Master of Medical Sciences in Clinical Investigation

Mentored Research Experience

As a core component of the program, you’ll conduct research at an HMS-affiliated hospital. Your faculty mentor will help you oversee all aspects of the project. At the end of the research experience, you’ll complete a thesis under the direct supervision of a thesis committee. It will include two first-author manuscripts of original research that you submit to a peer-reviewed journal or an extensive document describing the body of work you’ve completed. You’ll also give a public presentation of your work and your thesis will be archived at the Countway Library.

Intensive Workshops

The central pillars of the MMSCI program will consist of three intensive workshops and didactic sessions that are complemented by journal clubs, office hours, computer laboratory classes, team-based projects, and presentations.

Longitudinal Teaching

Between each workshop, further exploration of contemporary research topics will occur at weekly interactive sessions. Novel pedagogic approaches for this longitudinal series include the use of “flipped classroom” methods, where students review and dissect learning material in advance of facilitated discussions.

Contemporary Topics in Clinical and Translational Investigation

A course designed to complement the didactic and longitudinal curriculum through team-based database analysis. In it, students will develop their abilities to present the data in figures and tables in various formats.

Clinical and Translational Investigation Thesis Preparation

During the course, learners work with their mentors on two thematically linked research projects, which form the basis for two first-author publications, or a body of work. The Clinical & Translational Investigation Thesis Preparation course provides guidance on topics critical to the preparation and presentation of the written and oral forms of the thesis defense. Topics include a review of analytic strategies for qualitative and quantitative data, presenting skills for qualitative and quantitative data, writing an academic paper, writing an op-ed (opinion) piece for the popular press, and tips for writing and grammar. Weekly writing advising allows students to receive continuous feedback on their thesis composition.

Clinical Data Science: Design and Analytics I

This course introduces methods for the generation and analysis of data for clinical research through the 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 and confidence intervals). The predictive component introduces association measures, regression (linear as well as logistic), and other learning algorithms with applications to screening and clinical classification. The causal component introduces a causal inference (counter-factual) 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 each week. All methods are taught along with STATA and R software to implement them.

Leadership and Teamwork 

This course will examine the 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.

Ethics and the IRB (Institutional Review Board) 

This course will examine the regulatory and ethical oversight of the history and evolution of ethical research codes and regulations. The role and responsibility of physicians as investigators will be discussed, and information about the preparation of research protocol applications and informed consent documents for clinical research will be provided. The course also will review some timely and common challenges in the ethical conduct of patient-oriented research, including recruitment, issues related to vulnerable populations, and current topics such as biobanking and the use of social media in research. The curriculum also includes the importance of considering the perspectives of subjects and patients in clinical research. Students will be educated about their regulatory and moral responsibilities to increase transparency within the clinical research environment through lectures on the importance of clinicaltrials.gov and data sharing. The course will include didactic and group work that will emphasize critical thinking and practical application of ethical considerations while developing and implementing patient-oriented research.

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, as well as the basics of genetic study design and analysis; identify and use publicly available databases for genetic research; and understand the principles of ethical conduct in genetic research.

Mentored Research Experience 

During the mentored research experience, each student will have the opportunity to take the lead on clinical research projects in their areas of interest. Working in a Harvard-based laboratory, under the direct supervision of a primary mentor, each student is required to complete a thesis at the end of the program. The purpose of this requirement is twofold: to highlight the importance of publishing quality research in peer-reviewed academic journals and to promote excellence in the practice of scientific communication. Additional guidance and oversight are provided to each student by a thesis committee, which consists of the student, the primary mentor, one external member (i.e., someone who is not in the student’s primary laboratory and who is not directly involved in the student’s research) and an MMSCI program representative.

 

Clinical Investigation Curriculum

Clinical Data Science: Design and Analytics II

This course will extend 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 the building and evaluation of predictive models via regression and other learning algorithms. The causal inference sessions discuss the advanced design of randomized clinical trials (factorial, non-inferiority, adaptive, crossover, and cluster-randomized clinical trials) and evidence synthesis using meta-analysis. 

Clinical Data Science: Comparative Effectiveness Research I 

This course will introduce causal inference methodology when randomized clinical trials are not feasible. The course 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, such as confounding, selection bias, and measurement bias, are described via causal diagrams. Methods for confounding adjustment, including stratification, outcome regression, propensity scores, matching, and standardization, are introduced along with an emphasis on formulating well-defined questions in clinical research.

Clinical Data Science: Comparative Effectiveness Research II

This course will extend the topics introduced in Comparative Effectiveness Research I. The course covers efficient epidemiologic designs such as case-control, case-cohort, and case crossover. It also dives into advanced methods for confounding adjustment (inverse probability weighting and 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.

Drug Development, Safety, and Translational Pharmacology

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.

Clinical Trials

The goals of this yearlong series, comprising two semester-long courses, are to develop a deep understanding of how clinical trials are conceived, funded, developed (including protocol development and, in the case of industry trials, the industry approval process), conducted, and closed out. Key topics will include different trial designs (adaptive, point-of-care, pragmatic designs, etc.), trials in different settings (emergency, pediatrics, cancer, biomarker, device, etc.), statistical monitoring of trials, safety issues, secondary analysis of clinical trial data, committee organization and management, advanced ethics, post-marketing surveillance studies and writing up trials for publication. Practical examples mixed with theory will be emphasized.

 

Translational Investigation Curriculum

Investigative Models for Translational Research

This course will introduce the range of investigative models within the translational research spectrum, with emphasis on the advantages and disadvantages of each system. Introductory sessions focus on developing well- designed research questions and selecting appropriate analytic methods to interpret results. The course will consider both discovery-based hypothesis generating as well as hypothesis-driven mechanistic studies, illustrating each with case studies. Participants will learn about the various types of model systems used for translational research, from in vitro and ex vivo approaches to the use of animal models and human biospecimens. Lastly, commonly used bench techniques will be discussed. At the conclusion of this course, participants will have an appreciation for where translational investigation fits within the research spectrum.

Systems Biology and Omics Analysis

The goals of this course are to introduce participants to fundamental concepts in systems biology and to provide a basis for experiments that generate large genomic, transcriptomic, or proteome datasets. An introduction to gene expression and gene regulation is followed by an exploration of experimental design for the generation of large datasets and their integration using systems biology principles. Mass spectrometry-based proteomics and related technologies are discussed in the context of biomarker discovery and the course concludes with an investigation of the microbiome and its relevance in health and disease.

Cell and Molecular Biology in Medicine

The goal of this course is to provide translational investigators with a broad understanding of the fundamental processes that drive cell function in health and disease. An overview of cell biology is followed by an introduction to specific cell functions that play key roles in disease processes, including inflammation, angiogenesis, wound healing, and fibrosis. The innate and adaptive arms of the immune system are covered, with a focus on cutting-edge techniques for immunological investigation. Specific disease entities, including diabetes, cancer, cardiovascular, and neurodegenerative diseases, are explored as examples of studies in cellular and molecular medicine. Case studies will be used throughout to illustrate key points, and the course will conclude with a discussion of the therapeutic exploitation of cell biology in the pursuit of precision and personalized medicine.

Translating Innovation into Practice

This course is designed to provide learners with an introduction to the process of translating research innovations into clinical practice. It will examine the design of first in human studies, the process of filing patents, and the regulatory process to bring innovation to the clinic. Securing funding through industry networks, and how to approach commercializing a discovery are also covered, with case studies throughout.

In order to graduate with the degree of "Master of Medical Science in Clinical Investigation", students must fulfill all of the program’s academic and attendance requirements, including completion of the 64-credit curriculum and a successful oral thesis defense (two first author original manuscripts; one accepted submitted and one submitted to a peer-reviewed journal). The MMSCI degree will not be granted to any student who is not in good standing or against whom a disciplinary charge is pending. In addition, a student’s term bill must be paid in full before he/she will be awarded the degree.

A more detailed look at the HMS academic and financial policies can be found in the Student Handbook.

Evaluation of Didactic Components

Students receive a final grade for each core subject module they take. This may be a letter grade or a satisfactory/unsatisfactory rating. In addition, students are evaluated throughout each course through regular homework assignments, online quizzes, class participation, and team-based projects that are presented orally and in written form.

Evaluation of the Mentored Research Experience

Students must meet regularly (4 times over the two-year period) with their thesis committees and submit progress reports on each occasion. The thesis committee will comprise of the primary research mentor, a content mentor approved by the MMSCI Program leadership, and a MMSCI program representative.