GCSRT Program | Electives

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Electives

PROGRAM CURRICULUM: JUNE 21, 2014 TO JUNE 6, 2015

Electives: A, B, and C
 

A-ELECTIVE COURSES

A101 - Career and Leadership Development
This course examines different aspects of working and leading a team. Lectures will discuss the need to manage a talented group of people effectively, pilot successful collaborations within and outside a group, navigate the complexities of the institution, and manage the inevitable conflicts that arise in a high-stakes environment.

A102 - Ethics and Regulation
This course reviews some common challenges in the conduct and review of biomedical human subjects research. Lectures examine the history and evolution of ethical codes and regulations; the role and responsibility of physicians as investigators; the preparation of research protocol applications and informed consent documents; and the challenges of conducting research involving children and adolescents.

A103 - Biostatistical Computing
The ability to import data into a statistical package from a database or excel spreadsheet is considered essential in clinical research. Introductory lectures will consist of teaching the basic functions of the Stata program, including learning key commands, creating a do-file, getting data into the shape needed for analysis, and checking for errors. More advanced lectures will focus on using Stata for regression and survival analysis. Lastly, there will be lectures on developing polished manuscript-ready tables and figures.

B-ELECTIVE COURSES

B101 - Survey Design
This course covers the crafting of survey questions, the design of surveys, and different sampling procedures that are used in practice. longstanding basic principles of survey design are covered. Statistical aspects of analyzing complex survey data will be featured, including the effects of different design features on bias and variance. Different methods of variance estimation for stratified and clustered samples will be compared. The handling of survey weights will be discussed. The capabilities of Stata for such analyses will be emphasized.

B102 - Drug Development, Drug Regulation, and Drug Safety
Drug development, drug regulation, and drug safety are complex and highly interrelated activities that involve bringing a pharmaceutical, diagnostic, or device discovery to approval and market. Seminar topics include: How are Drugs Discovered and Developed, Case Study of the Pre-clinical Stages of Drug Development, Moving a Compound Through the Drug Development Process, Good Manufacturing Practices--a Global Perspective, and Overview of Diagnostic Device Development. overviews of drug regulation focusing on the activities of the u.S. Food and Drug administration and european medicines agency are also covered. lastly, lectures on drug safety include the following topics: Methods in Drug Safety Monitoring and Drug Safety in the Pre- and Post-approval Phases. The course is largely webinar-based and consists of discussions by experts from academia, industry, and government with years of hands-on experience with large and small pharmaceutical, biotechnology, and related organizations.
 

C-ELECTIVE COURSES

C101 - Principles and Practice of Clinical Trials
This course focuses on how to conduct clinical trials effectively. The course content includes lectures on study design and implementation including different designs, endpoints, study protocol, study population, recruitment, baseline assessment, randomization, stratification, and blinding. other key issues that are covered include data analysis and sample size and power, treatment regimens and follow-up procedures, and monitoring and interim analysis plans. Lastly, other areas covered include data management and ethical issues, including protection of human subjects.

C102 - Introduction to Advanced Quantitative Methods
This course will provide students with the application of advanced quantitative methods as they pertain to T4 translational research. Topics include an overview of comparative and cost-effectiveness research, metaanalysis, quasi-experimental designs including instrumental variables and marginal structural modeling, propensity scores, and time-series analysis.