Master of Science in Clinical Research

Flipped Classroom

This program uses the flipped classroom model, where students are provided with materials to study prior to coming to class, and time spent in the classroom is devoted to the discussion and application of this material. The flipped classroom allows students to acquire knowledge at their own pace while encouraging skill acquisition and active learning in the classroom setting. Class participation is an important part of student assessment in most of our core courses, ensuring that students come to class well-prepared and ready to participate.

Where didactic lecturing methods are used, our faculty will incorporate active student participation using methods such as audience response systems, breakout sessions, and asking questions to stimulate discussion.

Team-Based Learning

This is incorporated into the core courses, promoting social learning and the development of collaborations and networking within the program. Team concepts are taught through case examples in leadership and teamwork. Students are required to formally evaluate one another’s performance within teams and will receive anonymized feedback on their individual performance to enhance their education.

Capstone Project

As part of the course, students will work on a capstone project, which will be aligned with their goals and interests. Upon entry into the program, each student will be assigned to a Harvard Medical School faculty advisor who will advise them on their projects over the year. The capstone project represents a key unifying experience where theoretical training and practical skills are applied to real-world research questions. The program will provide training in the methods and conduct of systematic review and meta-analysis. Each student will be required to develop a research question, apply appropriate methodology for analysis, and communicate the results in both written and oral form.  

Future leaders in all aspects of health care have an inherent responsibility to ensure that they and their team and institution incorporate and practice the core concepts of diversity, equity, and inclusion (DEI). DEI’s importance will be emphasized and incorporated into each course learning objective, ensuring that students learn the relevance and importance of these principles for all aspects of evidence-based medicine. Specifically, this will include the collection, analysis, and communication of research data related to race, ethnicity, gender identity, age, and other relevant factors; challenges and potential solutions to achieving diverse representation in research; as well as the importance of engaging with various community advocates, societies, and organizations.

Ethics and the 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 principal investigators will be discussed. The course will include the history of research ethics and touch upon the ethics of animal research, which is often the precursor to trials in human beings. Information about preparing research protocol applications and informed consent documents for clinical research will be provided. The course also will review some current and common challenges in the ethical conduct of research, including consideration of diversity, equity, and inclusion; recruitment practices; vulnerable populations; and topics such as artificial intelligence (AI) and machine learning, genomics, and the use of social media in research. The importance of considering the perspectives of subjects and patients in clinical research will also be explored. The course will include didactic and group work emphasizing critical thinking and practical application of ethical considerations while developing and implementing patient-oriented research.

Clinical Data Science: Design and Analytics 

Clinical research requires the generation and analysis of data for three tasks: description, prediction, and causal inference. The course will introduce measures of frequency and association, study designs, and basic methods to understand and address confounding. The biostatistics component will introduce data types, data summaries, hypothesis testing, the essentials of statistical inference, and statistical methods for calculating summary estimates, measures of variability, confidence intervals, sample size calculations, and concepts for modeling. All methods are taught along with Stata software to implement them.

Interpreting Medical Literature, Part 1 

Throughout the program, students will delve into the intricacies of evidence development and how it is interpreted and disseminated. They will learn how to search databases, including Harvard’s HOLLIS database and PubMed; develop skills in organizing, analyzing, and interpreting this evidence; and disseminate this summarized evidence as either systematic reviews and/or meta-analyses, guidelines, or narrative summaries.  

Clinical Trials

The goals of this course are to develop a fundamental 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, 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.

Systematic Review and Meta-Analysis

The Systematic Review and Meta-Analysis course will be an advanced research methodology course designed to equip students with the skills and knowledge necessary to conduct comprehensive and rigorous syntheses of existing research literature. This course will delve into the principles and techniques of systematically gathering, critically appraising, and synthesizing primary research studies, with a particular focus on quantitative approaches like meta-analysis. Students will learn to formulate clear research questions, search for relevant studies across various databases, and assess the quality and bias of included studies using established tools and guidelines. The course also will cover statistical methods for combining data from multiple studies, exploring heterogeneity, and drawing meaningful conclusions. Additionally, ethical considerations, publication bias, and the interpretation of results will be discussed. By the end of the course, participants will be well prepared to contribute to evidence-based decision-making in their respective fields and to conduct rigorous systematic reviews and meta-analyses of their own.

Fundamentals of Evidence-Based Medicine, Part 1

This course will offer a comprehensive exploration of the fundamental principles and practices of evidence-based medicine (EBM). Designed for health care professionals, researchers, and students, this course will provide a structured framework for understanding how to integrate the best available evidence into clinical decision-making. Participants will gain a solid foundation in critical appraisal skills, enabling them to assess the quality and relevance of medical literature, including clinical studies, systematic reviews, and meta-analyses. Through a combination of lectures, case studies, and interactive discussions, they will learn to formulate clinical questions, search for evidence effectively, and apply the findings to real-world patient care scenarios. Additionally, the course will emphasize the importance of considering patient values and preferences in decision-making and promoting a patient-centered approach to health care. By the end of the course, participants will be equipped with the knowledge and skills necessary to navigate the ever-evolving landscape of medical information and make evidence-based decisions that improve patient outcomes.

Fundamentals of Decision Science

The Fundamentals of Decision Science course, with a specific focus on evidence-based medicine, provides a comprehensive understanding of the core principles and methodologies essential for making informed decisions in the field of health care. This course will delve into the fundamental concepts of decision analysis, statistical inference, and critical appraisal of medical evidence, equipping participants with the tools necessary to assess the effectiveness and safety of medical interventions. Students will explore various aspects of evidence-based medicine, including study design, data collection and analysis, and the interpretation and application of research findings in clinical practice. Moreover, the course will emphasize the importance of evidence synthesis and the use of systematic reviews and meta-analyses to inform medical decision-making. A key feature of this course will be an exploration of the use of artificial intelligence-based tools as they relate to making decisions related to health care. Through a combination of theoretical instruction and hands-on exercises, students will develop the skills needed to critically evaluate medical research and contribute to the delivery of high-quality, evidence-based health care.

Leadership and Teamwork

This course will examine different aspects of leadership, including working with, managing, and leading a highly functional team. Lectures will discuss different leadership styles and leadership techniques, such as having difficult conversations, giving feedback, negotiating, and leading in times of crisis. Students will be divided into teams and work on a team assignment focused on a leadership challenge.

Artificial Intelligence (AI) in Research

The course Artificial Intelligence (AI) in Research will delve into AI’s transformative role in various research domains. With AI increasingly becoming a cornerstone of modern scientific inquiry, this course will aim to equip students with the knowledge and skills necessary to leverage AI techniques effectively in their research endeavors. The course will address ethical considerations and best practices in AI research, including issues related to data privacy, bias mitigation, and reproducibility. Participants will learn how to navigate ethical challenges and ensure the responsible use of AI in their research projects. The course will begin with an exploration of fundamental concepts in AI, including machine learning, deep learning, and natural language processing. Through a combination of lectures, hands-on exercises, and case studies, students will gain a solid understanding of these foundational AI techniques and their applications in evidence-based medicine. Building upon this foundation, the course will examine advanced AI methodologies tailored specifically for research purposes. Topics covered may include data mining, predictive analytics, computer vision, and optimization techniques. Emphasis will be placed on understanding the underlying algorithms, selecting appropriate models, and interpreting results within a research context.

Interpreting Medical Literature, Part 2

Part 2 of this course will focus on manuscript writing and offer a comprehensive, hands-on approach to honing the art of creating well-crafted, scholarly, and engaging written works. Geared toward aspiring authors, researchers, and anyone seeking to improve their writing skills, this course will cover the entire spectrum of manuscript production. Students will delve into the nuances of structuring academic papers, research articles, essays, and more, while gaining a deep understanding of formatting, citation styles, and the importance of clarity and precision in writing. Emphasizing the writing process from inception to publication, participants will develop effective strategies for research, organization, revision, and proofreading. With a focus on fostering critical thinking and effective communication, this course will equip students with the tools needed to produce polished, publishable manuscripts that resonate with a wide range of audiences.

Fundamentals of Evidence-Based Medicine, Part 2

This comprehensive course on guidelines in evidence-based medicine will offer a thorough exploration of the principles and practices that underpin the field of evidence-based medicine. (EBM). Designed for health care professionals, researchers, and students, this course will equip participants with the essential skills and knowledge needed to critically appraise and apply clinical guidelines effectively. Throughout the course, participants will delve into the foundations of EBM, gaining a deep understanding of how evidence is generated, assessed, and synthesized. They will learn to navigate the hierarchy of evidence from randomized controlled trials to observational studies, and gain a deep understanding of the importance of systematic reviews and meta-analyses in evidence synthesis. Participants also will explore the nuances of guideline development, including the role of expert panels, the GRADE system, and the integration of patient preferences and values. Practical sessions will involve hands-on experience in appraising clinical guidelines and identifying potential biases or conflicts of interest. Furthermore, the course will address the application of EBM principles in clinical decision-making, emphasizing the importance of shared decision-making and patient-centered care. Participants will gain proficiency in interpreting and communicating guideline recommendations to patients, enhancing their ability to provide evidence-based, high-quality health care. By the end of this course, they will be well equipped to critically assess clinical guidelines, make informed clinical decisions, and contribute to the advancement of evidence-based health care practices in their respective fields.

Applied Omics Science

The Applied Omics Science course is a cutting-edge exploration of the multidisciplinary field encompassing genomics, proteomics, metabolomics, and other “omics” disciplines. With a strong foundation in molecular biology and bioinformatics, this course will delve into the “why” and “how” of omics science. Students will gain a comprehensive understanding of how genomics, transcriptomics, proteomics, and metabolomics data are generated and analyzed to unravel the intricacies of living organisms. This course will provide an in-depth examination of applications across various domains, from personalized medicine and drug discovery to agriculture and environmental science. Through computational exercises, participants will acquire the skills necessary to process, analyze, and interpret omics data, and gain a deeper appreciation for the potential of these technologies in advancing the understanding of biology and addressing real-world challenges. Applied Omics Science is an essential course for researchers, health care professionals, and individuals seeking to harness the power of big data in medical science and health care decision-making.

Translating Innovation into Practice

This course is designed to introduce translating research innovations into clinical practice. It will examine the design of first-in-human studies (including integration of translational medicine approaches, biomarker discovery, and validation), the regulatory process to bring innovation to the clinic, and academic-industry partnerships. Discussion topics, including how to secure funding through industry networks and how to approach commercializing a discovery, will be illustrated through case examples from guest lecturers.

Mixed Methods Research 

This course will provide students with a deep understanding of the principles, design, and application of mixed methods research in various academic and professional contexts. Through a combination of lectures, readings, and practical exercises, participants will learn how to effectively combine quantitative data collection and analysis techniques, such as surveys and statistical analysis, with qualitative methods like interviews, focus groups, and content analysis. The course will explore the theoretical foundations of mixed methods research, ethical considerations, and strategies for effectively integrating and interpreting data from different sources. Students also will gain hands-on experience in designing mixed methods studies, collecting, and analyzing data, and presenting findings. By the end of this course, they will be equipped with the knowledge and skills to conduct rigorous and comprehensive research that can provide a deeper understanding of complex phenomena and enhance the validity and reliability of research outcomes.

Capstone Project

The capstone experience is a required component of the Master of Science in Clinical Research program. The capstone project will require students to work on an individual systematic review and meta-analysis, supervised by a Harvard Medical School faculty advisor. Each student will be paired with other classmates who will serve as screening reviewers for one another during the selection of articles for their respective systematic reviews and meta-analyses. The experience will allow students to apply the tools, strategies, and methods from their didactic courses to develop a solution to an evidence-based problem seen in health care delivery. Successful completion of the capstone project will be based on assessment of a written proposal and an oral presentation.

In order to graduate with the degree of Master of Science in Clinical Research students must fulfill all of the program’s academic and attendance requirements, including completion of the 36-credit curriculum and a successful oral capstone presentation. A 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 they will be awarded the degree.

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

Evaluation of the Capstone

The Capstone Committee will be composed of the primary site mentor, their faculty facilitator, and a program representative. A structural framework for the capstone thesis will be provided. Students must meet regularly with their Capstone Committee and submit progress reports on each occasion.