital Health Technologies (DHT) curriculum comprises both required courses that all students take and elective courses that students choose to take to meet their elective credit requirement, or simply out of interest.


Credit Requirements

Students enrolling in DHT steam of MBiotech commencing May 2022 are required to complete 9·5 graduate course credits over a 24-month period on a full time basis. These 9·5 credits comprise the following—

  • 10 Science courses (0·5 credits each, for a total of 5·0 credits)
  • 3 Business courses (0·5 credits each, for a total of 1·5 credits)
  • 2 Work Term courses (1·0 credit each, for a total of 2·0 credits)
  • Electives (1·0 credits)

Course calendars for active classes compatible with Apple and Google Calendars can be downloaded by clicking these icons. How? ›› ››

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 Graduation requirements are changing. Students commencing the Program prior to May 2022 need only complete 9·0 graduate course credits in order to graduate.


Our Required Courses (R)


 YEAR 1

Seminar Series (BTC16x0)
BTC1600H  Biopartnering I { Sep‑Dec  bar-1600 cal googlecal
Digital Health Series (BTC18xx)
BTC1842H  Medical Device Reimbursement { May‑Jun  bar-1842 cal googlecal-grey
BTC1859H  Data Science in Health I { May‑Jun  bar-1859 cal googlecal-grey
BTC1877H  Data Science in Health, Part II { Sep‑Dec  bar-1877 cal googlecal
BTC1882H  Digital Ethnography in Health { Jan‑Apr  bar-1882 cal googlecal-grey
BTC1895H  Introduction to IT Consulting & Web Design Jan‑Apr  bar-1895 cal googlecal-grey
Business Series (BTC20x0)
BTC2000H  Effective Management Practices { May‑Dec  bar-2000 cal googlecal
BTC2010H  Fundamentals of Managerial Concepts { Sep‑Dec  bar-2010 cal googlecal
Biomedical Series (MSC201x)
MSC2011H  Special Topics in Biomedical Communications { May‑Aug  bar-2011 cal googlecal-grey
MSC2019H  Information & Data Visualization in Science & Medicine { Jan‑Apr  bar-2019 cal googlecal-grey

 YEAR 2

Seminar Series (BTC16x0)
BTC1610H  Biopartnering II { Sep‑Dec  bar-1600 cal googlecal
Digital Health Series (BTC18xx)
BTC1899H  Digital Health Technology { Sep‑Apr  bar-1899 cal googlecal
Work Term Series (BTC19x0)
BTC1900Y  Work Term I { May‑Aug  bar-1900 cal googlecal-grey
BTC1910Y  Work Term II { Sep‑Dec  bar-1900 cal googlecal-grey
Business Series (BTC20x0)
BTC2030H  Management of Technological Innovation { Jan‑Apr  bar-2030 cal googlecal-grey


The Electives (E)

Digital Health Series (BTC18xx)
BTC1889H  Deep Learning in Health Jan‑Apr  bar-1889 cal googlecal-grey
Work Term Series (BTC19x0)
BTC1920Y  Work Term III { Jan‑Apr  bar-1900 cal googlecal-grey
Business Series (BTC20x0)
BTC2040H  Change Management { Jan‑Apr  bar-2040 cal googlecal-grey
Special Topics Series (BTC21x0)
BTC2120H  Decision Analytics in Business, Healthcare & Management { Jan‑Apr  bar-21x0 cal googlecal-grey
IMI Series (IMIxxxx)
IMI3001H  Biocommercial­isation I: Analysis of Technology Driven Innovation { Sep‑Dec  bar-imi cal googlecal
IMI3003H  Biocommercial­isation II { Jan‑Apr  bar-imi cal googlecal-grey


Course Descriptions

All courses offered in the DHT stream are described in this section.
 

flag-2011MSC2011H Special Topics in Biomedical Communications: Coding in R Language { Year 1 }
Session: Summer
Instructor: Sebnem Kuzulugil
Credits: 0·5 (R)

Course Description:
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 reasonable problem or perform a task in their own domain of study.

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flag-1842BTC1842H Medical Device Reimbursement { Year 1 }
Session: Summer
Instructor: Mark Smithyes
Credits: 0·5 (R)

ether-1842
1842First use of ether in surgery by Long.

Course Description:
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.

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flag-1859BTC1859H Data Science in Health I { Year 1 }
Session: Summer
Instructor: Nicholas Mitsakakis
Credits: 0·5 (R)

pasteur-1859
1859 • Pasteur uses his col de cynet apparatus to disprove ‘spontaneous generation’ theory.

Course Description:
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.

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flag-2000BTC2000H Effective Management Practices { Year 1 }
Sessions: Summer & Fall
Instructor: Ann Armstrong
Credits: 0·5 (R)

Course Description:
This course introduces students to the basic skills and concepts needed to become an effective member of an organisation. 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 work place.

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

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flag-1877BTC1877H Data Science in Health, Part II { Year 1 }
Session: Fall
Instructor: Nicholas Mitsakakis
Credits: 0·5 (R)

osteotome-1877
1877 • William Macewen invents the osteotome, enabling bone grafts.

Course Description:
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 analysing 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 analyse.

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flag-2010BTC2010H Fundamentals of Managerial Concepts { Year 1 }
Session: Fall
Instructor: Kevin Yousie
Credits: 0·5 (R)

rna_vaccine
2010Derrick J. Rossi, former UofT alumnus, founds Moderna, Inc.

Course Description:
This foundational course introduces students to a broad range of the critical managerial concepts that are required to operate success­fully in today’s biotechnologically focused organisations. Topics covered include forms of business ownership, an introduction to financial statements, financial statement analysis, time value of money, marketing management, market segmentation, product positioning, the marketing mix, pricing decisions, channel and marketing communications management, as well as some aspects of organisational behaviour and strategic management. Theory and application are combined through the use of readings, case studies, presentations and a group project.

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flag-1600BTC1600H Biopartnering I { Year 1 }
BTC1610H Biopartnering II { Year 2 }
Session: Fall
Instructor: Duncan Jones
Credits: 0·5 (R)

Course Description:
The ‘Biopartnering’ seminar series is a program requirement for all MBiotech students—regardless of program stream. 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 student presentations as well as presentations by speakers from industry and academic institutions. All students registered in the Program are expected to attend all seminars in each of their two years and to participate in discussions of the topics that are presented during their residency in the Program. Each student will participate in at least one formal group presentation, usually in their first year, and will complete other academic requirements (such as critiques or team mentoring in the senior year) throughout the series. 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.).

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flag-1882BTC1882H Digital Ethnography in Health { Year 1 }
Session: Winter
Instructor: Jayson Parker
Credits: 0·5 (R)

manhattan-1882
1882Vladimir Bekhterev publishes Provodiashchie puti mozga (‘The Conduction Paths in the Brain and Spinal Cord’), beginning to note the role of the hippocampus in memory.

Course Description:
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 healthcare. 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.

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flag-1895BTC1895H Introduction to IT Consulting & Web Design { Year 1 }
Session: Winter
Instructor: TBC
Credits: 0·5 (R)

röntgen-1895
1895 • Wilhelm Röntgen discovers X-rays and become an inaugural Nobel Laureate

Course Description:
Information Technology (IT) Consulting is a growing profession that embodies the use of computer-supported collaborative tools in the execution of business functions. In this course students engage with the principles of Computer Supported Co-operative Work (CSCW) through an experiential opportunity to work with a real client. Students create an IT Consulting company and take on the role of consultants, learning core skills (soft and hard) necessary for this profession, including client management, communication, ideation, analysis and solution development, project management, presentation skills and web design. Using case studies we discuss consulting lessons learned and problems to avoid within the context of industry best practices. Student teams will also advance their case by citing relevant best in class examples.

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flag-2019MSC2019H Information & Data Visualisation in Science & Medicine { Year 1 }
Session: Winter
Instructor: TBC
Credits: 0·5 (R)

Course Description:
This course addresses the fundamental principles of information visualisation, including a discussion of human visual perception, cognition and approaches to graphic representation. This course will include weekly lectures and seminars, required readings, student presentations and a term paper. Topics will include the accurate representation of numerical and statistical data, innovative approaches to visual representation and appropriate use of design elements for clarity and legibility. Practical application of course material will require students to develop visualisations that yield insight into complex biomedical subject matter and successfully communicate to a range of audiences.

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flag-1900BTC1900Y / 1910Y / 1920Y Work Terms I, II & III { Year 1 + Year 2 }
Preparation: Fall & Winter
Sessions: Year-Long (begins Summer)
Instructor: Leigh Revers
Coordinator: Nazeem Shamsuddin
Credits: 2·0 (R) + 1·0 (E)

Course Description:
The course is designed to enable the students to gain 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 an industry setting. Students are expected to be complete two four-month full-time work terms that have been coordinated 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, who seeks input from the course coordinator.

Required preparatory exercises and assignments must be completed in the Summer and Fall sessions, leading up to the start of the work term in Winter, in order for students to qualify for the first Work Term itself. These preparatory requirements can involve resume workshops, one-on-one meetings with the Placement Team, attendance at the annual Career Day and more.

Students in Work Term II may continue with the same employer from their first work term or with a new employer or department. Evaluation of students’ performance and their work experiences will be done in a manner similar to that of the first work placement. Students will receive a credit/no credit grade for their second work term.

Note: BTC1920Y, Work Term III is an optional elective course.

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flag-1899BTC1899H Digital Health Technology { Year 2 }
Session: Fall & Winter
Instructor: Jayson Parker
Credits: 0·5 (R)

aspirin-1899
1899 • Felix Hoffmann & Arthur Eichengrün patent Aspirin.

Course Description:
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.

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flag-2030BTC2030H Management of Technological Innovation { Year 2 }
Session: Winter
Instructor: Ruben Gaetani
Credits: 0·5 (R)

Course Description:
In this course, we will define technological innovation as the process of leveraging new ideas to create economic value and deliver this value to shareholders, employees, consumers, and our society at large. This process involves critical strategic choices that are common to most organisations, from small startups to large established companies: What is the best way to bring an idea to the market, and to arrange production and distribution? How should we redesign our internal organisation, as well as the system of partnerships and relationships with external players? Should we redefine our vertical and horizontal boundaries, for example by outsourcing some activities or entering new geographical markets? Throughout the course, we will refine our ability to approach and find the best answer to these (and many other) questions. Using an applied and discussion-based method, we will learn how to effectively convert a creative idea into a valuable innovation.

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flag-2040BTC2040H Change Management { Elective }
Session: Winter
Instructor: Ann Armstrong
Credits: 0·5 (E)

Course Description:Managing change well has long been considered a key leadership skill. Many organizations are experiencing significant rates of change now! Knowing about change management will provide you with a significant competitive advantage in your careers.
 
In this course, you will learn about some current models of change management as well as examples of change management done well and not. The course is interactive. Central to the course and your learning is participation in a sophisticated change simulation, used by universities, corporates, and non-profits, to let you experience change. You will create—and implement—a change plan that will help you develop not only your understanding of change models but will provide you with tactics that you can use in any future change management work.

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flag-1889BTC1889H Deep Learning in Health { Elective }
Session: Winter
Instructor: Nicholas Mitsakakis
Credits: 0·5 (E)

russian-flu_1889
1889 • The Russian ’flu pandemic begins in modern-day Uzbekistan, now thought to be a human coronavirus.

Course Description:
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.

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flag-imiIMI3001H Biocommercial­isation I: Analysis of Technology Driven Innovation { Year 1 + Year 2 }
Session: Fall
Instructors: Duncan Jones & Tim Lee
Credits: 0·5 (E)

Course Description:
In this course through a series of lectures and case discussions, students learn about the formation, financing, and management of early-stage ventures especially as it relates to the (bio)technology and associated medical device space. Topics include opportunity identification and assessment, preclinical and clinical phases, regulatory procedures and pathways, legal issues including patents and venture finance. Students will each be required to select a young, publicly-traded company in which to complete an in-depth analysis, presentation and report.

Classes will be held every Monday from 6:30-8:30PM commencing on 13-Sep, 2021 and ending on 13-Dec, 2021. There will be no class on Monday, 11-Oct (Thanksgiving) nor on Monday, 15-Nov (Reading Week). Recommended preparation for this course: Three essays by Paul Graham, http://www.paulgraham.com/

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flag-imiIMI3003H Biocommercial­isation II { Year 1 + Year 2 }
Session: Winter
Instructors: Duncan JonesTim Lee
Credits: 0·5 (E)

Course Description:
This course is a compliment to IMI3001, in which student teams are given the opportunity to learn more about the issues and opportunities facing early-stage (bio)technology ventures through direct experiences working on real projects for select early-stage firms within the community. This experiential learning involves working in teams on select, negotiated work packages in conjunction with the company founders in addition to mentoring by the instructors or TAs. This project work is supplemented with lectures covering practical and applied topics such as project management, client communications, research methods, patent searching and analysis, market research, competitive intelligence and financial modelling. The final assessment involves a presentation and client report.

Classes will be held Monday from 6:30-9:30PM commencing on 10-Jan, 2022 and ending on 4-Apr, 2022. There will be no class on Monday, 21-Feb (Family Day).

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LEGEND: (R) Denotes a required course for graduation; (E) denotes an elective course.

Follow our step-by-step guides for subscribing to MBiotech’s live course calendars.

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Apple Calendar on iPhone & iPad

1 In your iOS browser, open this page and tap-and-hold the desired Apple Calendar icon.
2 Chrome users select Copy Link. Safari users scroll down and select Copy.
3 Open your calendar app of choice in iOS.
4 For Apple’s Calendar app, at the bottom of the screen, select Calendars and then choose Add Calendar followed by Add Subscription Calendar. Paste the copied link into the Subscription URL field and tap Subscribe.
Calendars added in this manner will now appear in the Apple Calendar app on your iPhone or iPad.

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calOption 2
Apple Calendar on macOS

1  On your Mac, using your browser, open this page and right-click on the desired Apple Calendar icon. Chrome users select Copy Link Address. Safari users select Copy Link.
2  On your Mac, launch Apple’s Calendar app.
3 From the File menu, select New Calendar Subscription… or type  + + S on the keyboard.
4 Paste the copied link into the Calendar URL field and click Subscribe.
Calendars added in this manner will now appear in the Apple Calendar app on your Mac and can be synced to your mobile devices.

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googlecalOption 3
Google Calendar on Desktop, iOS Device or Android

1 On your Mac or PC, using your browser, open this page and right-click on the desired Google Calendar icon. Chrome users select Copy Link Address. Safari users select Copy Link.
2  Open a new tab or window and log in to your Google account online.
3  Click Calendar from the Google apps palette at the top right of the browser window.
4  In the left-hand menu, click ‘+’ next to Other Calendars and choose From URL.
5 Paste the copied link into the URL of calendar field and click Add calendar.
Calendars added in this manner will now appear in the Google Calendar app on your mobile device.

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Option 4
Microsoft Outlook on Desktop, iOS Device or Android

Direct subscriptions to our calendars are currently not recommended. Subscribed calendars may be successfully added in the browser version of Outlook 365 by clicking Add Calendar on the calendar page, followed by Subscribe from web, but real-time synchronisation with Outlook in this manner has not proved reliable. Our fully tested work-around is as follows:
1  Follow the steps in Option 3, above, and subscribe to all of the desired calendars in Google Calendar using your browser.
2  Open a new browser window and log in to your UTmail account online.
3  Click Calendar icon from the pallet on the left (second icon down).
4  Click Add Calendar in the calendar pane, followed by Add personal calendars, in the pop-up dialogue window.
5  Click on Google to add synchronised calendars from your Google account.
All of your Google calendars will now be displayed in Outlook 365 and in your Outlook app on your mobile device.

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