Getting a Head Start With AI at the Icahn School of Medicine at Mount Sinai

Mar 2, 2026 | Artificial Intelligence, Research, School

Alvira Tyagi is a first-year medical student at the Icahn School of Medicine at Mount Sinai. She was part of a research team examining the limitations of ChatGPT Health in a study, which had findings published in Nature Medicine.

Most first-year medical students spend their time mastering anatomy, memorizing biochemical pathways, and adjusting to the pace of clinical training. For Alvira Tyagi, that first year coincided with an opportunity to understand the rapid transformation in how patients seek health information with AI tools.

“In January, OpenAI launched ChatGPT Health, and I was immediately curious as to how people were using it,” she says. ChatGPT Health is a service dedicated to answering health and wellness questions, with options to connect to medical records and wellness apps.

Within weeks of launch, OpenAI reported that more than 40 million people were using ChatGPT Health daily. “In a single day, this tool was engaging far more people than many major hospital systems see annually,” Ms. Tyagi notes. And barely into her first full year of medical training, Ms. Tyagi became involved in a study to examine the reliability of such AI tools for health recommendations, under the mentorship of Ashwin Ramaswamy, MD, an instructor in the Department of Urology.

“We set out to test how well ChatGPT Health handles clinical urgency—specifically, whether it steers users with serious symptoms toward emergency care,” she says.

The research team, comprising several physicians and members from Mount Sinai’s Windreich Department of AI and Human Health (AIHH), conducted a study in which they posed clinical scenarios to ChatGPT Health and gauged how it triaged them, compared to gold-standard decisions from physicians following medical society recommendations.

ChatGPT Health, launched in January 2026, is a service on ChatGPT that lets users ask questions about health and wellness. In addition to asking the chatbot questions, users can also sync wearables to it or even upload lab results and ask it to explain the results.

The team found that textbook emergencies were correctly triaged. However, more than half of true emergencies were under-triaged, and the service’s suicide crisis safety alerts were inconsistent and lacking. The full findings, in an article with Ms. Tyagi as the second author, were published as “ChatGPT Health performance in a structured test of triage recommendations” in Nature Medicine in February.

“I did not expect to be involved in AI-driven health care research so early as a student,” says Ms. Tyagi. “Being part of work that could directly impact patient outcomes has been incredibly meaningful.” Read on to learn how she began working at the intersection of AI and health care, and the importance for students to be familiar with this rapidly evolving field.

How did this research project get started?

It started with me shadowing Dr. Ramaswamy in the Urology Department. In-between surgeries, we talked about our interests in AI in health care, and I learned we had a robust department at Mount Sinai that focused on AI and research.

We continued having conversations about AI in health care, and when OpenAI released ChatGPT Health, the discussions intensified. Immediately, we were texting about the implications of this tool, which coalesced into the idea of a study to examine it.

The project started out with the two of us, but with the help of leadership from AIHH, and other physicians, we managed to find collaborators and were able to begin the study quickly.

What was it like being on the research project as a student?

At first, I was intimidated. I was a first-year student working alongside physicians with far more experience in AI and clinical medicine than I had. It took some time to realize that I didn’t need to match their background to contribute meaningfully. I brought a different perspective. I could think through how someone my age would realistically use a tool like ChatGPT Health—how we’d phrase questions, what we might take at face value, and where misunderstandings could happen. That lens helped us step outside a purely clinical viewpoint.

We knew we needed to move quickly. From its release, ChatGPT Health was already being widely used, and we felt a responsibility to evaluate it while people were actively using it. We completed the data collection within two weeks because we wanted to better understand its safety profile and identify any potential limitations as early as possible. Our goal was not to diminish the value of AI in health care, but to approach it thoughtfully by examining where it performs well and where caution may be warranted.

I have always enjoyed writing, whether for leisure or through my work with my undergraduate newspapers—so it naturally became a larger part of my role in the project. In addition to contributing to data collection, I took on significant responsibility for drafting and editing the manuscript. This involved many late nights and multiple rounds of revisions, but I valued that process. Given that the tool was already being widely used, it was essential that we communicate our findings clearly, accurately, and with appropriate nuance.
I was genuinely excited to be part of the project, especially as a student stepping into the world of AI research for the first time. At the same time, I felt a deep sense of responsibility. I wanted to contribute meaningfully alongside experienced researchers, and I was acutely aware that our findings could influence how people understand and use this technology. That awareness pushed us to be especially rigorous. We carefully crafted our prompts and clinical scenarios to be as comprehensive and realistic as possible.

Was it hard balancing school work and being on this project?

My school work always came first, and I was careful to keep that as my priority. Because of that, much of the research work happened in the evenings. It could be demanding at times, but I truly enjoyed it. Being part of a project that was unfolding in real time, and working alongside people who made the process engaging and collaborative, felt energizing rather than exhausting.

What also made this project so meaningful was that it never felt disconnected from my education. It was a different kind of learning: hands-on, fast-paced, and collaborative. There was constant progress and discussion, and that experience offered something you simply cannot replicate in a classroom.

The structure of the medical education program at the Icahn School of Medicine also helped tremendously. The flexibility and autonomy built into our curriculum made it possible to take on a project like this while staying on track academically. In the end, it was demanding, but it resulted in work I am genuinely proud of.

Should students be thinking about AI more?

As medical students, we’re trained to understand clinical systems and patient care. It can be easy to view AI as something reserved for computer science experts and engineers, and that it’s separate from us and the work we do as clinicians. But that is becoming less and less true by the day.

Patients now have direct access to AI technology, and many will go to doctor appointments having already used them to research symptoms or interpret medical information. At the same time, in our current health care system, patients may wait months to see a physician. In that gap, AI tools can function as a kind of interim resource—offering information, reassurance, or sometimes misinformation—before a patient ever steps into a clinic.

Because of this, it falls on us as future doctors to understand these AI health care technologies before patients come to see us. Understanding and discussing the AI-generated information a patient has already seen may soon become a routine part of taking a patient history. We cannot effectively counsel patients about tools they are using if we do not understand how those tools work, what their limitations are, and where they may fall short.

As part of a generation of physicians training alongside these technologies, we have a responsibility not only to react to AI’s presence in medicine, but to engage with it thoughtfully and proactively.

What advice do you have for students who are interested in AI research?

For students who are not sure whether they can even get started, you absolutely can. You don’t need to be an engineer or have years of technical experience to contribute meaningfully. AI research, especially in health care, needs people who can think critically, ask good questions, and communicate clearly.

Then, for those who aren’t sure how to get started, start having conversations—with classmates, professors, and doctors. A simple conversation in between patient cases is what transformed my shadowing experience at the Urology Department into this research project. There are so many talented scientists and faculty at Mount Sinai, and simply engaging with them by asking questions, sharing your interests, and expressing curiosity, can open doors. Sometimes all it takes is one thoughtful conversation to set something much larger in motion.

Being open to opportunities and willing to learn really makes a difference. I had never done AI research before this project, so stepping into it required me to get comfortable with not knowing everything. But I came to understand that AI is developing so quickly that no one has it completely figured out. Even people with years of experience are still asking questions and adjusting as the field evolves.

That realization made it feel less about being an expert and more about being engaged. You don’t have to start with deep technical knowledge; you just have to be willing to listen, learn, and contribute where you can. In a space that’s changing this fast, humility and curiosity go a long way.

How An Interest in Cardiothoracic Surgery Is Shaping Caroline Tavolacci’s Path as a Surgeon-Scientist at Mount Sinai

Updated on Feb 17, 2026 | Featured, Research, School

Sooyun Caroline Tavolacci, MD, MSCR, with her mentor, Anelechi Anyanwu, MD

Sooyun Caroline Tavolacci, MD, MSCR, is a third-year PhD student in the Clinical Research Program at the Icahn School of Medicine at Mount Sinai and a surgeon-scientist in training. Her dissertation research focuses on heart transplantation outcomes, specifically evaluating beating heart transplantation using ex-vivo heart perfusion and its impact on donor pool expansion, under the mentorship of Anelechi Anyanwu, MD, Professor and Vice Chair, Department of Cardiovascular Surgery, and Natalia Egorova, PhD, Professor, Department of Population Health and Science.

In parallel with her doctoral training, Dr. Tavolacci works as a clinical research coordinator in the Department of Cardiovascular Surgery at The Mount Sinai Hospital, Clinical Research Office, which is led by Julie Swain, MD, Professor and Vice Chair of the Department.

Having progressed from an international master’s student to a PhD candidate and hospital employee, she reflects on five years of training marked by perseverance, balance, and growth across research, work, and life.

Her interest in medicine began early, sparked by seeing the Jarvik-7 artificial heart in a school textbook. She was fascinated by the idea of replacing a vital organ, the multidisciplinary care behind it, and the trust required between patients and surgeons.

“What I liked most during my two years of research training at the Icahn School of Medicine was that I could apply what I learned in the classroom right away in real-world settings.” -Sooyun Caroline Tavolacci, MD, MSCR

 

Cardiothoracic surgery has since become her lifelong passion. She completed six years of medical school in South Korea, followed by a cardiovascular surgery sub-internship in Brescia, Italy. After graduating from medical school, and realizing that she lacked experience in clinical research, she sought a program that bridged scientific research and clinical practice, leading her to Mount Sinai’s Graduate School of Biomedical Sciences.

“The Icahn School of Medicine is unique as a pioneering model for a medical school grown directly from a hospital, not a university” she says. “The rich clinical environment, combined with strong multidisciplinary faculty, makes it ideal for studying clinical research.”

In 2021, in the middle of the COVID-19 pandemic, she entered the Master of Science in Clinical Research (MSCR) program at the Icahn School of Medicine while working on an NIH-funded study examining the serological response to the SARS-CoV-2 vaccine in lung cancer patients led by Fred Hirsch, MD, PhD, Professor and Director, Center of Excellence for Thoracic Oncology, The Tisch Cancer Institute. She described this experience as firsthand exposure to bench-to-bedside translational research. Her days began in the lung cancer clinic at the Institute and ended in the Biorepository and Pathology CoRE laboratories.

“Weekly meetings involved thoracic oncologists, thoracic surgeons, pathologists, virologists, immunologists, biostatisticians, and radiologists. This multidisciplinary collaboration and exposure to different perspectives taught me how to approach team science in research,” she says.

Dr. Tavolacci completed her master’s thesis, in which she investigated the mechanisms underlying sex-based differences in immunotherapy response in lung cancer, with Dr. Hirsch and co-mentor Rajwanth Veluswamy, MD, MSCR, a former faculty member of the Icahn School of Medicine and a graduate of the MSCR program. She presented her work at national and international meetings and published her several peer-reviewed articles during her master’s program.

“What I liked most during my two years of research training at the Icahn School of Medicine was that I could apply what I learned in the classroom right away in real-world settings,” she says. “I was extremely satisfied with the coursework and the quality of education I received.”

After completing her MSCR in June 2023, she decided to continue her research education and was accepted into the PhD in Clinical Research program.

“I developed a strong interest in biostatistics during my master’s program,” she says. “My experience was primarily in thoracic oncology, with a focus on lung cancer; however, I wanted dedicated time to learn outcomes research in cardiovascular surgery.”

After her acceptance into the PhD program, she faced significant financial hardship due to a loss in her family and visa restrictions that limited her ability to secure a job at The Mount Sinai Hospital at that time.

She considered returning to South Korea or continuing her academic journey in the United States, but instead reached out for help. In recognition of her academic excellence, she received Emergency Fund support from the Office of Postdoctoral and Student Affairs at the Graduate School of Biomedical Sciences and continued her work-study program through Westchester Medical Center in New York State. During this time, she completed her PhD coursework and conducted heart failure and transplant outcomes research under the mentorship of Suguru Ohira, MD, PhD, Cardiac Surgeon at Hartford HealthCare. This included large database analyses using the United Network for Organ Sharing registry.

Now Dr. Tavolacci balances her dissertation research with her role as a research coordinator in the Department of Cardiovascular Surgery at Mount Sinai. She credits the Icahn School of Medicine’s hospital-based model for naturally generating research questions through close interaction with surgeons, fellows, and residents.

“The clinical exposure I gain every day as a research coordinator helps me understand why these variables scientifically matter in clinical trials and studies, and it directly shapes my academic research,” she says. “With my master’s and PhD training in clinical research, I have a strong understanding of research methodology, such as study design, logistics, objectives and hypotheses, and analysis planning. This foundation is incredibly helpful in performing my role. It is a humbling experience to care for patients and to advocate for advancements in clinical research.”

Dr. Tavolacci frequently mentors prospective international applicants, particularly those navigating funding challenges in the PhD in Clinical Research program. She receives emails and LinkedIn messages from many people interested in clinical research asking how to find a mentor, identify research topics, and secure funding.

“It is challenging, and sometimes being equivalent as an international student is not enough—you have to be better to get noticed. However, people who have been through similar processes recognize your strengths.” She strives to do the same for prospective applicants by sharing her honest journey as an international student.

Dr. Tavolacci recalls what her PhD mentor, Dr. Anyanwu, said during their first meeting: “See how far you have come.” She carries this message with her whenever she faces difficulties or setbacks, using it as a reminder to keep moving forward.

In 2026, Dr. Tavolacci will present her doctoral research at various national meetings within the cardiothoracic surgery community. Throughout her academic journey, she has learned that research comes with many practical challenges. What has been most helpful to her is maintaining concentration and focus to push projects forward and see them through to completion. What she learned the hard way is that everything takes time and effort, and that there are many failures behind every achievement in academia.

Dr. Tavolacci will complete her PhD in two years and plans to enter cardiothoracic surgery residency. Her training will allow her to practice surgery while designing and conducting clinical studies and trials. Her ultimate goal is to become a surgeon-scientist.

Learn more about the Clinical Research Education Program at the Icahn School of Medicine at Mount Sinai

Mount Sinai AIHH Grand Rounds: A Thoughtful Way to Adopt AI in Health Care

Feb 10, 2026 | Artificial Intelligence, Featured, Research, School

Isaac Kohane, MD, PhD, Chair of the Department of Biomedical Informatics, Harvard Medical School, was keynote speaker of the Icahn School of Medicine at Mount Sinai’s Windreich Department of AI and Human Health (AIHH) December 2025 session of AIHH Grand Rounds.

Health care systems across the country have been increasingly using artificial intelligence (AI) systems to assist and augment what clinicians and researchers can achieve. As adoption of machine learning accelerates, thought leaders have been scrutinizing how AI is being embraced.

“Many doctors are already using these tools, such as OpenEvidence, but without visibility or oversight by health care systems,” says Isaac Kohane, MD, PhD, Chair of the Department of Biomedical Informatics, Harvard Medical School. OpenEvidence is an AI-powered clinical decision support and medical search engine.

Dr. Kohane is a prominent researcher in biomedical informatics and AI whose nearly 400 papers have been cited more than 95,000 times, according to Google Scholar. He was the keynote speaker of the Icahn School of Medicine at Mount Sinai’s Windreich Department of AI and Human Health (AIHH) December 2025 session of AIHH Grand Rounds. Dr. Kohane wants to see not just more use of AI, but more responsible use—a theme of his lecture, which was titled “A Tipping Point for Clinicians’ Influence Upon AI-Driven Clinical Decisions.”

Dr. Kohane gave a lecture, titled “A Tipping Point for Clinicians’ Influence Upon AI-Driven Clinical Decisions,” which focused on where the opportunities lie for the health care industry to use AI more, but in a thoughtful way that accounted for human values and ethics.
The AIHH Grand Rounds is a monthly seminar series hosted by Mount Sinai’s Windreich Department of AI and Human Health (AIHH). Clinicians and researchers who work extensively with AI, including Girish N. Nadkarni, MD, MPH, CPH, Chair of AIHH (left) and David L. Reich, MD, President of The Mount Sinai Hospital (right), attend to learn and discuss the latest developments in the field.
AI is transforming the health care and scientific publishing industries, with its potential to save time and effort for individuals and institutions. However, as long as there are incentives for perverse behaviors regarding AI, there will be bad actors abusing the technology, says Dr. Kohane. These fields need to collectively reset such cultures and behaviors.
A theme Dr. Kohane discussed in his lecture is the need to build in human values within AI models. There will be occasions when a broad, normative model will fail to account for the needs of an individual patient. He proposes that the responsibility for building human values in AI lies with the clinicians and researchers who use it.
A highlight of the AIHH Grand Rounds is not merely the lectures presented, but the discussions that occur after. These discussions help foster collaboration between researchers as they share ideas.

“I chose these topics for Grand Rounds because I view the Icahn School of Medicine and its leadership as among the most forward-looking in the country,” says Dr. Kohane, “and therefore they should be truly focused on setting an example in terms of accelerating adoption options that are both safe, and also enabling patients and clinicians to benefit from the complementarity of AI to human expertise, as well as changing the promotion process to reflect greater engagement with reproducibility and robust research.”

The AIHH Grand Rounds is a monthly seminar series that showcases developments in how AI, science, and medicine intersect, and features an open discussion to foster collaboration. The inaugural session launched in September 2025.

How should health systems think about engaging with AI as it pertains to patients, clinicians, and researchers in a way that is beneficial to all parties? Dr. Kohane discussed the following themes during the seminar.

Transforming the institution with AI

By their nature, large health care systems in the United States are high-revenue, low-margin businesses, and because of that, they face challenges in moving rapidly with change to avoid disruptions.

Institutionally, AI adoption has found more comfort and scalability on the administrative side of operations, including reimbursement and corporate functions. AI is a critical lever, but not a priority for health care system spending presently, according to Dr. Kohane.

However, the application of AI on the clinical side, including continuity of care, clinical operations, and quality and safety, remains nascent or in pilot stages.

“It’s actually the doctors who are leading [with AI adoption], even when their own institutions are not supporting them directly,” says Dr. Kohane.

That landscape is slowly changing as health care leaders begin to engage their clinicians with AI support where it is needed now, but it should not be at the cost of extended, effortful multi-year governance conversations, Dr. Kohane pointed out. The incentives for using AI in the practice of medicine must be focused on improving care rather than maximizing revenue.

“And so, I anticipate that the future first adoptions will happen in specialized high-end services like concierge services, primary care, or cancer care,” he says. “But eventually, it would become a requisite for the safe practice of medicine, and for meeting the expectation of our patients, that ultimately our health care systems will be propelled into more significant engagement [with AI].”

Transforming publishing and literature review with AI

“Every part of the scientific publication process—that is, the generation of manuscripts and review of manuscripts—is going to be augmented by AI,” says Dr. Kohane. “That is going to present, or is already presenting, challenges that the whole peer-review publishing industry is not well equipped to handle.”

Dr. Kohane discussed a case study in which he created a hypothesis that was incorrect, and with AI tools was ultimately able to generate data that were not only fictional, but designed by AI to avoid detection by the majority of fake-data-generation detectors.

“We’re going to really have to address, first and foremost, the incentives that drive perverse behaviors,” he says. An industry that prizes publication volume, or publishing in high-profile publications over producing work with actual scientific impact—such as important but unglamorous replication studies—is only going to drive bad actors.

In the right hands, AI will increase the efficiency and quality of scholarly scientific review. AI can serve as a prism that allows clinical and laboratory experience to be distilled into new knowledge, forming a substrate for truly lifelong medical education. “However, we have to reset the culture and incentives,” Dr. Kohane says.

Transforming AI with human values

In an industry where urgency and time matters, AI presents a strong value proposition with its capability to process large datasets and execute large volumes of actions in a blink of an eye. Time-consuming tasks can be automated by AI, but when decisions that pertain to the care of individuals with unique needs are left to a normative model that adheres to overarching policies, the individual’s needs might not be met.

The solution is not to turn away from AI, but to develop personal models that account for the needs of not just the patient at hand, but also their caretakers, doctors, or any other relevant stakeholders, says Dr. Kohane. It is about building human values within an AI model, which can flag when an individual case does not align with the normative model.

That work to develop such projects falls on the health care system, says Dr. Kohane. He introduced the Human Values Project, an international initiative led by Harvard Medical School’s Department of Biomedical Informatics, which aims to characterize how AI models respond to ethical dilemmas in medicine, measuring both their default behaviors and their capacity for alignment. And he proposed that researchers at the Icahn School of Medicine have that potential to develop their own human values-based AI models.

“My takeaway from presenting and participating in the AIHH Grand Rounds really stemmed not from the presentation itself, but from discussions I had afterwards with various leaders of the AI efforts,” says Dr. Kohane. “My sense was that more than most institutions, [Mount Sinai’s] leadership was willing to invest and take a chance on pilots of deployments of these technologies to learn fast and adapt fast. And at the same time, everybody recognized that this is very challenging, given our current regulatory environments and incentives.”

Dr. Kohane ended his presentation with a line of wisdom for participants to consider: “There is no one to lead this in the direction we want, other than us.”

Learn more about the Windreich Department of Artificial Intelligence and Human Health and AIHH Grand Rounds

Early Exposure to Peanuts Can Help Reduce the Risk of Developing Allergies in Children

Updated on Dec 2, 2025 | Allergy, Featured, Research

Over the past decades, doctors and researchers have learned a lot about food allergies, conducting many studies that have helped us get closer to understanding why such allergies might occur and, potentially, preventing them from developing.

The current understanding is that exposing young children to peanut protein may reduce the likelihood that they develop peanut allergies as they grow up. The National Institute of Allergy and Infectious Diseases (NIAID) issued guidelines recommending early introduction of peanut-containing foods to infants in 2017.

“Over the past two to three decades, we have learned a lot, and allergists and pediatricians have changed their thinking and recommendations as new evidence and studies point us one way or another,” says Scott Sicherer, MD, Director of the Elliot and Roslyn Jaffe Food Allergy Institute at Mount Sinai Kravis Children’s Hospital, who was also involved in the development of the NIAID 2017 guidelines.

How might peanut allergies—or food allergies in general—develop in people, and how might introducing peanuts at a young age help reduce this allergy risk? How can parents safely introduce peanut products to their young children? Dr. Sicherer explains the science and research behind this topic.

Scott Sicherer, MD, Director of the Elliot and Roslyn Jaffe Food Allergy Institute, and Chief of the Serena and John Liew Division of Pediatric Allergy and Immunology in Mount Sinai’s Department of Pediatrics.

Do we know what causes peanut—or food—allergies in general?
There are many ways to answer this question, but to answer broadly, it boils down to two things: environment and genetics.

Environment can include diet, the way we live, where we live, what the child and household are doing. Is there a dog in the house? How are we using antibiotics and soaps? Was the baby born by cesarian section? There is evidence that seems to link higher rates of allergies to babies born by C-section. The list could go on and on.

The genetics side has also been extensively studied. We had done studies at Mount Sinai on the role genetics might play in peanut allergies, comparing identical and fraternal twins, and found that genetics has a lot to do with it. We found a lot of heritability of allergies, where having a family history of it is also a risk factor for the baby.

Has the rate of peanut allergies in children increased over time?
Our institute at Mount Sinai looked at this rate over an 11-year period. We started in 1997, where we did a random survey of households across the United States, and asked about children and adults having peanut allergies. We did that same survey in 2002 and 2008 as well.

In 1997, we found the reported rate for children with a peanut allergy to be 0.4 percent, or1 in 250 children. In adults, that rate was 0.7 percent, or 1 in 150 adults. In 2002, that rate for children doubled to 0.8 percent, or 1 in 125 children, and the rate for adults was roughly the same, at 0.6 percent.

In 2008, we did the survey again, and I was shocked by the number for children, which was 1.4 percent, or 1 in 70 children. That’s almost a tripling from 1997, while the rate for adults in 2008 remained the same.

At first, I wondered if there was an issue with our survey. But it should have been accurate because our method was the same across the years. I was convinced when our 2008 findings were matched with studies coming out of Australia, Canada, and England at that time, which were reporting prevalence rates of more than 1 percent for children as well. So it did seem there was a real increase between 1997 and 2008.

What might have caused this increase?
One way to think about this phenomenon would be to think first about the mechanism behind allergies, which is the immune system. Our immune system has evolved over thousands of years and various exposures to the environment to fight off germs and pathogens. It has a tough job of destroying these dangerous invaders while having to recognize and smartly ignore innocent proteins, like those in foods, or types of bacteria that are helpful to our bodies.

What if the ground rules changed quickly, and the immune system was faced with relatively sudden changes that made it harder to adapt and attack the right potential dangers entering our body?

The “hygiene hypothesis” posits that our modern, industrialized society could be a cause for the increased allergy rates. Exposure to fewer or different germs, while making us healthy in some ways, could result in the immune system going out of balance and attacking things it should be ignoring, like allergens including pollens, animal dander, and foods. Add to that the many other changes in our modern world, we have a perfect storm for trouble.

Furthermore, back in the 1990s and 2000s, the prevailing understanding—based on early studies—was for mothers, if they had babies who were at high risk of developing allergy, to avoid allergens during pregnancy and breastfeeding. They were also recommended to avoid feeding babies cow milk until age one, eggs until age two, and fish and nuts until age three—these were from the American Academy of Pediatrics (AAP) in the year 2000.

By 2008, there were new studies showing that delayed introduction of allergenic foods might increase the risk of developing allergies. Around that time, I joined the AAP committee to rescind the previous recommendations.

What studies support early introduction of peanuts for reducing allergy risk?
A notable study started when Gideon Lack, MD, MSc, a professor of pediatric allergy at King’s College London, observed that in Israel, infants were often fed a peanut butter snack, Bamba, and that diagnoses of peanut allergies there were low. He conducted a study, published in Journal of Allergy and Clinical Immunology in 2008, that found that Israeli infants aged 8 to 14 months consumed a monthly median of 7.1 grams of peanut protein, and had a prevalence of peanut allergy of 0.17 percent. In the UK, the same age group consumed a monthly median of 0 grams of peanut protein, and the peanut allergy prevalence was 1.85 percent.

This prompted a landmark clinical trial, substantially funded by NIAID, called the Learning Early About Peanut (LEAP) study. The study assessed how infants ages 4 months to 11 months old with eczema and/or egg allergy—and thus at high risk for developing peanut allergies—would fare if fed peanut snacks until 60 months of age, compared with a group that avoided peanut products. The results, published in The New England Journal of Medicine in 2015, found that the prevalence of peanut allergies among those following the advice was 17.3 percent in the avoidance group, whereas the consumption group’s prevalence was 0.3 percent.

What do medical professionals and organizations recommend now?
In 2008, NIAID established a committee—which Hugh Sampson, MD, the Kurt Hirschhorn, M.D./The Children’s Center Foundation Professor of Pediatrics at the Icahn School of Medicine at Mount Sinai, was part of—to develop guidelines for the diagnosis and management of food allergies. At the time, the committee, like the AAP, didn’t make any active recommendations regarding early introduction of allergenic food, other than not delaying them in a set of guidelines in 2010.

When the LEAP study results came out, NIAID updated its guidelines in 2017—Dr. Sampson and I were authors—this time encouraging early peanut introduction, and with instructions about how to do it. There’s a resource called Appendix D that describes how to get peanuts safely into the diet, because peanuts and peanut butter can be a choking hazard for babies. Professional medical organizations, including the AAP and the American Academy of Family Physicians, have since adopted similar recommendations on the early introduction of peanuts. Additional guidelines extrapolate the advice to other common allergens—like milk, egg, and tree nuts—for them to be included in the diet in infant-safe forms on a regular basis, essentially treating solid foods as equivalent whether they are common allergens or not.

How can I begin introducing peanuts early for my child, safely?
If you’re nervous or worried, it’s helpful to talk to your pediatrician. They can walk you through ways of smoothing out peanut products into water, pureed fruits, or vegetables to give them safely. They’ll also be able to let you know how often and how much to feed your baby, as it does require a routine diet for it to confer a protective effect.

The bottom line is: If your baby is otherwise healthy and hasn’t had any problems with food allergies, typical food allergens can be added to a diverse diet, just like any other food in its safe form.

However, if your baby is already showing signs of allergy or problems with various foods, absolutely talk to your pediatrician, who may work with an allergist to fine-tune a path forward. The exciting thing is we do have treatments for food allergy now, and there are many great things happening in the field. Talking to your doctor can help your child lead a healthy, fulfilling life without the overhanging fear of triggering food allergies.

Appendix D instructions for home feeding of peanut protein for a low-risk infant

General instructions Feeding instructions
1. Feed your infant only when they are healthy; do not feed if they have a cold, are vomiting, or have diarrhea or other illnesses. 1. Prepare a full portion of the peanut-containing food.
2. Give the first peanut feeding at home, not at a daycare center or restaurant. 2. Offer your infant a small part of the peanut serving on the tip of the spoon.
3. Make sure at least one adult is able to pay full attention to the infant, without distractions. 3. Wait 10 minutes.
4. Make sure to spend at least two hours with the infant after feeding, to watch for any signs of allergic reaction. 4. If there’s no allergic reaction after the small taste, then slowly give the remainder of the peanut-containing food at the infant’s usual eating speed.

Stories Behind the Science: Preparing to Fight the Next Epidemic

Updated on Sep 9, 2025 | COVID-19, Featured, Research

Stories Behind the Science: Preparing to Fight the Next Epidemic

Kris White, PhD, Assistant Professor of Microbiology at the Icahn School of Medicine at Mount Sinai (right), and lab member Isidora Suazo, PhD, Postdoctoral Fellow (left), are part of a research network to discover new drugs for a viral epidemic preparedness initiative.

It was June 2022, and Peter White, a lawyer from Point Lookout, Long Island, was in Florida attending a work event. As he was waiting for his flight home, he started to feel sick.

“By the time I landed, I was very sick with a heavy pressure in my chest,” said Mr. White, 67. “Any time I had previously felt like this, it had always, at a minimum, developed into bronchitis or pneumonia.”

Mr. White was worried it was COVID-19, which could spell poor outcomes given his underlying respiratory condition. “When I get a cold, it has a tendency to morph into bronchitis and, at times, pneumonia. I’ve had walking pneumonia several times, as well as regular pneumonia,” he said. “I can’t count the number of times I have had bronchitis.”

His doctor advised him to go to the emergency room to seek treatment for COVID-19. Thankfully, just months prior—in December 2021—the antiviral medication Paxlovid (nirmatrelvir/ritonavir) from Pfizer had become available via emergency use authorization for the treatment of COVID-19.

“I did not feel better right away,” Mr. White recalled. “However, I did not get worse, which was huge given my prior history, and it was a comfort for me that the drug was working.”

“Thankfully, his bout with COVID-19 ended up being uneventful, because he was able to take Paxlovid quickly and clear it out of his system,” said Kris White, PhD, Assistant Professor of Microbiology at the Icahn School of Medicine at Mount Sinai and Mr. White’s son.

“The COVID-19 pandemic really taught us the value of having treatments ready to test and deploy quickly when an epidemic hits,” said Dr. White.

Mount Sinai has been working toward that goal, in part through its involvement in the Antiviral Drug Discovery (AViDD) Centers for Pathogens of Pandemic Concern, established in 2022 by the National Institutes of Health (NIH). Dr. White’s lab is among several at Mount Sinai contributing research as part of the AViDD Centers, developing antiviral drugs to tackle future outbreaks.

Dr. White (second from right) with his father, Peter (second from left), with five of Dr. White’s children and two nieces. Peter caught COVID-19 in 2022, but with Paxlovid antiviral treatment, it did not develop into something severe, for which Mr. White was at high risk.

However, recent cuts to NIH funding have threatened to stall progress. “We were halfway to the finishing point,” said Dr. White. “With our funding cut, it is like we have half a drug—and that is of no good to anyone.”

Read about how antiviral research can help us navigate future epidemics, and challenges the AViDD Centers face.

‘It Could Have
Been A Very
Different Pandemic’

The issue with relying solely on pharmaceutical companies to develop drugs for an epidemic is that until the health crisis is at hand, there is no incentive for them to carry out such research, noted Dr. White.

That was the case with COVID-19—when it hit in early 2020, there were few if any drug candidates to test right away. Pharmaceutical companies and academic institutions scrambled to find new compounds, or repurpose old ones, that could treat the infection.

Pfizer had a lead, PF-07321332, which had potential for targeting SARS-CoV-2, the virus that causes COVID-19. It was developed in 2003 to address the severe acute respiratory syndrome (SARS) outbreak in 2002-2004. But before it could make it into human clinical trials, the outbreak was contained and development was discontinued.

Even promising compounds take time before they can be used on patients. It wasn’t until March 2021 that Pfizer announced it would test PF-07321332 in humans in a phase 1 trial. In June that year, a phase 2/3 trial was carried out to test its effectiveness, and in December, the compound, which had been named Paxlovid, received its emergency-use authorization.

“We’ve seen that given the will, we can quickly test the effectiveness and safety of treatments and make them available to the public,” said Dr. White. “Imagine if we had compounds ready to test right at the beginning, it could have been a very different pandemic.”

For Dr. White’s father, that difference was between life and death. “Paxlovid was a game changer for me,” said Mr. White. “Knowing that I was most likely going to suffer, but not die, from COVID-19 was good news. It would have been better if this drug was available sooner rather than later.”

Having treatments available early on not only reduces transmission, disease severity, and mortality rates, but also has an impact on health policy.

“Having such an antiviral could even have mitigated the need for severe lockdowns, or even vaccine mandates,” said Dr. White. For people who might be ineligible for vaccines, or were resistant to such mandates, having a treatment available would have provided options for health providers and policymakers, he explained.

March 2020

The World Health Organization declares COVID-19 a pandemic.
September 2020

Pfizer completes pharmacokinetic study of PF-07321332 in rats.
March 2021

PF-07321332 tested in a first-in-human phase 1 trial.
June 2021

Phase 2/3 trial for PF-07321332 begins.
December 2021

PF-07321332 receives emergency-use authorization from the FDA, is named Paxlovid.

Kickstarting the Process

Dr. White, seen dressed in protective clothing, works with Biosafety Level 2 and Biosafety Level 3 viruses as part of his work. His lab’s research includes drug discovery of new antivirals and building up animal models of viral infection.

Following the authorization of Paxlovid, the National Institute of Allergy and Infectious Diseases (NIAID), part of the NIH, realized the benefits of having promising drug candidates ready to be tested at the onset of an outbreak.

“Academic institutions like Mount Sinai were perfectly suited for kickstarting that discovery work,” said Dr. White, whose lab studies viral-host interactions, develops cell culture and animal models of viral infection, and performs other antiviral drug discovery work.

Members of Dr. White’s lab, from left to right: Briana McGovern, BS, Senior Research Associate; Meg Gordon, BA, Research Associate; Dr. White; Dr. Suazo; Jared Benjamin, MS, Research Associate.

“Historically, drug discovery was a process that took billions of dollars, and was usually undertaken by pharmaceutical companies,” said Dr. White. “Now, with technological advances and artificial intelligence, the cost of that process has been brought down to millions of dollars, which is a realm that the federal government can provide funding for.”

NIAID awarded a total of $577 million in 2022 toward the creation of nine AViDD Centers, which collectively work to discover better treatments for SARS-CoV-2 and other coronaviruses, as well as six other pathogen families of concern, which include Ebola, Zika, and other cold-causing viruses. Mount Sinai researchers received a total of $16 million and are involved in four of the nine centers.

Progress
Cut Short

Dr. White handling cell cultures stored in a cold storage unit in his lab.

The AViDD Centers were conceived as a five-year project. However, in March 2025—three years into the Centers’ inception—the Centers for Disease Control and Prevention canceled more than $11 billion in funding earmarked for pandemic response.

This included funding for the AViDD Centers, where researchers had the remainder of their unspent budget terminated immediately, pulling out the rug from under several projects.

“I’ve had to let people go from my lab, and we’re currently working in an unfunded state for the AViDD project,” said Dr. White. “We’re only continuing because we had prepaid for certain things before the funding cutoff.”

The most advanced drug developed thus far was basically a better Paxlovid for targeting coronaviruses, but without the need for the ritonavir component, said Dr. White. This is critical because the ritonavir component severely limits the use of Paxlovid in some patients due to drug interactions with other drugs. That compound is more or less ready for a pharmaceutical company to take over for clinical trial testing, with its patents remaining open access, as directed by the NIH.

“We have an excellent coronavirus drug ready to go to clinical trials, but every other drug for the other viruses—paramyxovirus, filovirus, flavivirus, and more—none of them are even close,” he said.

At best, work on the other viruses are close to getting their animal model efficacy data, which is crucial for moving the drugs into human models, said Dr. White. “Getting animal model data is hard enough in five years. Without funding for the remaining two years, getting that data in just three years is almost impossible.”

The drug dispensing robotics system, operated by research associate Mr. Benjamin in this photo, is part of the workflow in which the lab tests new antiviral compounds, said Dr. White. The equipment functions similar to an inkjet printer, and is able to print drugs into a plate format.
Dr. White’s lab had been working on animal models of coronaviruses, flaviviruses, and enteroviruses, and with funding for AViDD Centers abrupted halted, cultures remain in cold storage, waiting for work to resume.
Mr. Benjamin is monitoring the high throughput liquid handler system, which increases the number of samples that can be tested. Throughput is what drives drug discovery, and the lab was able install the equipment thanks to AViDD Centers funding, said Dr. White.

Operating costs for AViDD projects are on a larger scale because they involve high-throughput structural biology and biochemistry that run millions of dollars per year, noted Dr. White. Researchers are reaching out for patchwork funding to keep operations going, including from the Department of Defense, NIH, not-for-profit organizations such as the Drugs for Neglected Diseases initiative, and philanthropy.

Getting continued funding is crucial because viral outbreaks do not take breaks.

“At our labs, we’ve been focusing on Zika virus disease and dengue fever, and these are viral infections we’ve already seen on our shores but still have no treatments for,” said Dr. White.

“At the end of the day, I want to be able to keep my dad and many other people like him safe when—and not if—the next viral outbreak occurs,” said Dr. White. “We were already caught by surprise once with COVID-19. Let’s not have history repeat itself again.”

Advancing Our Understanding of MS: One Researcher’s Quest to Uncover Hidden Brain Changes

Updated on Aug 28, 2025 | Featured, Research

Caption: An image from a standard clinical MRI, left, compared with an image from the same person using advanced methods on a stronger, 7T MRI. Compared to the standard clinical MRI, the research MRI is much clearer and multiple sclerosis lesions (dark spots) are more clearly seen.

How can clinicians better predict who will transition from relapsing to progressive Multiple Sclerosis (MS)? And can we use imaging techniques to diagnose MS more accurately and to select the right treatments for individual patients?

“These are questions people with MS and their doctors struggle with frequently, and so we hope to at least begin to answer them through our research,” says Erin S. Beck, MD, PhD, Assistant Professor of Neurology at the Icahn School of Medicine at Mount Sinai and a neurologist at the Corinne Goldsmith Dickinson Center for Multiple Sclerosis.

Erin S. Beck, MD, PhD

Dr. Beck, whose research program explores the intersection of neuroimaging, immunology, and clinical  care, is seeking answers using advanced magnetic resonance imaging (MRI).

“At the heart of our work is a commitment to advancing both science and patient care,” says Dr. Beck. “By deepening our understanding of cortical lesions and the inflammatory processes that drive them, we are helping to shape a more precise and informed future for MS diagnosis, treatment, and care.”

For MS patients, the implications of this work are significant. If these imaging methods are validated, cortical lesion detection could become part of routine MRI protocols within the next several years. This could enable earlier and more accurate diagnosis, improve predictions of how a patient’s disease will unfold, and support more personalized treatment decisions.

Dr. Beck’s lab studies how lesions in the brain and spinal cord form, evolve, and repair in MS and other related diseases. A central focus of her lab’s research is understanding MS lesions in the cortex, the outer layer of the brain, which helps to control most of the brain’s functions. While white matter lesions are well-established markers of MS activity, they explain only part of the disease.

Cortical lesions, though harder to detect with standard imaging, are increasingly recognized as widespread in MS and closely tied to physical disability and cognitive impairment, particularly in progressive forms of the disease. It is unclear whether current MS treatments, which work by stopping new lesions from forming in the rest of the brain, are also effective at stopping cortical lesion formation.

Using state-of-the-art imaging technologies—including more powerful, 7 tesla (T) MRI scanners—Dr. Beck combines MRI with cerebrospinal fluid (CSF) and blood analysis to investigate the formation, repair, and clinical significance of cortical lesions. Her research integrates imaging with measures of inflammation, aiming to discover how immune processes contribute to lesion development and disease progression.

One of her lab’s key contributions is the development of MRI methods to improve cortical lesion detection using widely available 3T MRI scanners. These include IR-SWIET, a novel MRI method specifically optimized for visualizing cortical lesions. The lab is currently testing whether IR-SWIET could be useful for MS diagnosis and for monitoring response to treatment.

Her investigations also extend to patients with Radiologically Isolated Syndrome (RIS)—those whose MRI scans show MS-like lesions despite having no symptoms. Through advanced imaging and CSF studies, she hopes to identify biomarkers that distinguish individuals likely to develop clinical MS from those who will remain symptom-free.

Dr. Beck earned her MD/PhD from Columbia University. Following her neurology residency at New York–Presbyterian/Columbia and a neuroimmunology fellowship at the National Institutes of Health, she joined Mount Sinai’s faculty in 2021. Since then, she has been building her research program at the intersection of neuroimaging, immunology, and clinical MS care.

Dr. Beck’s research has been recognized with awards such as a Clinician Scientist Development Award and a Career Transition Fellowship from the National MS Society. Her findings have been published in leading journals, including Brain Communications, Investigative Radiology, and Human Brain Mapping.

By Julia Bonem, a volunteer at the Corinne Goldsmith Dickinson Center for Multiple Sclerosis

Learn more about the Corinne Goldsmith Dickinson Center for Multiple Sclerosis

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