Curriculum

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Curriculum

TMEC Learning Suite

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The Harvard Medical School Master of Medical Sciences in Clinical Investigation (MMSCI) curriculum is specifically designed to enable students to: master core topics in patient-oriented research; apply new knowledge to real-life examples; develop and execute his or her own research proposal; and impart their findings to the scientific community.

CORE COURSES

CI701 Clinical Data Science: Design and Analytics I
This course introduces methods for the generation and analysis of data for clinical research through seamless integration of epidemiology, biostatistics, and machine learning.

The course is structured in three components that correspond to the three main objectives of clinical research: description, prediction, and causal inference. The descriptive component introduces different data types and study designs, summary measures (including frequency and occurrence measures), and statistical inference (hypothesis testing, confidence intervals). The predictive component introduces association measures, regression (linear, logistic) and other learning algorithms with applications to screening and clinical classification. The causal component introduces a causal inference (counterfactual) framework via randomized clinical trials, which covers survival analyses, sample size calculation, biases, and effect heterogeneity.

The course emphasizes critical thinking and practical applications, including assignments based on articles published in medical journals and a case study at the end of each week. All methods are taught along with Stata software to implement them.

CI708 Clinical Data Science: Design and Analytics II
This course extends the topics introduced in Design and Analytics I for each of the three goals of clinical research: description, prediction and causal inference.

The description sessions discuss data wrangling, data visualization, and unsupervised learning with a focus on clustering.  The prediction sessions discuss building and evaluation of predictive models via regression and other learning algorithms.  The causal inference sessions discuss advanced design of randomized clinical trials (factorial, non-inferiority, adaptive, crossover, cluster-randomized trials), and evidence synthesis using meta-analysis.

The course emphasizes critical thinking and practical applications, including assignments based on articles published in medical journals. All methods are taught along with Stata software to implement them.

CI722 Clinical Data Science: Comparative Effectiveness Research I
This course introduces causal inference methodology when randomized trials are not feasible. The courses focuses on the use of epidemiologic studies, electronic health records and other big data sources for comparative effectiveness and safety research. Key concepts of bias (confounding, selection bias, measurement bias) are described via causal diagrams. Methods for confounding adjustment (stratification, outcome regression, propensity scores, matching, and standardization) are introduced along with an emphasis on formulating well-defined questions in clinical research.

The course emphasizes critical thinking and practical applications, including assignments based on articles published in medical journals. All methods are taught along with Stata software to implement them.

CI732 Clinical Data Science: Comparative Effectiveness Research II
This course extends the topics introduced in Comparative Effectiveness Research I.

The course covers efficient epidemiologic designs (case-control, case-cohort, case-crossover), advanced methods for confounding adjustment (inverse probability weighting, parametric g-formula) for the comparison of sustained treatment strategies, and instrumental variable estimation. The course also covers techniques for the secondary analysis of randomized clinical trials in the presence of deviations from protocol.

The course emphasizes critical thinking and practical applications, including assignments based on articles published in medical journals. All methods are taught along with Stata software to implement them.

CI700 Ethics in Clinical Research and the Institutional Review Board
This course reviews some common challenges in the conduct of patient-oriented 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.

CI702 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.

CI720 Scientific Communication
Publishing in peer-reviewed journals and obtaining independent grant funding are critical for success in clinical research. The MMSCI program places special emphasis on developing skills in writing and the presentation of research data. The module offers students several unique opportunities to develop such skills. Examples include visits to the New England Journal of Medicine editorial meetings and the opportunity for each student to have their individual writing critiqued by the New England manuscript editors. Innovative pedagogic methods will facilitate the development of presentation skills through self- and peer-review of elevator pitches, oral presentations and sessions on how to give feedback.

CI724 Genetic Epidemiology
The goals of this course are to provide clinical researchers with the skills to: address opportunities to incorporate genetic studies to answer specific research questions; understand basic genotyping techniques; understand the basics of genetic study design and analysis; identify and use publicly available databases for genetic research; and understand the principles of ethical conduct of genetic research.

CI712 Leadership and Management
This course examines different aspects of working with, managing and leading a team. Lectures will discuss the skills and techniques that are needed 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.

CI740 Drug Development and Safety
This course will include topics such as: 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.

Admissions &

Financial Aid Deadlines

We are now accepting applications. Applications will close on March 1, 2018.

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