Updated on Nov 19, 2025 | Artificial Intelligence, Featured, Research
Akhil Vaid, MD, left, and Girish Nadkarni, MD, MPH, right, are working to make artificial intelligence models more feasible for reading electrocardiograms, using a novel transformer neural network approach.
Electrocardiograms (ECGs) are often used by health providers to diagnose heart disease. At times, irregularities in the recordings are too subtle to be detected by human eyes but can be identified by artificial intelligence (AI).
However, most AI models for ECG analysis use a particular deep learning method called convolutional neural networks (CNNs). CNNs require large training datasets to make diagnoses, which spell limitations when it comes to rare heart diseases that do not have a wealth of data.
Researchers at the Icahn School of Medicine at Mount Sinai have developed an AI model, called HeartBEiT, for ECG analysis, which works by interpreting ECGs as language.
The model uses a transformer-based neural network, a class of network that is unlike conventional networks but does serve as a basis for popular generative language models, such as ChatGPT.
Here’s how HeartBEiT works as an artificial intelligence deep-learning model, and how it compares to CNNs.
HeartBEiT outperformed conventional approaches in terms of diagnostic accuracy, especially at lower sample sizes. Study findings were published in
npj Digital Medicine on June 6.
Akhil Vaid, MD, Instructor of Data-Driven and Digital Medicine, was lead author, and
Girish Nadkarni, MD, MPH, Irene and Dr. Arthur Fishberg Professor of Medicine, was senior author.
In this Q&A, Dr. Vaid discusses the impact of this new AI model on reading ECGs.
What was the motivation for your study?
Deep learning as applied to ECGs has had much success, but most deep learning studies for ECGs use convolutional neural networks, which have limitations.
Recently, the transformer class of models has assumed a position of importance. These models function by establishing relationships between parts of the data they see. Generative transformer models such as the popular ChatGPT utilize this understanding to generate plain-language text.
By using another generative image model, HeartBEiT creates representations of the ECG that may be considered “words,” and the whole ECG may be considered a single “document.” HeartBEiT understands the relationship between these words within the context of the document, and uses this understanding to perform diagnostic tasks better.
What are the implications?
Our model forms a universal starting point for any ECG-based study. When comparing our model to popular CNN architectures on diagnostic tasks, HeartBEiT ended up with equivalent performance and better explanations for the model’s thinking and choices using as little as a tenth of the data required by other approaches.
Additionally, HeartBEiT generates very specific explanations of which parts of an ECG were most responsible for pushing a model towards making a diagnosis.
What are the limitations of the study?
Pre-training the model takes a fair amount of time. However, fine-tuning it for a specific diagnosis is a very quick process that can be accomplished in a few minutes.
HeartBEiT was compared against other conventional AI methods on diagnostic measures, including left ventricular ejection fraction ≤40%, hypertrophic myopathy, and ST-elevation myocardial infarction, and was found to perform better.
How might these findings be put to use?
Deployment of this model and its derivatives into clinical practice can greatly enhance the manner in which clinicians interact with ECGs. We are no longer limited to models for commonly seen conditions, since the paradigm can be extended to nearly any pathology.
What is your plan for following up on this study?
We intend to scale up the model so that it can capture even more detail. We also intend to validate this approach externally, in places outside Mount Sinai.
Learn more about how Mount Sinai researchers and clinicians are leveraging machine learning to improve patient lives
Updated on Jun 15, 2023 | Featured, Research, School, Vaccines
From left to right, Peter Palese, PhD, Horace W. Goldsmith Professor of Medicine; Miriam Merad, MD, PhD, Mount Sinai Professor in Cancer Immunology; Özlem Türeci, MD, Chief Medical Officer of BioNTech; Uğur Şahin, MD, Chief Executive Officer of BioNTech; Dennis Charney, MD, Anne and Joel Ehrenkranz Dean of Icahn School of Medicine at Mount Sinai
One of the great tools that helped turn the tide of the COVID-19 pandemic was the use of vaccines, which prevented millions of deaths and hospitalizations in the U.S. and around the world. Key vaccines were those based on messenger RNA (mRNA) technology, which provide information for the molecules that teach the cells in the body to generate proteins used by viruses or cancers, allowing the body’s immune system to recognize and fight off future infections or transformed cancer cells.
The Icahn School of Medicine at Mount Sinai honored the efforts of executives of German biotechnology firm BioNTech, which partnered with Pfizer to develop and make available one of the most widely used COVID-19 vaccines in the country, during its 54th Commencement on Thursday, May 11. Uğur Şahin, MD, Chief Executive Officer of BioNTech, and Özlem Türeci, MD, its Chief Medical Officer, received honorary Doctor of Science degrees.
Research into mRNA technology for vaccines goes back to the 1990s, and has grown in leaps and bounds since, said Dr. Türeci in a guest lecture hosted by the Marc and Jennifer Lipschultz Precision Immunology Institute, held separately from the Commencement.
The COVID-19 pandemic provided an opportunity for the technology to be adapted at a large scale, and the momentum gained and lessons learned was only the starting point to pave the way for greater heights for the development of mRNA vaccines, she said.
In this Q&A, Drs. Şahin and Türeci spoke about what the future of mRNA vaccines could look like.
After two years of COVID-19 vaccines:
- An estimated 18 million hospitalizations were prevented
- More than 3 million deaths were avoided
Source: New York City-based foundation The Commonwealth Fund
Percentage vaccinated in United States by manufacturer:
- Pfizer/BioNTech: 60%
- Moderna: 37%
- Johnson & Johnson: 3%
Source: Centers for Disease Control and Prevention
What are some active areas of research in which mRNA technology is being worked on?
Dr. Şahin: There are investigational cancer vaccines in which mRNA technology is being used to deliver instructions to generate antibodies or cytokines. This technology can theoretically be used to deliver any bioactive molecule.
Our focus at the moment is the development of cancer vaccines, and one special application of cancer vaccines we’re working on is the so-called “personalized cancer vaccines.” mRNA technology is particularly well suited to deliver a vaccine that consists of mutations of the tumor identified from the patient.
Dr. Türeci presenting to members of the Marc and Jennifer Lipschultz Precision Immunology Institute.
What is it about mRNA technology that makes it so well suited for cancer vaccines?
Dr. Türeci: We have been interested in cancer vaccines all along, and tried different technologies, and mRNA is the delivery technology that comes with its own edge. Its immunogenicity is very versatile and its transience has the potential to lead to a favorable safety profile. These characteristics are the reasons why we chose mRNA to deliver cancer antigens.
Any solid cancer could be appropriate for application. We have ongoing clinical trials in melanoma, head-and-neck cancer, pancreatic cancer, and non-small cell lung cancer.
Beyond cancer vaccines, we believe any bioactive cancer immunotherapy that is based on protein could be delivered by mRNA.
What about non-cancer diseases? Is mRNA technology suitable there?
Dr. Türeci: There are other areas, such as infectious diseases, in which mRNA could have an advantage. As long as you have the right protein structure to stimulate an immune response, you can theoretically also use mRNA here.
There are clinical trials in infectious diseases: COVID-19, for example, but also malaria or shingles.
What are some current limitations of mRNA technology? And how are researchers working to overcome those?
Dr. Türeci: We are very far advanced in the delivery component of the technology, and these advancements have made COVID-19 vaccines, as well as cancer vaccines in clinical testing, feasible. However, if you want to target specific organs, you need specialized, targeted delivery technologies.
For example, if you want to address something in the brain, you need a delivery technology that brings the mRNA into the brain. There may be monogenetic diseases in which the sample protein is deficient in the organ, and so limits how the mRNA can be expressed there.
So the lipid nanoparticle used to contain the COVID-19 vaccine, for example, might not be applicable for any other organs?
Dr. Türeci: This delivery technology was specifically designed and developed to deliver mRNA to the lymphatic system. If the mRNA needs to be delivered to different organs, it required new formulation.
When the public first became aware of mRNA technology through COVID-19 vaccines, there was skepticism. Do you envision similar skepticism as new mRNA vaccines roll out, and if so, how can we dispel such skepticism?
Dr. Türeci: Skepticism can only be addressed by transparent communication, through the disclosure of data, and proper education. I think there is a zeitgeist of skepticism. That skepticism isn’t necessarily specific to mRNA technology. But once they start to understand the mechanisms behind the technology, and the rationale of why we’re working on it, we can start to dispel it.
Do you foresee mRNA technology to grow exponentially into the future?
Dr. Şahin: Yes, mRNA vaccines could be really big, but it will happen slowly. It will take a few more years, but we are starting to see really promising candidates using this technology.
Updated on Nov 19, 2025 | Artificial Intelligence, Featured, Research
AI Spotlight: Forecasting ICU Patient States for Improved Outcomes
Girish Nadkarni, MD, MPH, and Faris Gulamali
Artificial intelligence (AI) and machine learning (ML) have seen increasing use in health care, from guiding clinicians in diagnosis to helping them decide the best course of treatment. However, AI still has much unrealized potential in various health care settings.
Mount Sinai researchers are exploring bringing AI into intensive care, and developed Spatial Resolved Temporal Networks (SpaRTeN), a model to assess high-frequency patient data and generate representations of their state in real time.
The work was presented at the Time Series Representation Learning for Health workshop on Friday, May 5, hosted by the International Conference for Learned Representations, a premier gathering dedicated to machine learning.
Hear from Girish Nadkarni, MD, MPH, Irene and Dr. Arthur Fishberg Professor of Medicine at the Icahn School of Medicine at Mount Sinai and the leader of the SpaRTeN research, and Faris Gulamali, medical student at Icahn Mount Sinai and member of the Augmented Intelligence in Medicine and Science lab, on what lay behind creating the model and what it could achieve for patients.
What was the motivation for your study?
A growing amount of research is indicating the need to redefine critical illness by biological state rather than a non-specific illness syndrome. Advances in genomics, data science, and machine learning have generated evidence of different underlying etiologies for common ICU syndromes. As a result, patients with the exact same diagnosis can have entirely different outcomes.
What are the implications?
In the ICU, representations of a patient can be used to guide personalized treatments based on personalized diagnoses rather than generic treatments with empirical diagnoses.
What are the limitations of the study?
In this study, we only looked at using one type of data at a time in real time. For example, we looked primarily at measures of intracranial pressure. However, the ICU has many types of data being output simultaneously. Future work hopes to integrate all the different types of data such as electrocardiograms, blood pressure, and imaging to improve patient representations.
How might these findings be put to use?
These patient representations are being combined with data on medications and procedures to determine how to optimize patient treatment based on underlying state rather than common illness syndromes.
What is your plan for following up on this study?
In this study, we focused primarily on creating the algorithm and showing that it works for the case of intracranial hypertension. In future studies, we would like to integrate multiple data modalities such as imaging, electrocardiograms, and blood pressure as well as intervention-based data such as medications and procedures to determine precise empirical interventions that lead to improvements in short-term and long-term patient outcomes.
Learn more about how Mount Sinai researchers and clinicians are leveraging machine learning to improve patient lives
Updated on Apr 7, 2023 | Cardiology, Featured, Research
Annapoorna S. Kini, MD, Director of the Cardiac Catheterization Laboratory at The Mount Sinai Hospital, was principal investigator of the late-breaking clinical trial.
Even after high-intensity statin therapy, a considerable residual risk exists for heart attack and stroke among adults with coronary artery disease (CAD). A clinical study led by Mount Sinai offers strong evidence that aggressive lipid lowering with a proprotein convertase subtilisin kexin type 9 inhibitor (PCSK9i), along with a statin, can significantly reduce that threat and potentially help doctors identify patients who would benefit most from intensification of treatment to change their coronary plaque morphology and composition.
The findings were presented by principal investigator Annapoorna S. Kini, MD, Director of the Cardiac Catheterization Laboratory at The Mount Sinai Hospital, as a late-breaking clinical trial at the American College of Cardiology/World Congress of Cardiology meeting in New Orleans in March.
The study, known as Yellow III, used advanced multimodality imaging to show favorable plaque characteristics after a 26-week regimen of evolocumab, including substantial reductions in total cholesterol, LDL cholesterol, and total/HDL cholesterol ratios. More specifically, the investigation showed a significant increase in the minimum fibrous cap thickness (FCT) through optical coherence tomography (OCT), reduction in lipid core burden index at the maximal 4-mm segment (maxLCBI4mm) through near-infrared spectroscopy, and reduction in atheroma volume through intravascular ultrasound in angiographically nonobstructive lesions.
“By using all three modalities for the first time in a study of this type we were able to demonstrate a measurable improvement in fibrous cap thickness, as well as in plaque volume,” says Dr. Kini, Zena and Michael A. Wiener Professor of Medicine (Cardiology) at the Icahn School of Medicine at Mount Sinai. “In addition, blood samples were drawn to enable us to conduct a gene expression analysis of peripheral blood mononuclear cells. This will help us uncover through ongoing research the molecular mechanisms responsible for beneficial changes in atherosclerotic lesions of patients treated with evolocumab.”
The investigation showed a significant increase in the minimum fibrous cap thickness through optical coherence tomography (OCT) imaging. Thicker fibrous caps are associated with more stable plaques that are less prone to rupture and subsequent adverse cardiac events.
Prior studies have established the ability of PCSK9 inhibitors—injectables that block PCSK9 proteins from breaking down LDL receptors—to reduce residual cardiovascular risk in statin-treated patients. As a result, the 2018 American College of Cardiology/American Heart Association cholesterol guidelines recommended the use of PCSK9 inhibitors in patients with stable CAD if sufficient LDL-lowering was not achieved on maximally tolerated doses of statins. In the Yellow III trial, 137 patients scheduled for elective coronary angiography were prescribed maximum-dosage statin therapy for at least four weeks before undergoing multimodality intracoronary imaging. They were then given evolocumab (140 mg) every two weeks for 26 weeks and reimaged to assess changes in plaque morphology and composition.
The gene expression analysis of peripheral blood mononuclear cells was a particularly important part of the Yellow III study because it could potentially lead to the development of biomarkers able to predict which patients would benefit the most from different approaches to lipid lowering. Researchers found that fibrous cap thickness did not improve in 20 percent of patients. The hope is that a genotypic characterization of patient response will ultimately reveal which patients should remain on statins, which should be put on a PCSK9 inhibitor, and which might benefit from combination therapy.
“We believe studies like ours can help physicians personalize therapies for their patients with coronary artery disease,” says Dr. Kini, a renowned interventionalist. “The first step could well be a recommendation for lifestyle modification, like exercise and diet. But it is important for cardiologists to know who could also benefit from the addition of a high-intensity PCSK9 inhibitor, particularly in the case of statin-treated patients with multiple risk factors.”
Mar 23, 2023 | Alumni, Featured, Research
Seated, from left: Sandra K. Masur, PhD, FASCB; Talia H. Swartz, MD, PhD, MSSM ’08, MSH ’13; Lakshmi A. Devi, PhD; Marta Filizola, PhD; Jessica R. Moise; Swan N. Thung, MD, FAASLD; and Kenneth Davis, MD, CEO of Mount Sinai Health System. Standing, from left: Patricia Kovatch; Ramon Parsons, MD, PhD; Bruce E. Sands, MD, MS; I. Michael Leitman, MD, FACS; Burton A. Cohen, MD, MSH ’79; and Dennis Charney, MD, Anne and Joel Ehrenkranz Dean, Icahn School of Medicine at Mount Sinai.
The Mount Sinai Alumni Association and Icahn School of Medicine at Mount Sinai presented accomplished physicians, researchers, educators, and administrators with the 2023 Jacobi Medallion, one of Mount Sinai’s highest awards. The annual ceremony was held Wednesday, March 15 at the Plaza Hotel.
The recipients of the Jacobi Medallion have made exceptional contributions to the Mount Sinai Health System, Icahn Mount Sinai, the Mount Sinai Alumni Association, or the fields of medicine or biomedicine.
View the digital program
Watch the In Memoriam video
Burton A. Cohen, MD, MSH ’79
Radiologist, New York Medical Imaging Associates
Associate Clinical Professor, Department of Diagnostic, Molecular and Interventional Radiology
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Cohen
Lakshmi A. Devi, PhD
Mount Sinai Professor in Molecular Pharmacology
Professor, Department of Pharmacological Sciences, Nash Family Department of Neuroscience, and Department of Psychiatry
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Devi
Marta Filizola, PhD
Dean, Graduate School of Biomedical Sciences
Sharon and Frederick Klingenstein/Nathan Kase, MD Professorship
Professor, Department of Pharmacological Sciences, Nash Family Department of Neuroscience, and Windreich Department of Artificial Intelligence and Human Health
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Filizola
Patricia Kovatch
Dean for Scientific Computing and Data
Professor, Department of Genetics and Genomic Sciences, and Pharmacological Sciences
Icahn School of Medicine at Mount Sinai
Watch a video of Dean Kovatch
I. Michael Leitman, MD, FACS
Dean for Graduate Medical Education
Professor, Department of Surgery, and the Leni and Peter W. May Department of Medical Education
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Leitman
Jessica R. Moise
Senior Associate Dean for Sponsored Programs, Grants and Contracts Officer
Icahn School of Medicine at Mount Sinai
Watch a video of Dean Moise
Ramon Parsons, MD, PhD
Icahn Scholar
Director, The Tisch Cancer Institute and Mount Sinai Health System Tisch Cancer Center
Ward-Coleman Chair in Cancer Research
Professor and Chairman, Department of Oncological Sciences
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Parsons
Bruce E. Sands, MD, MS
Dr. Burrill B. Crohn Professor of Medicine Professor
Professor and Chief, Dr. Henry D. Janowitz Division of Gastroenterology
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Sands
Swan N. Thung, MD, FAASLD
Professor, Lillian and Henry M. Stratton-Hans Popper Department of Pathology, Molecular and Cell-Based Medicine
Icahn School of Medicine at Mount Sinai
Watch a video of Dr. Thung
Updated on Mar 17, 2023 | COVID Response, COVID-19, Featured, Research
While COVID-19 community transmission, mortality, and hospitalization rates have come down across the country in recent months, the efforts to understand more about SARS-CoV-2, the virus responsible for COVID-19, continue at full speed. “The energy is still robust,” says Judith Aberg, MD, Chief of Infectious Diseases for the Mount Sinai Health System and Dr. George Baehr Professor of Clinical Medicine at the Icahn School of Medicine at Mount Sinai.
Judith Aberg, MD
Much research progress has been made since COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020, but more work remains to be done.
“At all levels, from academic institutions to federal agencies, resources are still being poured into studying COVID-19 and this level of dedication is unlikely to go away anytime soon.”
Judith Aberg, MD
“It is precisely because, as a community, we have put so much effort into studying COVID-19 that we were able to learn so much about the virus and come up with vaccines and therapeutics at an unprecedented pace,” says Miriam Merad, MD, PhD, Director of the Marc and Jennifer Lipschultz Precision Immunology Institute, and Mount Sinai Professor in Cancer Immunology.
How has COVID-19 knowledge grown over the years?
A recent breakthrough was learning why COVID-19 affects older people more severely than children, says Dr. Merad. In many other respiratory diseases, such as influenza, typically both very young and very old people are most susceptible to complications.
“One of the biggest factors we’ve discovered is that age affects innate immune response,” she says. Older individuals are more likely to have a defective response in which their type I interferon activity is less likely to mount an antiviral or anti-inflammatory response, she adds.
Understanding the links of age to inflammatory response had also been a big piece in solving the COVID-19 puzzle, Dr. Merad says.
“It appears that SARS-CoV-2 might not be directly destroying organs. Rather, pathogenic-led inflammation might be doing so instead.”
Miriam Merad, MD, PhD
While SARS-CoV-2 is in the class of coronaviruses, very little was known about its specific pathophysiology, how it infects cells and induces injury, and how the host can control the virus. The scientific community has made inroads into these fields over the past year, especially in recent months, Dr. Merad notes.
Miriam Merad, MD, PhD
At the start of the pandemic, there were also no objective biomarkers to characterize the disease. Today, researchers have identified various measures, including platelet hyperactivations, microclots, and immune and microbiome dysfunction, as ways to analyze the impacts of COVID-19 on the body, especially for post-acute sequelae of COVID-19, the condition colloquially known “long COVID.”
“It’s really bleeding-edge,” says David Putrino, PhD, Director of Rehabilitation Innovation at the Mount Sinai Health System. “It has really coalesced over time, and has taken two years before impressive articles were coming out about meaningful biomarkers.”
How had COVID-19 research been challenging?
“It is really difficult to do research in the middle of a pandemic,” recalls Dr. Merad. With measures in place to keep staff safe from infection, as well as prevent lab leaks, it became challenging to develop animal models. Additionally, given that COVID-19 was a new disease, there were few good models to start with, she adds.
Barriers to knowledge, tools, or resources also made studying COVID-19 an uphill task. As the disease has symptoms that span multiple specialties, including neurology, immunology, pulmonology, cardiology, and more, an effective effort into studying the pathogen required broad capabilities.
David Putrino, PhD
“I’m a neuroscientist, focusing on electrophysiology of the brain, and had a set of tools I was comfortable using,” says Dr. Putrino. “But along came COVID-19 and suddenly I had to become an expert on immune physiology, on drawing blood, and running a wet lab.”
“Collaboration became necessary, especially with people outside our usual fields.”
David Putrino, PhD
“While I feel fortunate that I’m in a position from a funding and career standpoint that can support my needs for long COVID research, many others aren’t as fortunate to develop those skill sets,” Dr. Putrino says. The reality of many scientists needing to keep their labs running and applying for grants could mean it was easier to relegate COVID-19 research to someone else, he adds.
The nascent field of COVID-19 research, especially for long COVID, means the scientific community is still divided on various definitions. But with the pandemic dying down, researchers are able to communicate and collaborate more effectively across the country on standards and definitions when it comes to conducting research or collecting data, especially as scientific conferences return in full force, Dr. Merad says.
What are some things we still don’t know about COVID-19?
On the clinical side, it is not clear for hospitalized patients what are the best immune modulating therapies or strategies. “When should we start combination immune modulating therapies? Are antivirals effective in patients on high flow oxygen if they still are shedding virus?” says Dr. Aberg. “We are still trying to optimize modalities.”
New treatments for COVID-19, including antiviral drugs such as Paxlovid, are now available to help reduce the likeliness of developing severe disease. But some shortfalls remain.
“For example, Paxlovid has significant drug-to-drug interactions and not everyone can take that,” notes Dr. Aberg. “We’re still learning how to be able to manage those who are immunocompromised and are experiencing persistent viral shedding.”
Some of the monoclonal antibody treatments that had been developed for COVID-19 and had shown efficacy earlier in the pandemic have since become less effective against current circulating variants. “We need to develop tools for rapid sequencing of virus to detect which variant is causing disease while simultaneously having available active antibody therapies. We hope that future anti-SARS-CoV-2 monoclonal antibodies will be effective to treat and prevent COVID-19, especially for those who are immunocompromised,” Dr. Aberg says.
In basic science, many questions about viral pathophysiology remain unanswered, especially with regards to how it affects coagulation, thrombosis, and inflammation, says Dr. Merad. Even with the success of COVID-19 vaccines at reducing infection incidence and severity, people still can still be infected, and it is not clear why that is so, she adds.
What is the current state of COVID-19 research and where is it headed?
Clinicians are looking at whether they can combine different treatment modalities, especially for immunocompromised patients, says Dr. Aberg.
The National Institutes of Health is still conducting its efforts through the networks the agency has formed during the pandemic, and is conducting multicenter clinical trials, Dr. Aberg points out. It has preserved its expedited pipeline for testing novel therapeutics, including the use of “adaptive platform studies,” where new investigative agents could use an adapted template without the need for developing a new protocol from scratch.
Long COVID clinical trials are coming down the pipeline, says Dr. Putrino. A trial to test the use of Paxlovid for treating long COVID has received an Institutional Review Board approval from the Food and Drug Administration, making it one of the first of its kind for a targeted treatment of the condition, he notes.
The discovery of objective biomarkers will also pave the way for new drugs to be developed for long COVID, or for existing treatments to be explored, says Dr. Putrino.
These biomarkers could also be leveraged for uses beyond COVID-19. “The pandemic made us realize how we have few assays to measure our immune fitness to tell us whether someone can be susceptible to disease,” says Dr. Merad. Immune biomarkers could be used to develop assays to measure whether an individual could mount a good immune response, perhaps to vaccination, or just in general. “Can we build novel tools to measure our immune fitness, in the same way we can measure our blood sugar?” she questions.
It is undeniable that clinicians and researchers are committed to COVID-19 research, says Dr. Merad. “That’s what we’re fighting for,” she says. “We’re talking to everyone—industry partners, government entities—on the need for continued effort, and everyone is on board.”
Here are Some COVID-19 Research Milestones at Mount Sinai
2022
- Dec 8: Mount Sinai researchers published one of the first studies about changes in blood gene expression during COVID-19 being linked to long COVID
- Aug 9: Mount Sinai launched CastleVax, a clinical-stage vaccine research and development company, whose capabilities can be leveraged to tackle SARS-CoV-2
- June 28: Mount Sinai-led team showed immune particles derived from the blood of a llama could provide strong protection against every COVID-19 variant
- June 14: Mount Sinai researchers have developed a rapid blood assay that measures the magnitude and duration of someone’s immunity to SARS-CoV-2
- Mar 31: Faculty from the Icahn School of Medicine at Mount Sinai play key roles in the SAVE program, established by the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health (NIH)
- Mar 21: Clinical investigators at the Icahn Mount Sinai launched a Phase 1, open-label, placebo-controlled study to evaluate the safety and immunogenicity of an egg-based COVID-19 vaccine in healthy, vaccinated adults who have never been infected with COVID-19
2021
- Nov 29: Icahn Mount Sinai served as a hub site for two cohort studies as part of nationwide health consortium study by NIH on the long-term effects of SARS-CoV-2
- May 25: Mount Sinai and the Pershing Square Foundation expanded a saliva-based COVID-19 testing program
- April 5: Mount Sinai launched the Mount Sinai COVID-19 PCR Saliva Testing program for businesses and leisure activities in New York
- Jan 27: Mount Sinai researchers demonstrated using a machine learning technique called “federated learning” to examine electronic health records to better predict how COVID-19 patients will progress
- Jan 27: Scientists at University of California, San Francisco, and the Department of Microbiology at Icahn Mount Sinai reported data showing the promise and potential of Aplidin® (plitidepsin), a drug approved by the Australian Regulatory Agency for the treatment of multiple myeloma, against SARS-CoV-2
2020
- Dec 29: Emergent BioSolutions and Mount Sinai initiated a clinical program to evaluate COVID-19 Human Hyperimmune Globulin product candidate in the first of two Phase 1 studies for potential post-exposure prophylaxis in individuals at high risk of exposure to SARS-CoV-2
- Sept 17: The Clinical Laboratories of The Mount Sinai Hospital has received emergency use authorization from the New York State Department of Health for quantitative use of Mount Sinai’s COVID-19 antibody test
- June 17: Mount Sinai submitted a request to the U.S. Food and Drug Administration (FDA) for issuance of an emergency use authorization for quantitative use of its serologic test
- May 14: Mount Sinai established the Institute for Health Equity Research to understand the effects of health issues including COVID-19
- April 15: Mount Sinai Laboratory, Center for Clinical Laboratories received emergency use authorization from the UFDA for an antibody test
- April 3: Mount Sinai developed a new remote monitoring platform to help health care providers care for COVID-19 patients who are recovering at home
- April 1: Scientists, physicians, and engineers at Mount Sinai launched STOP COVID NYC, a web-based app to capture the symptoms and spread of COVID-19 in New York City
