CTS 6010 is intended for beginning investigators who want to learn how to design clinical and translational research. The course is taught online in a live, small group seminar-based format. Students will take turns presenting materials to the group and leading the discussion. There will be assigned readings and homework. Each student will prepare a full research protocol. The topic of research will be selected by the student. The protocol format will be consistent with the Research Strategy section of a National Institutes of Health (NIH) Small Research Grant (R03) or equivalent program. Course objectives include learning how to discuss, review, and design research. Successful completers of this course will know how to evaluate the strengths and weaknesses of research designs common to clinical and translational research, critically evaluate research protocols, and write a rigorous, original research protocol, including posing an important research question, choosing an appropriate research design, identifying appropriate subjects, designing measurements and developing plans to collect and analyze data, estimating sample size requirements, and preparing a project timeline.
Instructor: Amanda Kennedy, PharmD, BCPS

This novel multidisciplinary course, presented in the fall semester, explores a societal issue, such as drug addiction or pandemics, at all levels from basic science origins through animal models, early translation to humans, large-scale clinical trials, initial introduction and marketing, to a consideration of the problems of integration into routine practice, late discovery of adverse effects, and cultural and economic barrier to diffusion.
Instructor: Connie van Eaghen, DrPh

This course is designed to provide basic analytical skills for clinical and translational research. Prior clinical research experience is helpful but not required. The course assumes no prior statistical experience and mathematics is kept to a minimum, requiring comprehension at the high school algebra level. Content includes basic data considerations, descriptive statistics, hypothesis testing, and bivariate analyses. Classes provide a small group interactive seminar approach with "hands on" analyses using the statistical software package STATA. Analyses of ample datasets are completed on a weekly basis. Specific datasets are provided, but students are encouraged to bring their own datasets to use throughout the course. Lectures are available online.
Instructors: Richard Pinckney, MD, MPH and Peter Callas, PhD

This course is designed to develop communications skills for writing, editing, and presenting clinical and translational science. The course prepares students to master five presentation formats: abstracts, posters, brief oral presentations, full-length presentations such as Grand Rounds or seminars, and research reports/journal articles. The course explores American Medical Association standards for publication style and terminology [Iverson 1998] using a text written by experienced clinical investigators [Browner 1999]. The course uses a three-session cycle for each of the five formats. The ethics of publication and the potential conflicts and pitfalls of authorship are also covered.
Instructor: Mark Fung, MD

This course is designed for new investigators and others wishing to learn the ethics, regulatory requirements, and practical considerations for undertaking a clinical research project. Example topics include: Protecting human subjects; Research with vulnerable populations; Roles, rules, and mechanics of the IRB; Recruitment, compensation, and consent of subjects; Data safety and monitoring; Planning and carrying out surveys and interventions; Conflicts between research and care for individual patients; and, Legal issues in clinical research-authorship, collaboration and conflict of interest. Students will acquire the knowledge and skills to present and defend a proposal before an Institutional Review Board (IRB). The class functions as a mock IRB as it considers proposals and problems designed to illustrate many facets of conducting research. Students present their own protocols before the "Board" as a final class project.
Instructor: Gail Rose, PhD

This intermediate course builds upon the descriptive and bivariate statistical methods presented in Analyzing Clinical Research. Emphasis is on developing the foundational skills and knowledge for using regression analytical techniques based on the correlational aspects of clinical data. The conceptual and applied applications of correlational and regression analyses to clinically relevant research datasets are the focus of the course while keeping mathematics to a minimum of basic college-level algebra. Specific datasets are provided along with encouragement for students to incorporate their own research datasets into the course. Class assignments involve actual computer analyses illustrating the concepts discussed in class while allowing students the flexibility of choosing datasets and variables that are of specific interest.
Instructors: Richard Pinckney, MD, MPH and Peter Callas, PhD

The Certificate in CTS is our 18-credit-hour core curriculum designed for scientists, health care professionals, and scholars in other fields (e.g., ethics, business, engineering, law) who are seeking to broaden their horizons in CTS.

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The M.S. degree is a 30-credit-hour program designed for individuals who desire more intensive exposure to focused areas in CTS. Choose from these three master’s program options:

• The Non-Concentration, Course-based Master’s requires a capstone project. It is the only option that is 100% online, and that can be completed in one year when studying full-time.
• The Concentration in Research Management requires a research internship.
• The Concentration in Investigation requires a thesis. Students selecting the thesis option will propose and conduct research under the supervision of a research advisor and prepare and publicly defend a thesis. 

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The Ph.D. in CTS is a 75-credit-hour program designed for individuals who wish to become independent investigators. Students applying to the Ph.D. program must have a source of funding, a UVM Research Advisor, and an environment in which to conduct research as part of the application.

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