phd clinical research harvard

Foundations of Clinical Research

This Harvard Medical School six-month, application-based certificate program provides the essential skill sets and fundamental knowledge required to begin or expand your clinical research career.

Associated Schools

Harvard Medical School

What you'll learn.

Understand and apply the foundational concepts of biostatistics and epidemiology

Develop a research question and formulate a testable hypothesis

Design and begin to implement a clinical research study

Cultivate the skills required to present a clinical research study

Critically evaluate the research findings in medical literature

Synthesize crucial statistical analyses using Stata software

Course description

The Foundations of Clinical Research program is rooted in the belief that clinical research training is critical to professional development in health care. Clinical research training not only creates potential independent investigators, but also enables clinicians to advance their careers through a greater understanding of research evidence. Designed to provide learners with the foundational knowledge and skill sets required to produce high-quality clinical research, our program will lay the fundamental groundwork in epidemiology and biostatistics required for a multifaceted career in clinical research.

The overarching goal of the Foundations of Clinical Research program is to equip the next generation of researchers with the skill sets essential to evaluating evidence, understanding biostatistics, and beginning their clinical research careers. Our aim is to ensure that learners develop a strong foundation in the design, implementation, analysis and interpretation of clinical research studies.

During the program, our innovative active learning approach emphasizes the traditional tutorial system with weekly live video tutorials, seminars and symposia anchored by 3 live intense weekend online workshops.  The Foundations of Clinical Research program’s six-month online curriculum emphasizes real-time skill-based learning. 

Participants will be eligible for Associate Alumni status upon successful completion of the program. Early tuition and need-based tuition reductions may be available.

Course Outline

Live Workshops

The interactive workshop curriculum will focus on hands-on skill development through active learning. To that end, the intensive schedule is designed to accelerate the growth of high-yield clinical research skills via individual and team-based workshop exercises. Students will be immersed in a dynamic learning environment that encourages collaboration and collegial networking with faculty and peers. 

Essential elements of the workshop include instruction and practical exercises in the core concepts of biostatistics, epidemiology and research question development, as well as critical assessment of the medical literature and practical training in statistical software using real-life datasets. In addition to providing training in mentorship, academic career development and leadership, we create a supportive and active learning environment where opportunities for knowledge retention and networking abound.

Live Symposia, Tutorials and Seminars

Symposia, tutorials and seminars are mandatory and will be delivered live online and organized according to eight specific clinical research topics. 

Eight 3-Hour Symposia

• Instruction on a specific clinical research topic (e.g., cohort study design and interpretation)
• In-depth discussion on a related epidemiology concept (e.g., odds ratio)
• Hands-on guidance for implementing the related analysis with statistical programming in Stata

Eight 1-Hour Tutorials

• Interpret and report on papers related to the specific clinical research topic

Eight 1-Hour Special-Topic Seminars

• The biostatistical and epidemiological concepts to specific clinical research topics with concrete examples

Assignments

All students will be expected to complete all assignments by the due dates. Assignments will be graded as either “pass” or “fail.”

Individual Assignment 1

Individual Research Question and Study Design

• Generate a novel research question in the evidence-based PICO format
• Receive expert faculty review

Individual Assignment 2

Design, Implement and Present an Original Abstract

• Design and implement a clinical research study based on a publicly available dataset
• Analyze and create data visualizations via a user-friendly R Shiny web app
• Write a formal 350-word abstract suitable for submission to an international conference
• Present a digital poster to faculty at Workshop 3

Online Lectures

Research Study Introduction 

• Designing a Clinical Research Study I–III
• Introduction to Evidence-Based Medicine, Systematic Review and Meta-Analysis
• Study Design 1 – Observational
• Study Design 2 – Randomized Controlled Trials
• Study Design 3 – Quasi-Experimental Studies
• Introduction to Biostatistics
• An Investigator’s Responsibility for Protection of Research Subjects
• How to Search PubMed
• Overview of Evidence-Based Medicine

Statistical Programming in Stata

• Loading Data
• Basic Programming Commands
• Data Cleansing
• Data Analytics I – Central Tendency
• Data Analytics II – Statistical Testing
• Data Analytics III – Regression Testing

Instructors

Jamie Robertson

Djøra Soeteman

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The Clinical Epidemiology Area of Interest is the largest of the 12 Areas of Interest in the Department of Epidemiology. Faculty members from this Area of Interest are national and international leaders in research and teaching aspects of Clinical Epidemiology.

• Over 40 primary, secondary, and adjunct faculty members of the Department of Epidemiology are based in the Harvard Teaching Hospitals, or in other national and international clinical research institutions.
• A large amount of the research done by the these faculty member fall under the umbrella of Clinical Epidemiology and its related research fields of Outcome Research , Health Services Research . Comparative Effectiveness Research , and Patients Centered Outcomes Research .
• This Area of Interest spearheads the Department of Epidemiology’s role as the educational hub for training in clinical research at Harvard University
• Program in Clinical Effectiveness ,
• Members of this faculty direct the MPH Concentration in Clinical Effectiveness and the Concentration in Quantitative Methods , containing more than 50% of the MPH students at HSPH.
• Faculty in the Area of Interest were co-instructors in Health in Numbers: Quantitative Methods in Clinical and Public Health Research (PH207X), one of the first two Massive Online Open Courses (MOOCs) offered by Harvard University, which enrolled over 50,000 students throughout the world and granted certificates of completion to over 5,000 students.
• Members of the faculty from this Area of Interest have assisted in the development of clinical research training programs in Portugal, Cyprus, Lebanon, Saudi Arabia, and Portugal.

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• CORRESPONDENCE
• 02 April 2024

How can we make PhD training fit for the modern world? Broaden its philosophical foundations

• Ganesh Alagarasan 0

Indian Institute of Science Education and Research, Tirupati, India.

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You have highlighted how PhD training assessment has stagnated, despite evolving educational methodologies (see Nature 613 , 414 (2023) and Nature 627 , 244; 2024 ). In particular, you note the mismatch between the current PhD journey and the multifaceted demands of modern research and societal challenges.

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doi: https://doi.org/10.1038/d41586-024-00969-x

Competing Interests

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Anticipate, accommodate, empower

Exploring generative ai at harvard.

Jessica McCann

Harvard Correspondent

Leaders weigh in on where we are and what’s next

The explosion of generative AI technology over the past year and a half is raising big questions about how these tools will impact higher education. Across Harvard, members of the community have been exploring how GenAI will change the ways we teach, learn, research, and work.

As part of this effort, the Office of the Provost has convened three working groups . They will discuss questions, share innovations, and evolve guidance and community resources. They are:

• The Teaching and Learning Group , chaired by Bharat Anand , vice provost for advances in learning and the Henry R. Byers Professor of Business Administration at Harvard Business School. This group seeks to share resources, identify emerging best practices, guide policies, and support the development of tools to address common challenges among faculty and students.
• The Research and Scholarship Group , chaired by John Shaw , vice provost for research, Harry C. Dudley Professor of Structural and Economic Geology in the Earth and Planetary Sciences Department, and professor of environmental science and engineering in the Paulson School of Engineering and Applied Science. It focuses on how to enable, and support the integrity of, scholarly activities with generative AI tools.
• T he Administration and Operations Group , chaired by Klara Jelinkova , vice president and University chief information officer. It is charged with addressing information security, data privacy, procurement, and administration and organizational efficiencies.

Klara Jelinkova, Bharat Anand, and John Shaw.

Photos by Kris Snibbe/Harvard Staff Photographer; Evgenia Eliseeva; and courtesy of John Shaw

The Gazette spoke with Anand, Shaw, and Jelinkova to understand more about the work of these groups and what’s next in generative AI at Harvard.

When generative AI tools first emerged, we saw universities respond in a variety of ways — from encouraging experimentation to prohibiting their use. What was Harvard’s overall approach?

Shaw: From the outset, Harvard has embraced the prospective benefits that GenAI offers to teaching, research, and administration across the University, while being mindful of the potential pitfalls. As a University, our mission is to help enable discovery and innovation, so we had a mandate to actively engage. We set some initial, broad policies that helped guide us, and have worked directly with groups across the institution to provide tools and resources to inspire exploration.

Jelinkova: The rapid emergence of these tools meant the University needed to react quickly, to provide both tools for innovation and experimentation and guidelines to ensure their responsible use. We rapidly built an AI Sandbox to enable faculty, students, and staff to experiment with multiple large language models in a secure environment. We also worked with external vendors to acquire enterprise licenses for a variety of tools to meet many different use cases. Through working groups, we were able to learn, aggregate and collate use cases for AI in teaching, learning, administration, and research. This coordinated, collective, and strategic approach has put Harvard ahead of many peers in higher education.

Anand: Teaching and learning are fundamentally decentralized activities. So our approach was to ask: First, how can we ensure that local experimentation by faculty and staff is enabled as much as possible; and second, how can we ensure that it’s consistent with University policies on IP, copyright, and security? We also wanted to ensure that novel emerging practices were shared across Schools, rather than remaining siloed.

What do these tools mean for faculty, in terms of the challenges they pose or the opportunities they offer? Is there anything you’re particularly excited about?

Anand: Let’s start with some salient challenges. How do we first sift through the hype that’s accompanied GenAI? How can we make it easy for faculty to use GenAI tools in their classrooms without overburdening them with yet another technology? How can one address real concerns about GenAI’s impact?

While we’re still early in this journey, many compelling opportunities — and more importantly, some systematic ways of thinking about them — are emerging. Various Harvard faculty have leaned into experimenting with LLMs in their classrooms. Our team has now interviewed over 30 colleagues across Harvard and curated short videos that capture their learnings. I encourage everyone to view these materials on the new GenAI site; they are remarkable in their depth and breadth of insight.

Here’s a sample: While LLMs are commonly used for Q&A, our faculty have creatively used them for a broader variety of tasks, such as simulating tutors that guide learning by asking questions, simulating instructional designers to provide active learning tips, and simulating student voices to predict how a class discussion might flow, thus aiding in lesson preparation. Others demonstrate how more sophisticated prompts or “prompt engineering” are often necessary to yield more sophisticated LLM responses, and how LLMs can extend well beyond text-based responses to visuals, simulations, coding, and games. And several faculty show how LLMs can help overcome subtle yet important learning frictions like skill gaps in coding, language literacy, or math.

Do these tools offer students an opportunity to support or expand upon their learning?

Anand: Yes. GenAI represents a unique area of innovation where students and faculty are working together. Many colleagues are incorporating student feedback into the GenAI portions of their curriculum or making their own GenAI tools available to students. Since GenAI is new, the pedagogical path is not yet well defined; students have an opportunity to make their voices heard, as co-creators, on what they think the future of their learning should look like.

Beyond this, we’re starting to see other learning benefits. Importantly, GenAI can reach beyond a lecture hall. Thoughtful prompt engineering can turn even publicly available GenAI tools into tutorbots that generate interactive practice problems, act as expert conversational aids for material review, or increase TA teams’ capacity. That means both that the classroom is expanding and that more of it is in students’ hands. There’s also evidence that these bots field more questions than teaching teams can normally address and can be more comfortable and accessible for some students.

Of course, we need to identify and counter harmful patterns. There is a risk, in this early and enthusiastic period, of sparking over-reliance on GenAI. Students must critically evaluate how and where they use it, given its possibility of inaccurate or inappropriate responses, and should heed the areas where their style of cognition outperforms AI. One other thing to watch out for is user divide: Some students will graduate with vastly better prompt engineering skills than others, an inequality that will only magnify in the workforce.

What are the main questions your group has been tackling?

Anand: Our group divided its work into three subgroups focused on policy, tools, and resources. We’ve helped guide initial policies to ensure safe and responsible use; begun curating resources for faculty in a One Harvard repository ; and are exploring which tools the University should invest in or develop to ensure that educators and researchers can continue to advance their work.

In the fall, we focused on supporting and guiding HUIT’s development of the AI Sandbox. The Harvard Initiative for Learning and Teaching’s annual conference , which focused exclusively on GenAI, had its highest participation in 10 years. Recently, we’ve been working with the research group to inform the development of tools that promise broad, generalizable use for faculty (e.g., tutorbots).

What has your group focused on in discussions so far about generative AI tools’ use in research?

Shaw: Our group has some incredible strength in researchers who are at the cutting edge of GenAI development and applications, but also includes voices that help us understand the real barriers to faculty and students starting to use these tools in their own research and scholarship. Working with the other teams, we have focused on supporting development and use of the GenAI sandbox, examining IP and security issues, and learning from different groups across campus how they are using these tools to innovate.

Are there key areas of focus for your group in the coming months?

Shaw: We are focused on establishing programs — such as the new GenAI Milton Fund track — to help support innovation in the application of these tools across the wide range of scholarship on our campus. We are also working with the College to develop new programs to help support students who wish to engage with faculty on GenAI-enabled projects. We aim to find ways to convene students and scholars to share their experiences and build a stronger community of practitioners across campus.

What types of administration and operations questions are your group is exploring, and what type of opportunities do you see in this space?

Jelinkova: By using the group to share learnings from across Schools and units, we can better provide technologies to meet the community’s needs while ensuring the most responsible and sustainable use of the University’s financial resources. The connections within this group also inform the guidelines that we provide; by learning how generative AI is being used in different contexts, we can develop best practices and stay alert to emerging risks. There are new tools becoming available almost every day, and many exciting experiments and pilots happening across Harvard, so it’s important to regularly review and update the guidance we provide to our community.

Can you talk a bit about what has come out of these discussions, or other exciting things to come?

Jelinkova: Because this technology is rapidly evolving, we are continually tracking the release of new tools and working with our vendors as well as open-source efforts to ensure we are best supporting the University’s needs. We’re developing more guidance and hosting information sessions on helping people to understand the AI landscape and how to choose the right tool for their task. Beyond tools, we’re also working to build connections across Harvard to support collaboration, including a recently launched AI community of practice . We are capturing valuable findings from emerging technology pilot programs in HUIT , the EVP area , and across Schools. And we are now thinking about how those findings can inform guiding principles and best practices to better support staff.

While the GenAI groups are investigating these questions, Harvard faculty and scholars are also on the forefront of research in this space. Can you talk a bit about some of the interesting research happening across the University in AI more broadly ?

Shaw: Harvard has made deep investments in the development and application of AI across our campus, in our Schools, initiatives, and institutes — such as the Kempner Institute and Harvard Data Science Initiative. In addition, there is a critical role for us to play in examining and guiding the ethics of AI applications — and our strengths in the Safra and Berkman Klein centers, as examples, can be leading voices in this area.

What would be your advice for members of our community who are interested in learning more about generative AI tools?

Anand: I’d encourage our community to view the resources available on the new Generative AI @ Harvard website , to better understand how GenAI tools might benefit you.

There’s also no substitute for experimentation with these tools to learn what works, what does not, and how to tailor them for maximal benefit for your particular needs. And of course, please know and respect University policies around copyright and security.

We’re in the early stages of this journey at Harvard, but it’s exciting.

Share this article

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Teaching & Learning

Harold j. berman, 1918-2007, a scholar of great social account.

Professor Emeritus Harold J. Berman, an expert on comparative, international and Russian law as well as legal history and philosophy and the intersection of law and religion, died Nov. 13. He was 89.

Known for his energetic and outgoing personality, Berman recently celebrated his 60th anniversary as a law professor. He joined the Harvard Law School faculty in 1949 and held the Story Professorship of Law and later the Ames Professorship of Law. A prolific scholar, Berman wrote 25 books and more than 400 scholarly articles, including his magnum opus, “Law and Revolution: The Formation of the Western Legal Tradition.”

“Harold was a scholar of boundless and lofty ambition,” said HLS Professor Emeritus Henry Steiner ’55. “His projects reached deeply not only into comparative analysis and history, but also religion and jurisprudence. This is a record that any distinguished scholar would take pride in.”

Born in 1918 in Hartford, Conn., Berman received a bachelor’s from Dartmouth College in 1938 and a master’s in history from Yale University in 1942. After a year at Yale Law School, he was drafted by the Army and served as a cryptographer in Europe, earning a Bronze Star. He returned to New Haven and finished his degree in 1947.

Berman’s interest in the Soviet legal system began during his law school years, when he studied Russian and taught himself Soviet law. He argued his first case in Moscow in 1958, representing the estate of Arthur Conan Doyle, creator of Sherlock Holmes. Seeking to obtain royalties from the Soviet state on the millions of Conan Doyle books sold in the Soviet Union, Berman won the case in a Moscow city court. He later lost on appeal to a higher Russian Federation court.

Berman was a frequent visitor to Russia as a guest scholar and lecturer. As a result of his firsthand knowledge of the Soviet Union—rare for an American in the Cold War era—he became a leading consultant to Russian officials in the mid-1980s during glasnost and perestroika.

HLS Professor Emeritus Detlev Vagts ’51 was part of a group of academics Berman brought together to teach what they referred to as “capitalist law” in the Soviet Union during that time. Vagts recalled the challenges of their task:

“The young Muscovites had been trained to think of the act of two persons getting together to buy goods low and sell them high as a conspiracy to profiteer—which would get you five years of re-education in Siberia. Now they had to adjust to the idea that it was a legitimate partnership,” he said. “The first Russian law on corporations was drafted by lawyers who could not bear to use the term ‘capital’ for the account in the lower right corner of the balance sheet; they called it ‘the social account’ instead.”

In 1985, faced with the prospect of mandatory retirement, Berman left HLS for Emory Law School. At Emory, he held the Robert W. Woodruff Professorship of Law—the highest honor Emory bestows on a faculty member—for more than 20 years. He was the principal founder of the American Law Center in Moscow, a joint venture of Emory and the Law Academy of the Russian Ministry of Justice. He was also co-chairman of Emory’s World Law Institute, an organization that sponsors educational programs around the world.

Reflecting another of his long-term interests, Berman helped to develop Emory’s Center for the Study of Law and Religion. In 2003, he published “Law and Revolution, II: The Impact of the Protestant Reformations on the Western Legal Tradition.”

Modal Gallery

Gallery block modal gallery.

Phase 3 trial of coronavir (favipiravir) in patients with mild to moderate COVID-19

Affiliations.

• 1 Clinical Research Department, The Federal Budget Institute of Science "Central Research Institute for Epidemiology" of The Federal Service on Customers' Rights Protection and Human Well-being Surveillance Moscow, Russia.
• 2 Medical Center "Eco-safety" Saint-Petersburg, Russia.
• 3 Medical Center "Group of Companies "MEDSI" JSC Moscow, Russia.
• 4 Clinical Pharmacology Department, "Clinical Hospital of Zhukovsky" Zhukovsky, Russia.
• 5 Medical Center "Neuroprofi" LLC Korolev, Russia.
• 6 L.A. Vorokhobov City Clinical Hospital No. 67 of The Moscow City Healthcare Department Moscow, Russia.
• 7 City Clinical Hospital No. 52 of The Moscow City Healthcare Department Moscow, Russia.
• 8 Infectious Clinical Hospital No. 1 of The Moscow City Healthcare Department Moscow, Russia.
• 9 Voronezh Regional Clinical Hospital No. 1 Voronezh, Russia.
• 10 City Hospital No. 40 of The Kurortny District Sestroretsk, Russia.
• 11 N.I. Pirogov National Medical and Surgical Center of The Ministry of Health of The Russian Federation Moscow, Russia.
• 12 N.N. Burdenko National Medical Research Centr of Neurosurgery of The Ministry of Health of The Russian Federation Moscow, Russia.
• 13 R-Pharm Group of Companies Moscow, Russia.
• PMID: 34956474
• PMCID: PMC8661194

Favipiravir has demonstrated efficacy against the SARS-CoV-2 virus in several preliminary studies. This study aimed to evaluate the efficacy and safety of favipiravir for treatment of mild to moderate COVID-19 in outpatients and hospitalized patients. We conducted an open-label, randomized, active-controlled trial of a generic form of favipiravir in patients with COVID-19 confirmed by PCR-test. Eligible patients (18-60 years) after stratification were randomly assigned (in a 2:1 ratio) to receive either favipiravir (1800 mg BID on day 1, followed by 800 mg BID for up to 9 days), or standard of care (SOC) treatment (umifenovir + intranasal interferon alpha-2b, or hydroxychloroquine) for up to 10 days. The co-primary outcomes were the time to clinical improvement and the time to viral clearance. Among 190 patients assessed for eligibility 168 were randomized to favipiravir (n=112) or to SOC (n=56) group. The median time to clinical improvement was 6.0 days (IQR 4.0; 9.3) in the favipiravir group and 10.0 (IQR 5.0; 21.0) days in the SOC group; the median difference was 4 days (HR 1.63; 95% CI 1.14-2.34; P=0.007). The statistically significant difference in the median time to viral clearance was observed only for hospitalized patients: 3.0 (IQR 3.0; 3.0) days in the favipiravir group vs. 5.0 (IQR 4.5; 5.5) days in the SOC group (HR 2.11; 95% CI 1.04-4.31; P=0.038). The rate of viral elimination on Day 5 in the favipiravir group was significantly higher than in SOC group: 81.2% vs. 67.9% (RR 1.22; 05% CI 1.00-1.48; P=0.022). The rate of clinical improvement on Day 7 in the favipiravir group was 1.5-fold higher than in SOC group: 52.7% vs. 35.8% (RR 1.50; 95% CI 1.02-2.22; P=0.020). Favipiravir was well-tolerated and the most common adverse reactions were asymptomatic hyperuricemia, transient elevation of ALT & AST, and mild gastrointestinal disorders. Favipiravir was superior to the SOC in shortening the time to clinical improvement in patients with mild to moderate COVID-19.

Keywords: COVID-19; SARS-CoV-2; coronavirus; favipiravir.

AJTR Copyright © 2021.

Introducing the Inaugural Scholars of K12 Urology Research at Stanford (KUReS) Career Development Program in Benign Urology

Meet the inaugural scholars of the K12 Urology Research at Stanford (KUReS) , Kathleen Kan , MD and Alexandra Polasko , PhD!

Kan, a clinical assistant professor of urology and a pediatric urologist, studies pediatric lower urinary tract symptoms (pLUTS), a prevalent and often overlooked condition affecting elementary school-aged children, using a community-engagement approach.  She will focus on the development of momentary assessment and observation tools in school settings to capture child- and school-level factors in daytime bathroom use with the long-term goal is to reduce disease burden and improve local policies and practices.  Her multidisciplinary mentors include Anisha Patel, MD and Korey Hood, PhD from the Department of Pediatrics and James Brooks, MD from Urology.

Polasko, a postdoctoral scholar in urology with an engineering background, will investigate the role of bone morphogenic protein 5 (BMP5) in the pathophysiology of benign prostatic hyperplasia (BPH), a common disease that affects a large percentage of aging men with lower urinary tract symptoms.  BPH, according to Polasko, is characterized by abnormal growth of the prostate stromal and epithelial compartments.  She and colleagues have discovered that transcript levels of BMP5 produced by a subset of prostate fibroblasts are upregulated 50-fold in human BPH tissues compared to normal prostate.  “Our findings suggest BMP5 plays a promoting role in human BPH growth and BMP5 inhibition may be an effective treatment for BPH patients,” added Polasko, who will perform her research in the lab of James Brooks with additional mentorship from Sharon Pitteri and Jon Pollack.

Based in the Department of Urology, KUReS is a new multidisciplinary career development program funded by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).  Under the leadership of program directors Joseph Liao and James Brooks , KUReS provides mentorship and funding support for the promising early-stage urologic surgeon scientists and research scientists who are engaged in advancing research in benign urological diseases.