Master of Science in Clinical Research (MSCR) Course Descriptions
MSCR 761 Introduction to Clinical and Translational Science [CTS] (2 credits)
This course introduces the fundamentals of human subjects research in CTS. It begins with the building blocks of hypothesis development, population and study sample selection, defining study measures, and power and sample size calculations. The course then conducts a broad survey of observational and experimental study designs, including systematic review and meta-analysis. Throughout the semester the team science aspect of CTS is emphasized with students working together in groups in organized class and on-line activities.
MSCR 530 Analytic Methods for Clinical and Translational Research I (3 credits)
Epidemiologic methods are covered for studying the determinants and distributions of health outcomes in human population with an emphasis on hypothesis formulation; causal inference; experimental vs. observational research; measurement; detection of interaction; study design (e.g. cohort, cross-sectional, case-control); evaluation of the sources and direction of bias; control of confounding factors; random error (frequentist vs. Bayesian approach); and epidemiology in clinical settings (screening, diagnosis, and therapy).
MSCR 500 Introduction to Biostatistics (3 credits)
Provides an introduction to applied biostatistical data analysis. Topics covered include numerical and graphical descriptive statistics, one-and two-sample inferences for means and proportions, simple and multiple linear and logistic regression, and one- and two-way analysis of variance. After completing the course, students are expected to be able to independently and rigorously implement the covered methods and to interpret results for standard analyses.
MSCR 533 Data Management (2 credits)
Provides an introduction to concepts in data management and analysis using SAS statistical software on personal computers. Topics covered include importing data, in-stream data entry, variable manipulation, subsetting, concatenating and merging data sets. Data management principles for maintaining data quality are presented. The course is coordinated with MSCR 500, and SAS procedures used to implement the statistical methods from that course are also presented. After completing the course, students are expected to be able to independently manage small or moderately large data sets and to analyze the data using SAS.
MSCR 591 Community Engagement in Clinical and Translational Science (1 credit)
Led by Morehouse School of Medicine and Emory University faculty, this course is an introduction to the concepts, methods, and issues involved in research with communities. Special emphasis is given to social and behavioral science concepts and methods; principles and historical roots of community engagement; clinical and translational research partnerships, multidisciplinary research collaborations; ethical issues; and practical considerations in planning, implementing, evaluating, and disseminating community-engaged research. Case studies and course activities are shaped to accommodate students with diverse interests in health disparities, communities, and/or translational research. Students are assumed to have a general research and clinical background, but the course emphasizes research theory and concepts with a goal to encourage thoughtful and effective community-based research collaborations.
MSCR 595 Health Services Research (1 credit)
This course provides students with an understanding of the nature, methods, scope, magnitude, and impact of Health Services Research (HSR). Students gain an appreciation for the importance and relevance of HSR in improving healthcare delivery as well as key tools employed in HSR and areas of funding. Classes are designed to demonstrate the broad scope and multi-disciplinary nature of HSR by providing lectures from experts on a wide variety of topics that also provide practical examples of HSR.
MSCR 534 and MSCR 534 (Lab) - Analytic Methods in Clinical and Translational Science II (3 credits)
Continuation from analytic epidemiology and data management courses in the first semester. Aids students in developing analytic skills necessary to model data collected from experimental and observational studies in order to assess the role of multiple risk factors in association with health outcomes. The focus is on linear regression, logistic regression, and survival analysis. The goal is to provide a foundation for understanding the multivariable nature of human health events and develop the critical reasoning to apply these skills towards an overall analytic approach.
MSCR 536 Analysis of Clinical Research Data (2 credits)
Provides hands-on experience in the analysis, interpretation, and presentation of clinical research data. Topics covered include methods for data collection, data management and data cleaning in SAS, overview of descriptive and multivariable analysis techniques, strategies for addressing missing data, and the writing and communication of science in the format of a peer-reviewed manuscript and an oral, in-class scientific presentation. The goal is for the student to reach a level of skill with data collection, data analysis, and data presentation to begin and successfully complete the analysis and presentation of thesis research data.
MSCR 509 Overview of High Dimensional Data Analysis (2 credits)
To introduce modern bioinformatics techniques to researchers and practitioners, including statistical and computational techniques for the analysis of high dimensional data. This course will emphasize the statistical and computational concepts behind these techniques, and illustrate their applications to the medical field. Often, these illustrations will take the form of reading and discussing results from recently published medical studies dealing with high dimensional data.
MSCR 520 Clinical Trial Design (2 credits)
MSCR 520 is an introduction to fundamental and quantitative issues in clinical research and clinical trial design co-taught by a biostatistician and a clinician. Traditional and non-traditional study designs including aspects of experimental design and analysis are covered in this course. Study design, sample size, randomization, repeated measures, interim analyses, missing data and interpretation of results are emphasized. Major topics in clinical trial design including good clinical practice and challenges and successes associated with clinical trials conducted at Emory are highlighted. Students participate in class sessions with oral presentations on the advantages and disadvantages of a selected innovative clinical trial design.
MSCR 592 Clinical and Translational Science Colloquium (1 credit)
Seminar-style course that covers a wide array of practical issues in CTS including: research administration and grants management; federal funding process; IRB and HIPAA; Conflict of Interests; Legal Aspects of Translational Research; Drug Discovery; Industry interactions (drug discovery and device development); Multidisciplinary research and Team Science; Mentor and mentee training; Translational Research Informatics, Health Services and Implementation Science Research.
MSCR 593 Ethical, Legal, and Social Issues of Responsible Clinical and Translational Research (1 credit)
This course prepares students to engage in theoretically and practically based discourse and decision making in ethical issues involved in clinical and biomedical research. The course will survey a variety of ethical issues occurring in basic and applied research settings and analyze approaches that seek to prevent or resolve them. Classes will primarily consist of the faculty and students leading discussions around various articles and case studies.
MSCR 594A&B Scientific and Grant Writing (2 credits)
This is a 2-semester, 2-credit, year-long course. The fall semester meets in-person while the 2nd semester will be independent study. This class is designed to teach those who conduct clinical, biomedical, biobehavioral and/or public health research to enhance their scientific and grant writing skills. This is a hands-on tutorial style course. The majority of class time is spent learning about the nuts and bolts of a typical NIH grant. The instructors are available to work with you one-on-one to craft a highly competitive grant proposal. Ideally, you will submit a grant proposal to an external funder to carry out new research, or an extension of your current research. You will complete the entire 2-credit course when you turn in a final grant product which has been accepted by the instructors as final.
MSCR 598 Big Data to Knowledge (BD2K) in CTS Research (1 credit)
Over the last 15 years, there has been an explosion of the amount of data collected in clinical and translational research studies. The rapid increase in “big data” is multifactorial and the primary contributing factors include 1) technical innovations that allow for quick measurement of multiple data points simultaneously with little to no sacrifice in accuracy, 2) reduced costs for performing assays that generate large numbers of data points, and 3) increasing computing infrastructure that allows for meta-analysis of large numbers of clinical and experimental records. “Big data” can be derived from several patient care sub-domains including electronic medical records, continuous health monitor signal processing, self-quantized patient data (mHealth/interpersonal networks), public health surveillance data, and ‘-omics’ data from biologic specimens. This course will seek to convey an understanding of the fundamental principles of these domains in “big data” and introduce ways to incorporate them into translational medical research studies. We will introduce the conceptual basis for analytic strategies to harness the power of big data, including unbiased and unsupervised statistical methods and cutting edge approaches using artificial intelligence.
MSCR 599R - Investigative Mentored Research Thesis (4 credits)
All MSCR student conduct a mentored thesis project in clinical or translational research/science (PhD graduate students will complete a PhD thesis on a CTS related topic in lieu of the master's thesis). The thesis requires developing a hypothesis-driven research proposal to investigate a clinical/translational research question, followed by data collection, analysis of data and presentation of results (both oral and written in a format suitable for publication in the medical literature). It should incorporate appropriate procedures and skills learned in formal course work. The research thesis may focus on a therapeutic clinical trial, interventional study, observational study, an epidemiologic or molecular epidemiologic study, a clinical evaluation program (health services, outcomes, etc.), or a translational research or science project. Students provide an oral presentation to the Georgia CTSA Research Education Executive Committee and submit a written thesis which must be approved by the MSCR program and Dean of the Emory Laney Graduate School. MSCR students are strongly encouraged to present their thesis data at a national meeting and publish their thesis data in a peer-reviewed journal. The data may also impact and serve as the foundation for a career development grant submitted to NIH (e.g. F32, K-series) or a foundation.
ELECTIVES (1-2-credit)
MSCR 596 Advanced Data Management in R (2 credits)
The overarching objective of this elective course is to introduce the R statistical programming language with a focus on data management tasks (importing, cleaning, reshaping, transforming, and exploring data) and reproducible statistical analysis. R packages for the creation of publication-quality figures and tables will be introduced further extending the student’s capabilities to create a complete and reproducible data-processing pipeline from raw data to presentation and publication. While we intend to introduce some of the statistics available in R along with packages for logistic and time-to-event modeling, we will not spend much time on how to perform a given statistical analysis in R nor will we cover the underlying statistical theory of analyses. Nevertheless, anyone who successfully completes the course will have acquired the skills to find and run any common statistical analysis available in R while gaining the much more valuable skills of creatively solving challenging data management problems.
MSCR 515 Scientific Communication for Clinical & Translational Science (1 credit)
Communication of scientific information is essential in connecting with stakeholders in the translational process, including other scientists as well as patients, community members, and the lay public. At the core of effective communication is narrative structure which if mastered will ensure communication that is both engaging and clear, BUT learning narrative structure requires specific tools and techniques, THEREFORE this course is built around the ABT Framework using the ABT Template (And, But, Therefore) to develop a solid set up, problem, solution approach which is now gaining widespread use through organizations such as the World Bank, Pfizer, Genentech and the Global Health Labs.
MSCR 510 Translation and Implementation Science (2 credits)
The course aims to introduce students to methods for translating scientific knowledge into real-world practice and policy. The course covers topics around identifying and appraising the evidence base, assessing, and addressing barriers that impede implementation of proven interventions, designing innovative solutions and studies to test these, and concepts of decision science to promote implementation and sustainability of proven interventions. Throughout the course, students are exposed to case studies of global health interventions or programs which illustrate implementation science concepts while evoking discussion and critical thinking.
Non-credit requirements include an Institutional Review Board (IRB) rotation, a monthly CTS Journal club as well as training in leadership, team science, mentorship and entrepreneurship.
Questions
We encourage interested MSCR candidates to contact the MSCR Program Administrator, Rachel Hardison, for questions and assistance with the application process. For questions, especially technical issues, or problems with the online submission website please contact Alexey Kurbatov.