Just as Formula One racing teams rely on advanced technology, strong teamwork and meticulous precision, so does Mayo Clinic’s automation strategy.

Anjali Bhagra, M.D., M.B.A., who leads Mayo Clinic’s automation efforts and became a Formula One racing fan thanks to her youngest son, finds parallels between the two. Both have a shared need for high-performance solutions, which require a robust foundational infrastructure.

"In racing, Ferraris cannot succeed if there is no infrastructure,” she says. "It’s the same with healthcare — we must build the roads, and building those is the hard work. Not only is Mayo Clinic building the roads, but the organization is also bringing the Ferraris.”

Dr. Bhagra’s experience watching competitive athletes has instilled in her an appreciation for the dedication, precision and collaborative spirit required to achieve peak performance.

This same mindset is crucial to Mayo Clinic’s work in automation. Mayo Clinic is creating a blueprint for healthcare’s automated future — one that enhances rather than replaces human care, improving outcomes for both patients and healthcare workers.

The Year of Automation

Dr. Bhagra’s interest in automation stems from a personal and professional journey that spans decades of innovation in healthcare.

Her early work in radiology exposed her to the challenges of interpreting massive volumes of imaging data — an experience that highlighted the need for intelligent tools to support clinical decision-making. She began integrating point-of-care technology at the bedside to better assess patients nearly 20 years ago.

"We have all these capabilities,” she says, “but we don’t have the processes in place to put them in the hands of people taking care of patients.”

That’s when, in mid-2023, Mayo Clinic leaders declared 2024 as the “Year of Automation.” Partners from all over the organization came together to strategize how to bring this vision to life with a focus to transform the future of healthcare delivery. They began by establishing four core outcomes to guide their efforts: enhancing patient care and outcomes; improving staff experience and burden reduction; improving operational efficiency and cost reduction; and empowering innovation and engagement.

As part of this effort, leaders identified key areas as testing grounds for pilots, scalable initiatives and transformative innovations.

One initiative is the Virtual Nursing (ViRN) program, an inpatient model for virtual nursing that uses automation to improve various aspects of patient care, including admissions, bedside care and discharge. ViRN resources were integrated into daily operations, drastically reducing manual data entry and alleviating multitasking demands that previously contributed to nurse burnout and turnover.

This initiative improved staff efficiency and morale, enhanced patient safety and care quality, and eased the burden on nurses.

“It’s about letting our staff focus on what matters most — caring for our patients,” Dr. Bhagra says.

Among the more than 100 initiatives that have been implemented across the organization in the past year, Dr. Bhagra is most proud of a project to enhance access for international patients, a group that often faces significant barriers to care.

The intake process for international patients was slow due to its complexity and the diversity of patient backgrounds, languages and medical documentation formats. To address this, Mayo Clinic assembled a multidisciplinary team whose goal was to streamline intake, triage and care coordination using automation and process mining, a data analysis technique used to optimize business processes.

The team focused not only on bringing patients in faster, but also on ensuring they move through the right areas of Mayo Clinic at the right pace to receive the most appropriate care. This includes automating decision trees, language translation and routing mechanisms to reduce delays and improve the patient experience.

“These tools are really bringing that intelligence that humans need to be able to take care of patients better, and that fundamentally is my driver,” says Dr. Bhagra.

Restoring Human Touch

One might think of automation as factory lines or robots replacing humans. But healthcare automation today is far more nuanced — it’s less about replacement and more about augmenting human capabilities, handling repetitive tasks, and freeing people to focus on creative problem-solving and strategic work. In healthcare, it becomes more about the patient.

Healthcare tasks are highly amenable to automation, and thoughtful implementation of automation and AI can significantly enhance human connection with patients.

“I think there is an automation paradox,” Dr. Bhagra says. “Automation and AI — when done right — will bring humanity back in the healthcare experience.”

Many healthcare professionals spend excessive time on administrative tasks such as data entry, ordering and recordkeeping, diverting their attention from patient interaction. Mayo Clinic clinicians have adopted AI-powered ambient listening technology that automatically captures and summarizes patient discussions, freeing them from note-taking tasks that previously disrupted personal interactions.

“If I have automation and AI working in the background, I can offer my real empathy and compassion,” Dr. Bhagra says. “I don’t have to have my mind in two places at the same time — one with the machine and one with my patients.”

By strategically integrating automation, Mayo Clinic is creating a more efficient and compassionate healthcare system, ensuring the human touch remains central to patient care.

The Future of Automation

While the future of automation is bright, Dr. Bhagra, who also leads Mayo Clinic’s Office of Belonging, stresses the importance of fairness, ethics and accountability in developing and deploying automation strategies.

Mayo Clinic’s culture of belonging and innovation distinguishes it from profit-driven organizations. This ethos underpins the commitment to creating safe, effective and equitable healthcare.

It’s a perspective appreciated by her administrative partner, Biju Samkutty, who is chief operating officer of Mayo Clinic’s enterprise automation efforts.

“Dr. Bhagra’s commitment to advancing what’s best for patients is truly inspiring,” Biju says. “She brings both strategic vision and a relentless drive to ensure that innovation translates into real-world impact.”

And with Dr. Bhagra in the driver’s seat, so to speak, Mayo Clinic’s efforts to use automation to drive more humanity into healthcare are well on their way.

“To reach the championship podium, integrating automation takes all of us at Mayo Clinic working together to meet the needs of the patient,” she says. “We’re on the right track.”

The post The Power and Precision of Automation appeared first on Mayo Clinic Magazine.

Discover three ways Platform is translating vision into action — and data into solutions.

‘Virtual Clinical Trials’ Point to New Treatment Options for Heart Failure

Bringing a new drug therapy to market can cost up to $1 billion and take over a decade. As drug testing and approvals slowly unfold, many patients continue to suffer. But what if there was a way to test the ability of existing drugs to treat challenging conditions?

Using data drawn from Mayo Clinic Platform — specifically, the de-identified records of nearly 60,000 patients with heart failure — Nansu Zong, Ph.D., and his team were able to virtually assess the ability of certain already-approved drugs to treat heart failure. Instead of recruiting participants, the team drew on patient records to form control groups. They then used advanced artificial intelligence (AI) models that predict how drugs interact with biological systems to determine outcomes. This approach allowed researchers to rapidly test over a dozen medications already on the market without requiring the lengthy, difficult process of conducting a full clinical trial for each one.

“We’ve shown that within our framework, we can say with high confidence if a drug is likely to succeed or not,” Dr. Zong says. The results of the study have been published in NPJ Digital Medicine.

Mayo Clinic teams are now working to refine this new virtual approach to drug testing. While real-world clinical trials will always be essential, virtual options could help to expand and supplement their findings.

To learn more, visit Mayo Clinic News Network.

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15 Startups Use Platform Data to Shape Solutions

Mayo Clinic Platform regularly accepts promising tech startups into its incubator program, Mayo Clinic Platform_Accelerate. Participants gain access to Platform data — and the insights of Mayo Clinic experts — as they refine their devices, apps, algorithms and other products. The companies below all “graduated” in the April 2025 Accelerate cohort:

• Bloom Standard has developed a device that can be used to provide quick and effective heart and lung ultrasounds for children.
• Ethos uses AI to monitor alcohol use and predict risk of liver disease and other complications.
• OPTT is a digital mental health platform that provides clinicians with validated tools for evaluating and treating patients more effectively.
• Smart Opinion, Inc. uses AI to detect breast cancer earlier, particularly in women with dense breast tissue.
• Splink, Inc. is harnessing the power of AI to deliver earlier diagnoses for brain disorders like dementia, depression and schizophrenia.
• Voythos uses machine learning to help surgeons predict when patients with complex aortic disease may experience complications, allowing for earlier and more effective interventions.

Mayo Clinic Platform_Accelerate aims to speed up the development of innovative healthcare solutions that can improve patient care and transform medicine.

To learn more about these startups and other Accelerate graduates, visit Mayo Clinic News Network.

PlatforMed Conference Generates Patient-Focused Insights

In June 2025, Mayo Clinic hosted more than 250 leaders from healthcare, government, business and academia at the PlatforMed conference in Minneapolis. The goal: To discuss how sharing data and collaborating through platform technologies produces better care for patients. Speaker highlights included:

• John D. Halamka, M.D., M.S., Dwight and Dian Diercks President of Mayo Clinic Platform, who described how platform-based advances will help aging patients consistently access quality care. The automation and accessibility that platform tools deliver will ensure these patients aren’t overlooked in a future where healthcare resources may be more limited.
• Maneesh Goyal, chief operating officer of Mayo Clinic Platform, who discussed how Mayo Clinic Platform is enabling an average of 60 patients a day to receive hospital-quality care at home through the Advanced Care at Home program. He likened this Platform-powered development to a new “virtual floor” connected to existing Mayo Clinic hospitals.
• Patrick Woodard, M.D., M.H.A., of Monument Health, who explained how platform technologies are helping democratize access to care. As chief information officer of a hospital in rural South Dakota, he can use shared data and tools to ensure his patients have access to the same standard of care as patients in major urban centers.
• Deepak Abraham, Ph.D., M.B.A., of King Hamad American Mission Hospital in Bahrain, who discussed how platform technologies are helping providers save time on tasks like data entry, allowing them to spend more time interacting directly with patients. “The doctor-patient relationship is sacrosanct,” he emphasized. “Platform enhances that.”

To hear more from these and other speakers, watch the episode of Tomorrow’s Cure below, which was recorded at the conference.

The post 3 Ways Mayo Clinic Platform Impacts Patient Care appeared first on Mayo Clinic Magazine.

Persistence Pays Off

Gelareh Zadeh, M.D., Ph.D.’s medical career almost ended before it even began. That’s because she went home for lunch during the two-part Medical College Admissions Test (MCAT) convinced there was no need to return for the second half of the six-hour-plus exam.

“I told my mom I probably failed. There’s no point in going back,” recalls Dr. Zadeh, the chair of Mayo Clinic’s Department of Neurosurgery in Rochester. “The exam was a lot of new material to me because I had been studying mathematics in college to become an actuary — I had not studied biology or related courses.

“And my mom said, ‘We paid a lot of money for you to try. You should go back for the writing portion.’ Somehow, she convinced me.”

The lesson in persistence proved prescient. Dr. Zadeh, who was recently named the David C. and Flora C. Pratt Distinguished Chief Medical Officer for Mayo Clinic Platform, not only scored well on the MCAT, but also her efforts set the stage for a career in research science and medicine as a world-renowned neurosurgeon.

SHARED PERSPECTIVES

Persistence was key throughout Dr. Zadeh’s childhood. Her family immigrated to Canada from Iran. Her father, an economist, and her mother, a nuclear chemist, settled in Manitoba.

“I watched my mom study really hard,” Dr. Zadeh says. “My parents inspired me to commit myself to whatever I do. I feel most rewarded — whether a project is successful or not — when we complete it together as a team.”

The varying perspectives of her life also gave her an advantage practicing medicine — her ability to understand others and translate it to servant leadership.

“Having lived through revolution, through war, immigration, I’m able to recognize that we each have a very unique perspective,” Dr. Zadeh says. “By nature, we’re all very distinct, and it’s the way we were designed to be. For me it is important to understand each person’s strengths and experiences.”

Dr. Zadeh treats patients with skull base tumors and brain cancers, leading multidisciplinary teams in specialized programs for brain metastases, pituitary disorders and neurofibromatosis. In her research laboratory, she analyzes the molecular signatures of brain tumors, using computational modeling to predict treatment outcomes and identify new therapeutic targets for difficult-to-treat brain cancers.

JOINING MAYO CLINIC

Mayo Clinic’s Department of Neurosurgery stands as one of the world’s most prestigious neurosurgical programs because of its exceptional patient outcomes, groundbreaking research and innovative surgical techniques that have defined excellence in the field for over a century.

The institution performs thousands of complex neurosurgical procedures annually while maintaining complication rates well below national benchmarks, demonstrating how high volume can coexist with superior quality. This achievement reflects Mayo Clinic’s century-long commitment to subspecialty expertise, multidisciplinary collaboration and continuous innovation.

“Mayo Clinic’s brand has been recognized internationally as top ranked, and having the responsibility of being highly regarded helps motivate us to make the next discoveries that improve outcomes, care and experiences for our patients,” Dr. Zadeh says.

“We have an approach that ensures healthcare is delivered safely and at its highest quality, so when the institution recognizes the value of a new direction and implements a new method in medicine, it gains international recognition.”

Mayo Clinic’s investments in artificial intelligence, Mayo Clinic Platform and other strategic priorities swayed Dr. Zadeh to join the staff in 2024 where she is recognized as a William J. and Charles H. Mayo Professor.

“What we have at Mayo Clinic is a vision for the future. We’re trying to be balanced and realistic — but we’re actively thinking about what is possible for our patients and pursuing solutions,” she says. “I arrived at a time where access to Mayo Clinic Platform was now possible by clinicians, and in a few months, we’ve been able to interrogate the data that’s available, which is an unparalleled resource to ask some key clinical questions.

“This year, we had our first clinical trial born out of Platform, which is a huge success and an exciting step forward.”

FORWARD FOCUS

From that fateful lunch hour, Dr. Zadeh ultimately embarked on a career that has advanced brain tumor research and broken barriers, and she now holds a position leading Mayo Clinic to the forefront of neuroscience innovation.

Her persistence has driven her to unparalleled heights as a servant leader and has earned her numerous awards, such as the Canada Gairdner Momentum Award, William E. Rawls Prize from the Canadian Cancer Society, and American Brain Tumor Translational Research Award.

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Dr. Zadeh also holds leadership roles in international organizations, including the Society of Neuro-Oncology, World Federation of Neurological Societies, and International Consortium on Meningiomas, which she co-founded.

“I always tell people I think a negative outcome is just as important, if not more important, than a positive, because the positive is no mystery. We had a hypothesis, and we proved it,” she says. “In the lab the unexpected negative result is what sparks the next questions and drives further investigations.”

Sometimes the most important discoveries come not from success, but from the persistence to continue when everything seems to be going wrong. As Dr. Zadeh learned from watching her parents, the difference between failure and the next breakthrough can be as simple as asking the next question.

The post Persistence Pays Off appeared first on Mayo Clinic Magazine.

Mayo Clinic Using AI to Pinpoint Migraine Treatments

Treating migraine has long been an exercise in uncertainty.

The unpredictability of therapeutic responses frustrates both doctors and their patients suffering from migraine and other forms of recurring headache. While tension-type headaches occur more frequently in the population, migraine are the most common disabling form.

But Mayo Clinic scientists are using new technologies to demystify migraine treatment — advancing toward a future where personalized medicine delivers hope and healing to patients who have been disappointed in their search for relief.

“When treating migraine, about 30% to 50% of people who try a specific treatment will actually have a tangible benefit,” says headache specialist Todd Schwedt, M.D., who is chair of the Headache Division in the Department of Neurology at Mayo Clinic in Arizona. “We’ve been working for years on ways to identify which treatment is the best one for an individual patient, so that the best treatment is the first one prescribed.”

Chia-Chun Chiang, M.D., a Mayo Clinic headache specialist in Minnesota, centers her clinical and research focus on the application of artificial intelligence (AI) and machine learning to the study of migraine and vascular neurology.

Dr. Chiang, a Gerstner scholar, was the lead author of a 2024 study developing machine learning models to predict treatment responses to commonly used migraine preventive medications. For this work, she was the winner of the annual Harold G. Wolff Lecture Award from the American Headache Society, given for the best scientific paper on headache, head or face pain, or the nature of pain itself.

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Neurologist Michael Cutrer, M.D., who was the longtime head of the Headache Division at Mayo Clinic in Minnesota, was the paper’s senior author. Dr. Cutrer has treated patients with complex headache syndromes for more than 25 years and is the creator of the Mayo Clinic Headache Subspecialty Clinic Database, a key foundation for Mayo Clinic’s research.

He says one of the biggest obstacles that has hampered the effective treatment of migraine has been a limited understanding of its underlying mechanisms.

"This challenge has resulted in a trial-and-error approach that can take months or years for each patient before finding a treatment that works for them,” Dr. Cutrer says.

Researchers demonstrated that migraine characteristics — such as headache intensity, location and frequency — are important in predicting treatment responses to individual classes of preventive medications. These results suggested that precision migraine treatment is feasible.

"We're developing self-learning algorithms that incorporate patients’ treatment outcomes,” Dr. Cutrer explains. "This continuous refinement will help us provide increasingly precise treatment recommendations."

The study led by Dr. Chiang analyzed data from the Mayo Clinic Headache Subspecialty Clinic Database prospectively collected from 2001 to 2023. The database includes detailed clinical characteristics and headache symptoms from about 17,000 patients who have completed in-depth questionnaires, which asked patients to describe their headaches, associated symptoms, family history of headache, migraine triggers and medications they’ve tried.

We have additional work to do, but we are close to having clinically useful predictive models that increase the chance that the first migraine medication a patient takes is the one that works.

— Todd Schwedt, M.D.

During follow-up visits, patients are asked about the change in their headache frequency. Their treatment responses provide valuable additional data and allow Mayo Clinic researchers to further use AI to personalize care as they develop algorithms that use natural language processing.

Headache researchers have historically needed to review patient records to obtain information from patients’ verbal responses to provider questions. This manual process significantly slows down the acquisition of potentially valuable data.

“We developed a model that can analyze language to extract headache frequency — a key parameter for measuring treatment response — directly from medical records," Dr. Chiang says.

In addition to the 17,000 patients in the Mayo Clinic Headache Subspecialty Database, Dr. Schwedt led the effort in constructing a Mayo Clinic Migraine Dataset that includes data from 200,000 patients with migraine who have been seen in Mayo Clinic Health System, which will further enrich the ongoing effort from the team using AI to tackle this unmet need.

The results of this study are beginning to take some of the guesswork out of therapeutic responses.

“Based on this work, we can identify some clinical features that predict treatment response,” Dr. Chiang says. “Headache-associated symptoms, things that trigger headaches, these are predictive of treatment response to many different migraine preventive medications.”

Researchers are also studying genetic biomarkers related to headache. Their analysis includes comprehensive biological data such as proteins within cells (proteomics) and small molecules involved in metabolism (metabolomics).

Mayo Clinic has one of the world’s leading research and clinical programs in headache medicine. Other Mayo Clinic contributors included scientists from the departments of Neurology, Cardiology and Radiology — spanning Mayo Clinic’s locations in Minnesota and Arizona.

“We’re leading the effort to use AI modeling to predict migraine treatment responses,” says Dr. Schwedt, who is the current president of the American Headache Society. “We have additional work to do, but we are close to having clinically useful predictive models that increase the chance that the first migraine medication a patient takes is the one that works.”

The post Mayo Clinic Using AI to Pinpoint Migraine Treatments appeared first on Mayo Clinic Magazine.

Dr. Staff and his colleagues have created the first artificial intelligence (AI) tool that can analyze routine nerve tests, called electromyography (EMG), to spot ALS sooner and predict how the disease may progress — potentially helping patients get access to treatments and clinical trials earlier.

Dr. Staff sat down with Mayo Clinic Magazine to share how AI is opening new doors for ALS research and care. This interview has been edited for clarity and length.

What is the inspiration for your work?

As a clinician who diagnoses and manages patients living with ALS long-term and participates in clinical trials, I saw firsthand the challenges and delays in diagnosis. That experience made me realize how impactful AI could be — not just for diagnostics, but also for improving clinical trial design and patient care.

I saw firsthand the challenges and delays in diagnosis. That experience made me realize how impactful AI could be — not just for diagnostics, but also for improving clinical trial design and patient care.

— Nathan Staff, M.D., Ph.D.

My colleagues and I were also intrigued with the question: What parts of our EMG data could help us advance diagnostics and prognostics? We see a high volume of patients seeking second opinions, so we knew we had a rich dataset to work with.

Ultimately, our inspiration came from a mix of clinical need, technological opportunity and a desire to bring something truly useful into practice. We wanted to build a tool that could help clinicians make earlier, more confident diagnoses and improve outcomes for patients living with ALS.

What are some key findings that have emerged from your research so far?

When we started this project, we had one big goal: to help doctors diagnose ALS earlier and more accurately using AI. ALS is a tough disease. It’s hard to diagnose, and there’s no cure yet. But we believed that by using the data we already collect — like EMG tests that measure how muscles respond — we could train a computer to spot patterns that even experienced doctors might miss.

This tool, built on EMG waveform data and trained using machine learning, is designed to help clinicians identify ALS earlier and more confidently. What’s amazing is how well it worked, even in early tests. We published the research in Brain in 2025.

How does your research integrate AI?

Our AI algorithm analyzes EMG data using machine learning to identify subtle patterns that aren’t visible to the human eye. It’s like a supercharged calculator that compares muscle response data from patients with confirmed ALS to those without, extracting features that help us assess the likelihood of ALS. The results were surprisingly strong — our model performed with a high degree of accuracy, which was both exciting and validating.

While the tool is still in the research phase, we’re designing feasibility trials to integrate it into clinical workflows. Ultimately, this could mean earlier access to trials, better symptom management, and peace of mind for patients and their families.

Why is this research important?

ALS is a devastating disease, and one of the most frustrating aspects for both patients and clinicians is the delay in diagnosis. Symptoms can be vague at first — just weakness — and that often leads to misdiagnosis or long waits for clarity. That delay can mean missed opportunities for clinical trials, delayed symptom management, and prolonged anxiety for patients and their families.

This tool is designed to help clinicians identify ALS earlier and more confidently. Our vision isn’t to replace clinicians but to equip them with another tool — one that nudges the diagnostic needle in the right direction, especially in ambiguous cases. This tool has the potential not only to confirm ALS sooner but also to rule it out in cases where the diagnosis is uncertain. That kind of reassurance can be just as powerful.

What excites me most is that this isn’t just a research project. It’s something that could truly change lives, and it’s just the beginning. With continued support, we can keep building tools like this to help patients and families facing some of the hardest diagnoses.

Without philanthropic support, we wouldn’t have had the resources to even begin this work. Benefactors’ generous philanthropy empowered us to think differently. It gave us the space to collaborate across disciplines, to test ideas that might have seemed too ambitious otherwise, and to move quickly from concept to clinical feasibility, ultimately enhancing quality of life for patients and their families.

Dr. Staff is a recipient of the Tianqiao and Chrissy Chen Established-Investigator Development Award in Translational Research. The Chen Institute’s generous support accelerates projects that leverage AI and translate it into applications for patient care.

The post Turning Data Into Diagnosis appeared first on Mayo Clinic Magazine.

It wasn't a typical medical question or appointment request. Instead, a patient with alcohol-related liver disease was reaching out in a moment of crisis, seeking help with his addiction to alcohol.

For Vijay Shah, M.D., the Mr. and Mrs. Ronald F. Kinney Executive Dean of Research, that message crystallized everything wrong with current approaches to healthcare and everything that needed to change.

“That patient reached out for support when and where he needed it most, but our current technologies couldn't provide that support,” says Dr. Shah, who is also recognized as the Carol M. Gatton Professor of Digestive Diseases Research, Honoring Peter Carryer, M.D. 

In that moment, the patient didn’t need a prescription or a blood panel. They needed a medical team who saw them as more than a name and a set of numbers on a chart. They needed care that was designed just for them and their specific struggles and needs, including the challenge of managing alcohol cravings.

The experience led Dr. Shah to reflect on the current state of medical care, and particularly the way it prevents patients from receiving the care they need.

“That patient message drove me to ask key questions: How do we serve patients better?” he says. “Imagine if that patient had a wearable device that sent an alert to his care team when he had a craving, so someone could reach out proactively and ensure that he had the support that he needed right in that moment. How do we create those sorts of technologies, to help people before they reach a crisis point?”

To answer these questions, Dr. Shah and his team have created a vision for research at Mayo Clinic that will drive the transformation of medicine from a reactive, one-size-fits-all pipeline to a platform where healthcare is a proactive, personalized journey throughout life.

The Challenge in Healthcare Today

While medical institutions like Mayo Clinic excel at providing expert care, the broader healthcare system still operates largely in reactive mode. Patients develop symptoms, seek care and receive treatments based on population-level guidelines rather than their individual biology and circumstances.

Even when care is accessible in a timely manner, the fundamental approach remains the same: respond to disease after it manifests rather than prevent it from occurring. This model, while effective for many conditions, falls short for patients facing serious or complex diseases that might be intercepted or prevented entirely with the right tools and insights.

The solution required rethinking everything. As leader of Mayo Clinic's research enterprise, Dr. Shah developed a vision that transforms healthcare from reactive treatment to predictive prevention, aligning the institution’s discovery and translational science efforts with Mayo Clinic’s Bold. Forward. transformation of healthcare to accelerate access to new treatments and cures for patients everywhere.

“At Mayo Clinic, our research and practice are intertwined,” he says. “Everything we do must serve our primary value of putting the needs of the patient first, so that's where we focused our vision for research. We are addressing the fundamental challenge that our current system doesn’t have the cures our patients need for most serious or complex diseases.”

His perspectives have been shaped by his career working on liver disease.

“I’ve been interested in liver disease my whole life,” Dr. Shah says. “The liver is an organ of serious and complex diseases — such as cirrhosis. It’s a very complicated organ, and ripe with data, which is critical to our approach. Alcoholic liver disease holds such power over people’s lives, and our current medical technologies and approaches are not what patients need.”

Open image in lightbox

Open image in lightbox

Heidi Dieter, chair of Research Administration, works alongside Dr. Shah, serving as his administrative partner and overseeing many of the primary business functions of the Research shield.

“What excites me most about this vision is how it fundamentally changes our relationship with patients," says Heidi. "We're not just treating disease anymore. We're partnering with people throughout their entire life journey, using data and technology to help them remain healthy and prevent illness before it starts.”

And with 25 years of experience as a clinician and researcher, Dr. Shah brings a wealth of expertise using leading-edge digital tools, including artificial intelligence (AI), to bridge discovery science to clinical trials and beyond.

The most dramatic example of this patient-first transformation is already taking shape in how Mayo Clinic conducts clinical trials.

Revolutionizing Clinical Trials

One of the most transformative aspects of this vision involves completely reimagining clinical trials. Traditional trials face a fundamental ethical dilemma: half of participants receive an inactive treatment known as a placebo. This provides a baseline against which the effectiveness of the actual treatment is measured.

“No one participating in a trial wants to be in the placebo group, but we need to collect this data to have the most rigorous study design and truly understand treatment efficacy,” says Dr. Shah. “But what if we could change that?”

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Through AI tools and the power of Mayo Clinic Platform, a vast repository containing millions of patient records from Mayo Clinic and beyond, clinical trial teams can now conduct analyses on data from other patients with the same condition to determine the natural course of the disease without any treatment. These AI-powered control groups are called synthetic placebo arms.

“With AI and our data intelligence, we're starting to reach the point where we can collect real-world data, make synthetic placebo arms, and thereby allow our clinical trials to focus on the active intervention for all of the human patients,” says Dr. Shah. “We're not fully there yet, but we're well on our way.”

This tactic will also include the use of “digital twins” — AI-powered replicas built from individual patient data that can simulate hundreds of different treatments to determine which options might work best for any given patient. This means that clinicians will be able to match patients to the trials that are most likely to succeed for them, while simultaneously identifying which patients will benefit the most from a new treatment or trial.

As these technologies expand, there will also be opportunities to improve access to treatments by developing scalable approaches for decentralized clinical trials, bringing these opportunities into patients' own homes and communities. In short, patients anywhere around the world will be able to access Mayo Clinic-level care, where and when they need it.

“These clinical trials of the future are more patient-centric, they go faster, and they're less expensive,” Dr. Shah says. “With these advances, I believe we can reduce the time it takes to go from discovery to clinical treatment by tenfold — from 17 years down to 17 months.”

This acceleration sits within a broader framework built on three interconnected strategies that work together to deliver cures faster.  

Through the seamless integration of pioneering science discoveries, AI-powered data intelligence, and revolutionary clinical impact approaches, Mayo Clinic is creating a self-reinforcing cycle that not only accelerates the path from laboratory bench to patient bedside but also fundamentally transforms healthcare from a reactive system into a globally accessible platform for preventing and curing serious or complex diseases.

Driving Toward Cures

While these approaches represent the long-term vision for 2045, the foundation is being built today.

The Research shield has already launched two key initiatives — Precure and Genesis. Precure is aimed at intervening before patients get sick, connecting patients to critical insights that can intercept serious diseases before they manifest. Genesis’ goal is cures — using cell therapy technologies and AI-driven solutions to predict organ failure, restore organ function and eliminate the need for transplant.

As part of this effort, research teams are advancing bioengineering and manufacturing efforts, in partnership with industry experts, to design and test new therapies. Scientists are also working on advancing biosensing technology, and new trials are being launched for early detection and treatment across organ systems.

Through it all, the team is building the infrastructure and relationships necessary to make this vision a reality with strategic funding and industry partnerships to turn promising developments into new treatments and cures.

“If a researcher wants to explore a disease under Genesis, we have all the infrastructure set,” says Dr. Shah. “If a company wants to work with us to explore a new biomanufacturing approach to developing cell therapies, we can do that. It’s a scalable process.”

For Dr. Shah and his team, this isn't just about advancing medicine. It's about fundamentally changing what's possible for every patient who walks through Mayo Clinic's doors.

Detecting Cancer Risk Decades Earlier

The work of hematologist Mrinal Patnaik, M.B.B.S., with clonal hematopoiesis of indeterminate potential (CHIP) exemplifies Mayo Clinic's Precure initiative in action, shifting from reactive treatment to proactive prevention.

As we age, the DNA in our blood cells mutates due to environmental exposures like radiation, chemicals and stress. While most damaged cells are eliminated, some survive and multiply. When numbers of these mutated clones grow large enough to detect, they're classified as CHIP. This precancer stage causes inflammation and over time, significantly increases risk of blood cancers and the risk of dying from all causes, especially cardiovascular disease.

Using advanced DNA sequencing, Dr. Patnaik's team in the Center for Individualized Medicine and Division of Hematology detects CHIP mutations from a simple blood draw. AI-driven software analyzes the data and translates it into actionable insights.

“We're creating tools that can identify precancer decades before it would traditionally be diagnosed,” says Dr. Patnaik. “This gives us a crucial window to intervene.”

Since 2016, Mayo Clinic has monitored over 1,000 patients with CHIP. Under Precure, the goal is accelerating the work and scaling to 100,000 patients. His research examines why people develop CHIP, including hereditary and environmental factors, and understanding which interception strategies have the greatest impact.

CHIP research demonstrates Precure's approach: early detection followed by interception. For patients, this means knowing cancer risk decades in advance and having concrete steps to reduce it, representing a fundamental shift from treating disease to preventing it entirely.

A Legacy Worth Building

These efforts represent more than just a vision for research at Mayo Clinic. They’re part of the Bold. Forward. blueprint for a research-driven, transformed global healthcare system.

“When I think about the legacy we're building, I imagine a world where no patient has to endure what that patient with alcohol liver disease wrote to me about in his portal message, struggling alone when he needed help the most,” says Dr. Shah. “We're creating a future where serious or complex diseases don't define the end of someone's story but become preventable chapters we can rewrite.”

By 2045, Mayo Clinic envisions a new approach to medical care where serious or complex diseases are identified and intercepted before they manifest, and where interventions are tailored to each patient’s unique profile and needs.

“This research vision isn't just about Mayo Clinic becoming the global authority in healthcare innovation,” says Dr. Shah. “It's about ensuring that every person, everywhere, has access to the tools and insights they need to thrive. That's a legacy worth dedicating our lives to building.”

The post N of 1 appeared first on Mayo Clinic Magazine.

In Minnesota, Bold. Forward. Unbound. in Rochester represents a $5 billion investment over six years. It embodies Mayo Clinic's most significant and forward-looking vision for the future of healthcare by integrating our physical and digital infrastructure and blending inpatient and outpatient care. By 2030, Mayo Clinic will transform the Rochester campus and establish a new model for continuous, digitally integrated, patient-centered care.

Craig Daniels, M.D., critical care physician and medical director for Bold. Forward. Unbound. in Rochester, sat down with Mayo Clinic Magazine’s editorial team to provide an inside look at what fuels Mayo Clinic’s vision and motivates him to help lead this transformation. This interview has been edited for clarity.

How will these spaces be radically different from today’s healthcare environment?

We recognize that patients today experience outpatient, inpatient and virtual care — all delivered in different environments — which can feel quite bumpy. With Bold. Forward. Unbound. in Rochester, we are striving to create an environment where care is seamless for patients.

As we began designing the future of care as a single, integrated experience, we realized that traditional outpatient, inpatient and digital spaces would not work. Our spaces must be flexible to meet patients’ needs wherever they are in their Mayo Clinic healthcare journey.

That means designing buildings that do more than house care — they actively support and enhance it. For example, we are creating care "neighborhoods" where diagnostics, imaging, consultations and procedures occur in one continuous environment, reducing the need for patients to move from place to place.

We're also incorporating healing design principles in every element — spaces filled with natural light, expansive winter gardens, and areas of rest and reflection for both patients and their loved ones. We're integrating technology not as a layer on top, but as an embedded member of the care team: ambient intelligence, robotics, predictive analytics and automation will allow our teams to focus more on the human aspects of caregiving.

At Mayo Clinic, we’ve always understood that the physical environment can shape medical outcomes. Just as Dr. Henry Plummer’s vision for the Plummer Building transformed medicine a century ago, this next generation of care environments will transform how we deliver hope and healing — not just for today, but for the next hundred years.

To fully live our primary value — the needs of the patient come first — we must design our spaces with patients at the center.

— Craig Daniels, M.D.

Why is now the right time for this investment?

Healthcare is at the precipice of transformation. As stewards of Mayo Clinic — the world’s leader in healthcare — we must lead this transformation and make Mayo Clinic and all healthcare better for patients and staff.

We have the tools, the technology and an incredibly talented staff who dedicate their lives to improving patient outcomes and experiences. This allows us to solve increasingly complex problems and deliver more cures. Combined with physical spaces in a new healthcare design centering on patients’ needs, we will elevate our collaborative care model to provide even more hope and healing in the world.

This is the moment when digital technology, artificial intelligence, robotics and human-centered design are converging — and Mayo Clinic is uniquely positioned to bring them together to transform how care is delivered.

Bold. Forward. Unbound. is not just an investment in buildings — it’s an investment in people, in tools that reduce burdens on staff, and in care environments that foster teamwork, innovation and healing. These spaces are designed to be flexible and intelligent, evolving with patient needs and medical advancements over the next century.

We cannot stand still. We have clarity of purpose, a shared vision and the momentum to act. Now is the time.

Tell us more about the “neighborhoods.” What is innovative about this concept?

To fully live our primary value — the needs of the patient come first — we must design our spaces with patients at the center. This means centralizing care teams and services around patients' unique needs. Neighborhoods at Mayo Clinic are innovative care environments designed to transform how healthcare is delivered and to elevate the experience of both patients and staff.

Historically, healthcare buildings have been built around departments and specific services. Think about the fact that almost all radiology equipment is located on the bottom floor of a hospital. This means that patients often need to travel significant distances between appointments for their imaging. This is also largely true for laboratory and specialty care.

By creating care neighborhoods, we'll reduce the distance patients need to travel for appointments and more closely situate things they most often will need. We believe they will experience better care, better outcomes and greater comfort throughout their entire time at Mayo Clinic.

These neighborhoods allow our teams to work side by side, surrounded by familiar spaces and supported by curated digital tools — breaking down the boundaries that have historically separated departments and stages of care. This will foster greater team-based collaboration, continuous innovation, and integration of clinical practice, research and education.

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What motivates you most about this work?

The Mayo-Franciscan “RICH TIES” values — Respect, Integrity, Compassion, Healing, Teamwork, Innovation, Excellence and Stewardship — perfectly align with our primary value of putting patients’ needs first. I am driven to live out our values through the transformational work of Bold. Forward. Unbound.

Even at an incredible place like Mayo Clinic, opportunities like this don’t come along very often, and so I am excited for my colleagues and me to directly contribute to building and experiencing these new spaces that will provide even better care to our patients and care teams.

It’s a generational moment to reimagine how we deliver care, to remove barriers for our staff, and to shape a future where patients receive more seamless, compassionate and innovative care than ever before. We’re building something that will carry forward the mission of Mayo Clinic — not just for today’s patients, but for those we haven’t met yet, and for future staff members who will carry this work forward long after we’re gone. That sense of responsibility — of stewardship — is what drives me.

The post Building Tomorrow’s Healthcare With Craig Daniels, M.D. appeared first on Mayo Clinic Magazine.

Dr. Ali sat down with Mayo Clinic Magazine to share the personal experience that inspired her work, key insights from her research, and her vision for using technology to protect the aging population. This interview has been edited for clarity and length.

What initially sparked your interest in this area of research?

My interest in fall mechanisms and prediction in aging individuals dates to a personal event. My mom, who is otherwise healthy, had a fall in her 60s. The fall resulted in fractures, which affected her confidence in balancing and many daily activities. I saw firsthand that one fall can be life-changing. This situation really motivated me as it hit close to home.

As a movement disorders provider, I am passionate about gait and balance because it affects every single human being as we get older and all my patients who suffer from neurological disorders. Over the age of 65, 1 in 4 people experience a fall annually. While gait and balance changes may be thought of as part of aging, they can be an early indicator of neurodegenerative disease and give us an opportunity to intervene and prevent falls before they occur.

My research is trying to answer some important questions: Can we predict falls before they happen? Can we predict what causes them? How can we prevent them?

— Farwa Ali, M.B.B.S.

Currently, our ability to predict falls before they occur is limited, and there are few treatments for gait and balance disorders. As a result, falls have a very significant healthcare impact. My research is trying to answer some important questions such as: Can we predict falls before they happen? Can we predict what causes them? How can we prevent them?

What are some key findings that have emerged from your research so far?

I have been able to partner with the Mayo Clinic Study of Aging to analyze several thousand gait samples, and we are working to gain a better understanding of how a patient’s clinical history and gait performance predict future falls.

We were pleased to publish some of these initial results in Nature Communications in early 2025. We found that individuals with worse gait performance had higher levels of Alzheimer's disease biomarkers, indicating that changes in gait can be an early sign of brain pathology, even before cognitive symptoms appear.

How does your research integrate AI?

We’re actively working to use AI and data science to predict incident falls in the aging population. In partnership with the Mayo Clinic Study of Aging, we are using large datasets to discover clues in a patient’s gait phenotype that can predict future risk of a fall before it actually occurs. We are also evaluating how this relates to early neurodegenerative diseases.

Why is your research important?

Falls are very common among older adults. The healthcare economic burden and individual and societal impact of falls are high and are projected to increase as the aging population grows. Older adults also have a higher burden of neurological diseases, such as stroke and Parkinson’s, that can cause disability due to both cognitive and motor issues. Identifying individuals at risk of falls from aging and neurodegeneration can allow early diagnosis and implementation of preventive strategies. Our goal is to develop a tool to predict falls before they happen so we can identify people who are at highest risk and institute appropriate preventive measures.

With generous support from benefactors, I have been able to advance my research by supporting a multidisciplinary team and work toward the aims of the project. I'm incredibly grateful for their investment in science and the betterment of humanity.

Dr. Ali is a recipient of the Tianqiao and Chrissy Chen Early-Career Development Award in Translational Research. The Chen Institute’s generous support accelerates projects that leverage AI and translate it into applications for patient care.

The post Predicting Falls With Precision appeared first on Mayo Clinic Magazine.

Biology in Three Dimensions

After doing his medical training in his native country of Hungary, Dr. Ordog studied neuroendocrine biology, touching on topics like electrical signals in the hypothalamus regulating the menstrual cycle. He started as a junior faculty member at the University of Nevada, Reno, before coming to Mayo Clinic in 2006. In 2012, he helped found the Epigenomics Program at the Mayo Clinic Center for Individualized Medicine. In 2020, he moved to work with the Center for Cell Signaling in Gastroenterology.

Now he and Jeong-Heon Lee, Ph.D., are hard at work creating a first-of-its-kind research enterprise: a core dedicated entirely to spatial biology.

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“‘Spatial’ is a little bit of a misleading term,” says Dr. Ordog, “because currently almost everything we do is in two dimensions [like flat X-rays of body parts], but there is no theoretical limit to why anything we discover doesn’t apply in 3D.”

Spatial biology is essentially what it sounds like: the study of tissues, cells and genes put into terms of how they relate to each other in three dimensions. Think of an organ or a tumor as a complex city, where each cell is a building with its own role and relationships to its neighbors. Some cells might be driving a disease, while others are trying to fight it off. Traditional methods could tell us what types of buildings existed in the city, but not how they are arranged or how they influence each other. Spatial biology changes that by creating a detailed 3D map of every cell in a tissue sample, showing not just what genes each cell is expressing, but how those cells work together — or against each other — in the complex ecosystem of a complete tissue.

The Perfect Partnership

Drs. Ordog and Lee make a top-notch team. Dr. Ordog brought Dr. Lee, then a postdoctoral researcher at Indiana University, to Mayo Clinic to tune the technology he developed there toward human health applications. Dr. Lee’s primary focus now is an area called spatial transcriptomics, studying how gene expression in one cell affects gene expression in its neighbors.

“The ultimate goal is to build a 3D model of any tissue we study, providing information about how the cells are positioned relative to each other and how they behave — as in what genes and molecules they express,” says Dr. Ordog.

Molecules and genes are just the beginning. To Drs. Lee and Ordog, spatial biology isn’t just about the relationship between cells in one modality, but in all the ways they can relate to one another — their genes, their proteins, the ways they contact one another, cells dividing in one region and dying in another. Dr. Ordog calls this “spatial multiomics,” combining different techniques in the same space.

“We want these to be more than the sum of their modalities,” says Dr. Ordog. “The goal is to bring all these elements — the study of genes, molecules, proteins, etc. — into all relevant tissues.”

The Power of Spatial Multiomics

Bringing together all these different scientific threads will help Mayo Clinic do something completely unprecedented: create a whole new kind of pathology.

“Spatial biology shortens the translational pipeline,” says Dr. Ordog. Rather than needing to start with preclinical models, doctors and researchers can now start primary discovery with a tissue biopsy or surgical materials directly from a patient. They are looking for the needle in the haystack that might lead to a new discovery or therapy. 

The bottom line is that we want to increase the amount of information gathered from the precious biopsy material taken from our patients.

— Tamas Ordog, M.D.

“That’s what modern biology has enabled. You can pick out your molecule of interest based on whatever you’re studying,” says Dr. Lee. “You can study diseased versus not-diseased tissues. Say you discover molecules in diseased state that aren’t in healthy tissues, that’s your target.” Then scientists can go back to the lab and examine what they’ve discovered in other models to look for treatment options, armed with the knowledge that what they have found is directly involved in a patient’s health.

From Lab to Clinic

Dr. Ordog envisions a “virtual patient vignette”: A patient comes in with a form of cancer that comes in multiple forms, each with different prognoses, signs of progression and immune cell profiles, and each responds to different therapies. In the past this would be a dizzying knot to untie, but with spatial multiomics, it becomes clearer. A biopsy taken from the patient is serially chopped into sections, each of which gets processed a different way. Then the data is put back together into a three-dimensional image.

Instead of trying different therapies to see what works, clinicians could use this approach to examine the tumor's cellular architecture and predict which treatment would be most effective, saving precious time in the fight against cancer.

“The bottom line is that we want to increase the amount of information gathered from the precious biopsy material taken from our patients,” says Dr. Ordog. “Spatial biology can increase the understanding that comes out of the tissue exponentially.” That, in turn, can allow for in-depth machine learning and artificial intelligence analysis of patient data, which Dr. Ordog hopes to test sometime in the future.

All in all, Dr. Ordog, Dr. Lee and the entire team are hopeful their work will simplify the detective work that doctors and patients often experience when hunting for a diagnosis or treatment. Looking over a slide deck he uses to explain the technology, Dr. Ordog sounds a hopeful note.

“We can find the needle in the haystack without having to grind all the hay up.”

The post Reconstructing a Tumor Cell by Cell appeared first on Mayo Clinic Magazine.

Now, thanks to an innovative technology known as spatial transcriptomics, Mayo Clinic experts are able to examine how genes are expressed in a tissue sample in three dimensions, providing unprecedented insights into cellular relationships and tissue structure.

Understanding ‘Omics’

“Omics” is a term used to describe the collective study of biological molecules, from genes to proteins and beyond. Transcriptomics specifically refers to the study of gene expression — how our genetic code, or DNA, gets transcribed into RNA, which is then used to build proteins.

Understanding gene expression can help scientists better understand human biology by providing insights into where and when genes are turned on and off during development and disease. This is important for knowing how different cells function and how they interact with one another in the healthy body, as well as what changes when someone gets sick. Transcriptomics can be especially helpful for identifying biomarkers of disease, which can aid in diagnosis and treatment.

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Traditionally, transcriptomics is focused on understanding the overall gene expression within a tissue — for example, a researcher might examine the gene expression of healthy pancreatic tissue and compare it to the gene expression in a pancreatic cancer tumor, or even how a single cancer cell compares to a single healthy one. But these approaches do not preserve organizational information about how genes are expressed in different areas of a tissue or a tumor, or whether there might be variations in that expression across a sample.

A New View Through Spatial Transcriptomics

Spatial transcriptomics is radically advancing our understanding of biology thanks to the fact that with this technology researchers can see not just what genes are being expressed, but exactly where a gene is active within a tissue. This means that scientists can examine the gene expression within individual cells while preserving the broader context of how those cells are interacting with their neighbors.

This feat is accomplished through tissue preservation and microscopy techniques that maintain the tissue’s structure while measuring the expression of many different genes across the sample. This produces a detailed map of how different cells are behaving and communicating within, for example, a biopsy from a cancerous tumor.

In cancer, this is particularly impactful because it means that researchers and pathologists can now see exactly where certain genes are active within a tumor, allowing for a clearer picture of the molecular dynamics of the disease and opening new avenues for treatment.

Pioneering the Future

Mayo Clinic’s investment in spatial biology is another step toward truly personalized medicine. Led by Tamas Ordog, M.D., and Jeong-Heon Lee, Ph.D., a team of Mayo Clinic scientists are building a first-of-its-kind research core dedicated entirely to spatial biology, beginning with spatial transcriptomics. Supported by machine learning and artificial intelligence tools that analyze the 3D data generated from patient samples, they say this tool will reimagine how diseases are classified and treated.

This technology is already transforming how Mayo Clinic approaches complex cancers, as researchers work to create new ways to examine biopsy samples to predict which therapies will be most effective based on a tumor's unique cellular architecture and molecular signatures.

As the spatial biology technique develops, the team plans to build detailed tissue atlases to map the progression of various diseases in unprecedented detail, potentially revealing early intervention points and novel therapeutic targets that would otherwise remain hidden in the complex biology of human disease.

The post What Is Spatial Transcriptomics? appeared first on Mayo Clinic Magazine.