Johnson & Johnson

The corporations on our annual list of the world's 500 largest companies combined to generate $41.7 trillion in revenue over the past year.

Fortune Global 500

Almost $20 trillion in revenue—and a record-breaking $1.87 trillion in profits. Introducing the 2025 Fortune 500, the definitive list of the biggest companies in America.

Fortune 500

The 300 companies on this year’s list brought in over $12.6 trillion in revenue for the latest 12 months, with the median revenue figure at $22 billion.

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Leaders in all industries rely more than ever on Big Tech—and appreciate the giants that deliver, at scale, without drama.

World's Most Admired Companies

The corporations on our annual list posted aggregate revenues of $41 trillion for the second year in a row.

Industries included in the sector are insurance and managed care, medical products and facilities, pharmacy services, and pharmaceutical companies.

Fortune Sector Leaders: Health Care

The Fortune 500, in its 70th year in 2024, ranks the biggest U.S. companies by revenue.

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The 26th edition of the list shows how much esteem Big Tech giants command among other business leaders.

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The 25th Fortune World’s Most Admired Companies list suggests that tech giants’ peers respect them as much as ever.

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The corporations on our annual list of the world’s largest companies delivered a record $41 trillion in aggregate revenues.

The 300 companies on this list are transforming industries from the inside out.

The Fortune 500, in its 69th year in 2023, ranks the biggest U.S. companies by revenue.

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The health care company is best known for household items like baby shampoo and Tylenol, but pharmaceuticals and medical technology are its big revenue drivers, bringing in $52.5 billion and $27.4 billion respectively, compared to $14.9 billion in the consumer health segment. 
<ul> 
 	<li>Revenue inched up 1.2% to $94.9 billion in 2022, but profits fell 14.1% to $17.9 billion.</li> 
 	<li>The U.S. government phased out Johnson &amp; Johnson’s one-shot COVID vaccine, hurting the company’s pharmaceutical division.</li> 
 	<li>In April 2023, the company settled a decade-long legal dispute in which consumers accused J&amp;J’s iconic baby powder of causing cancer. The company agreed to pay $8.9 billion to tens of thousands of plaintiffs but has not admitted wrongdoing. Before the settlement is final, a court must accept a controversial bankruptcy filing by a subsidiary that Johnson &amp; Johnson created to shield its corporate assets from litigation. A court rejected an earlier bankruptcy filing aimed at reaching a settlement, which allowed thousands of related cases against J&amp;J to go ahead.</li> 
</ul>

Just as it dominates our economy, Big Tech now dominates Fortune’s annual ranking of corporate reputation.

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Aggregate sales hit $37.8 trillion last year—an increase of 19%, the highest annual growth rate in the list’s history.

This year’s Fortune 500 marks the 68th running of the list.

F500 2022-Johnson and Johnson

J&amp;J is home to globally known household products such as Tylenol pain medication and Aveeno body lotion. But over the past year, its health care and pharmaceutical businesses made the most news. The company began distributing its Janssen single-dose COVID-19 vaccine in March 2021. Manufacturing problems and the vaccine’s lower efficacy compared with products from Pfizer-BioNTech and Moderna hindered its adoption, but as of May 2022 about 19 million doses had been administered in the U.S., and millions more internationally. In July 2021, J&amp;J agreed to pay up to $5 billion as part of a nationwide settlement agreement to fund state and local efforts to address the opioid crisis. (The company admitted no wrongdoing related to marketing of its pain medications.) And in November 2021 the company announced that it would essentially become a pharma pure play; by late 2023, J&amp;J will spin off its consumer products businesses as a separate company.

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WMAC 2021-15-Johnson & Johnson

Total revenue for the world’s biggest companies fell 4.8% to $31.7 trillion this year—the first decline in half a decade.

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The 135-year-old global health care conglomerate sells everything from Band-Aids and artificial hips to surgical robots, cancer drugs, and one of America’s first three authorized COVID vaccines. The pandemic affected many of those businesses, and J&amp;J’s sales overall were relatively flat last year—notching up 0.6%. While the company’s pharmaceutical division performed well, results were mixed for the consumer segment: Sales of over-the-counter products like Tylenol surged, while baby care and women’s health revenues plummeted. Likewise, the company’s medical devices business recorded a sales decline of 11.6%, largely owing to people delaying procedures during the pandemic.

This year’s Fortune 500 marks the 67th running of the list.

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For an astounding 13th straight year, Apple claims the top spot in Fortune’s annual ranking of corporate reputation, based on a survey of almost 3,800 executives, directors, and analysts.

This year's Fortune Global 500 generated $33.3 trillion in revenues and $2.1 trillion in profits.

G500-2020-104-JJ

The sprawling 134-year-old health conglomerate eked out 0.6% sales growth in 2019 thanks to the strong performance of its pharmaceutical business, and particularly its immunology and oncology drugs. J&amp;J’s consumer business—with a portfolio that includes Neutrogena, Tylenol, and Listerine—was boosted by the acquisition of Zarbee’s, a purveyor of naturally based over-the-counter remedies. The company continued its push into the robotic surgery market in an effort to revive its struggling medical device business. J&amp;J is also mired in litigation surrounding its opioid and baby powder products. (In May, it announced it would stop selling talc-based baby powder.) While COVID-19 has dinged sales of some of its products—like contact lenses and artificial knees and hips—the company is one of the frontrunners in the race for a vaccine; J&amp;J has said it hopes to begin late-stage human trials by the end of September.

This year's Fortune 500 marks the 66th running of the list.

F500-2020-035-Johnson and Johnson

The sprawling 134-year-old health conglomerate eked out 0.6% sales growth in 2019 thanks to the strong performance of its pharmaceutical business, and particularly its immunology and oncology drugs. J&amp;J’s consumer business—with a portfolio that includes Neutrogena, Tylenol, and Listerine—was boosted by the acquisition of Zarbee’s, a purveyor of naturally based over-the-counter remedies. The company continued its push into the robotic surgery market in an effort to revive its struggling medical device business. J&amp;J is also mired in litigation surrounding its opioid and baby powder products. No surprise, the company has been impacted by COVID-19 in various ways; while its pharma division is racing to develop a vaccine, sales of products like artificial knees and hips are down due to the cancellation of elective surgeries during the pandemic.

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Change the World

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This year's Fortune 500 marks the 62nd running of the list.

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The world's 500 largest companies generated $31.2 trillion in revenues and $1.7 trillion in profits in 2014. Together, this year's Fortune Global 500 employ 65 million people worldwide and are represented by 36 countries.

This year's Fortune 500 marks the 61st running of the list. Wal-Mart claims the top spot again. See who made the list.

Global business is back. After limping through a worldwide financial crisis and economic slowdown, the 500 largest companies ranked by revenues shattered all sorts of performance records in 2013: They racked up combined revenues of $31.1 trillion, up 2.5% from 2012, and profits soared 27% to nearly $2 trillion. China’s 95 companies (up from 89 last year) posted $5.8 trillion in revenues. The U.S. has four fewer companies on the list than last year but remains (for now) the country leader, with 128 corporations on the list—including No. 1 Wal-Mart Stores—reporting $8.6 trillion in revenues. 

Wal-Mart stayed on top as its sales crept closer to half-a-trillion dollars. Apple moved into the top five. And UnitedHealth Group continued its steady climb. 

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Johnson &amp; Johnson, founded in 1886, is among the world’s largest and most influential health care companies. It is involved in the research, development, manufacture, and distribution of innovative medicines and medical technologies. The company’s innovative medicine business operates in areas including oncology, immunology, neuroscience, and cardiopulmonary treatment. In medtech, the company is focused on developing and delivering cardiovascular, orthopedics, surgery, and vision solutions.

Q2 2025

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Q4 2024

Johnson & Johnson (JNJ): Company Profile, Stock Price, News, Rankings

legacy

johnson & johnson

Johnson & Johnson, founded in 1886, is among the world’s largest and most influential health care companies. It is involved in the research, development, manufacture, and distribution of innovative medicines and medical technologies. The company’s innovative medicine business operates in areas including oncology, immunology, neuroscience, and cardiopulmonary treatment. In medtech, the company is focused on developing and delivering cardiovascular, orthopedics, surgery, and vision solutions.

Johnson & Johnson (JNJ): Company Profile, Stock Price, News, Rankings | Fortune

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Highlights from Fortune's annual CEO Initiative event include U.S. Treasury Secretary Janet Yellen and Johnson & Johnson CEO Joaquin Duato.

Leadership Next: Janet Yellen and J&J

Leadership

I suppose I should let this group in on a little secret about our past. I have a master's degree in Economics, which I got at the London School of Economics for which was the one year that secretary Yellen taught there. So she, she taught what little I know about macroeconomics. I learned from Janet Yellen. Welcome to leadership. Next, the podcast about the changing rules of business leadership. I'm Alan Murray and I'm Mia Allen. I see you're back in New York after a whirlwind few days in DC, there was so much going on there, including our very own fortune CEO I conference. So for listeners who don't know the Fortune CEO initiative was created seven years ago to give ceos of purpose driven companies that really want to focus on improving their positive social impact on society. Give them a forum where they could exchange ideas and best. I got a master's degree in Economics at the London School of Economics for six months. I would go in uh every day and get a uh what I'm sure was a brilliant but completely incomprehensible lecture from George Akerlof. And then in the afternoon, Janet Yellen would come in and tidy it all up. She's still the same person who stood at the front of that classroom uh so many years ago and can take very complicated subjects and make them sound very simple and clear. This was very exciting. She joined you on stage actually, just a few days after the government narrowly avoided shutting down. The first question for you is, is this mess going to change the relative optimism you had about the US economic outlook. Look, I'm very optimistic about the US economic outlook. Short term. Um inflation is coming down in the context of an extremely strong labor market, what people would normally call a soft landing um which is amazing by the way, it hardly ever happens. Correct. And um it it's great because of course, we want to see inflation come down. It's been burdening Americans, but we want to maintain the good strong labor market that we have. And we seem to be on that kind of path and medium term. Um We are now engaging in a very substantial program of investments to strengthen our economy, to boost our productive capacity, to boost productivity growth, to draw more American workers into the labor market and to address long-standing structural problems like um climate change and inequality across people races and places. One of the interviews that we're really interested in sharing with all of you uh was an interview that our editor in chief Allison Chantelle did with Johnson and Johnson, Ceo Joaquin Duato. Um Tell us a little bit about that one. The thing about Johnson and Johnson is, it has been a purpose driven company for many years. It has this famous credo that they really train everyone at the company and and Joaquin was a perfect representative of that credo. I think you'll get that in this conversation. I think there's a number of reasons for having low attrition. One is the size of the company that enables people to work in different sectors and have careers between Johnson and Johnson. Sometimes I say Johnson and Johnson has its internal job market. The other one is that people simply like to work for Johnson and Johnson. Uh our engagement levels are high. People like to work for a company with a purpose in health care. We are a company that pays a lot of attention to inclusion, so everybody feels good when they come to work. And certainly we like to believe that we are a caring company that we care, not only for the patients, but we also care for each other. So we, we try to have a strong health and wellness offering for our employees. So overall, people like working in Johnson and Johnson and stay longer in Johnson and Johnson, our average tenure, for example, in the US is more than a decade. So people can do careers and and we are happy of that. We, we, we are glad that people like to stay at Johnson and Johnson longer.

Alyson Shontell sits down with Johnson & Johnson CEO Joaquin Duato to discuss how AI is being used in cancer cell therapy to attack the cells and turn the cancer into a chronic illness. The company's also using robotics technology to assist surgeons to significantly improve the average outcome of the surgeries.

Here's how Johnson & Johnson's CEO is using AI to end cancer

Conferences

Alyson Shontell sits down with Johnson & Johnson CEO Joaquin Duato to discuss how AI is being used in cancer cell therapy to attack the cells and turn the cancer into a chronic illness.

Here's How Johnson & Johnson's CEO Is Using AI To End Cancer

First, I should note Johnson and Johnson has been one of 49 companies to be in the Fortune 500 List every single year since we've made it since 1955. This year, they clocked in at number 40. As Alan said, the health care and pharma markets have been booming. Um And you've been in the job for two years, but you've been at the company for 34. So you've seen quite a bit um two years in what's your primary focus and biggest surprise since becoming CEO? Thank you. And um it's, I'm proud to be uh the CEO of Johnson and Johnson in our, 100 and 38 years of history. We have had only eight CEO S uh and I am the first one who is not born in the US. And I'm proud to represent that. And uh certainly it's a great legacy that we have had during this period. So in becoming CEO of Johnson and Johnson, uh I have a dual purpose. One is to uh remain a company that is true to our mission of addressing uh difficult to treat diseases. Um And the other one, it's to be able to continue to be a company which is principal based people based and maintains the reputation that we have had during such a long period of time. Now, is it true that you didn't get the job at first? I mean, not the CEO job, but you initially, when you were interviewing 34 years ago, they said, no, it's true. I, when I finished graduate school, I interviewed with Johnson and Johnson and I didn't make it to the second interview. So um then I, I joined another company, a pharmaceutical company and eventually found my way back to uh Johnson and Johnson and I've been here for 34 years and I'm really a product of the development opportunities that Johnson and Johnson provided me working in different geographies in different sectors, in different functions. So I'm here. Really thanks to the opportunities that Johnson and Johnson provided me. I mean, the longevity of your career there, I think is telling and the attrition rate is shockingly low at Johnson and Johnson. Right. Yeah, it's, it's very low. Uh it's lower than the industry and our pr companies. And I think there's a number of reasons for having low attrition. One is the size of the company that enables people to work in different sectors and have careers within Johnson and Johnson. Sometimes I say Johnson and Johnson has its internal job market. The other one is that people simply like to work for Johnson and Johnson. Uh Our engagement levels are high. People like to work for a company with a purpose in health care. Uh And we are a company that pays a lot of attention to our people, their development. We just had yesterday, for example, we had a, a global learning day. So we gave all employees a full day to develop a learning mission and to get acquainted with the learning resources that they want to use. We are a company that pays a lot of attention to inclusion. So everybody feels good when they come to work. And certainly we like to believe that we are a caring company that we care, not only for the patients, but we also care for each other. So we, we try to have a strong health and wellness offering for our employees. So overall people like working in Johnson and Johnson and stay longer in Johnson and Johnson, our average tenure, for example, in the US is more than a decade so people can do careers and, and we are happy of that. We, we, we are glad that people like to stay at Johnson and Johnson longer. So when you became CEO and even in your memo to become CEO, you said, I think we should spin out the consumer business. Um You know, Johnson and Johnson can compete with l'oreal there, but should it? And so could you speak a little bit about KVI, which is the company that you spun out just earlier this year, it's now publicly traded. Um How you, why you did that? Um why is return to focus important for Johnson Johnson versus diversification of business? Yeah. So is our consumer company. So when you think about the Johnson and Johnson and the brands that you know about Johnson and Johnson Band Aid Tylenol or Baby shampoo? Now, they are all in KVI. Why did we decided to separate KVI and create a global consumer champion with? Because we thought that uh focusing on the consumer market and focusing on health care was going to deliver better results for consumers and for patients. Uh for us, it was very complex to be able to compete with l'oreal, as you mentioned in skin care. And at the same time, competing biologics with biopharmaceutical companies and in surgical robotics with medical technology companies. So we thought there was a benefit for Johnson and Johnson to be exclusively focused on health care, on research and development on innovation. And that was going to create a better platform for us to be true to our mission, not only in the next two or three years or post IPO, but during a long period of time. Um and what's your advice been to the new CEO? And how did you make sure that they were set up with a good culture and you maintained yours? I am, I am very proud of the, of the management team of the entire management team of including the new CEO come from Johnson and Johnson. They are also the product like me of the development opportunities of Johnson and Johnson. And uh I told him, uh you know, be patient and put perspective on things, learn how to listen more. And I gave him confidence that they were going to do great. So I put my emphasis in providing confidence to the management team and to give him some advice about uh be patient and put in perspective in the job of CEO, you have to be patient, you have to put perspective on things and I'm helped myself by being a Mediterranean. And uh I take things with certain perspective and I wanted to transmit that wisdom to him. Um Well, this conversation is short and so I want to make sure we hit on a number of things we've talked about that spin off for a long time. But one thing I do want to make sure I hit on is um R and D is a huge part of Johnson and Johnson. Um What are you seeing in the face? You said that this is the golden era for your business that there will be more change and more positive movements towards curing disease over the next few years than you've seen in the last number of decades. So, what are you seeing? That's exciting. What are the innovations and, and what are you doing with things like robotics? A I how is that all changing the industry? Yeah. So R and D is the, the, the heart of an innovation based company. Uh Last year we invested $14.6 billion in R and D. And Johnson and Johnson, we are one of the largest, if not the largest investor in R and D in life sciences. Um What we see now is a combination of more knowledge on the biology and genetics of disease with an acceleration of that due to technology, things like artificial intelligence, machine learning and now generative A I. It's helping us accelerate drug discovery and it's helping us also making medical technologies smarter. So that combination is what I believe is going to help us addressing some diseases that are considered incurable or diseases that create a lot of suffering around the world. Two examples. One is in the area of cancer. We are being very successful utilizing different treatment modalities in cancer. For example, now we are using in cancer cell therapy in imma tumors, utilizing your immune system cells to attack the cancer cells and we obtain incredible responses in a way that you could think that some cancers Emma cancers are going to become chronic diseases in the surgical side. Uh surgeons are now able to utilize robotic assisted techniques, better visualization, better sensors. They, those instruments are connected, they can provide them insights and they can significantly improve the average outcome of surgery. So those are things that are going to help accelerating discovery and progressing health care in a way that we have not seen in the last 10 years. And one thing we had a lunch previously and you had mentioned, you imagine knee surgery, but being done by maybe a robot versus a surgeon. I mean, think about the precision needed. I might prefer a robot for something like that than someone with a potentially shaky hands. Absolutely. All our instruments now have some component of intelligent intelligence or connectivity. So our instruments now have sensors that can measure pressure temperate to have visualization capabilities, which at the end of the day is software is digital that give an idea of the surgeon of where are they in, are they going to interfere with a critical structure and all that can be visualized and we can even provide uh guidance to the surgeon in real time or where they have to go. So that's gonna be transformational in the way we do surgery and it's gonna help improving the outcomes of a procedure, which is very common. I'm sure in the audience every one of you have had some type of surgery during your life. So that's important if we can improve the outcomes and the quality of surgery. When I think about what we can do as a company, uh we have the range of technologies to be able to do what no other company can do. We can do cell therapy, but we can do robotic surgery. We can do, we can do genetic or MRN A therapeutics and we can do also smart implants. So there's a lot of things that we can do as a company based on the number of technologies and capabilities that we have. So as the leader of a company, he used to lead in good times and in bad and with a company as large as Johnson and Johnson, there are hard things and there are lawsuits. Um You've had talcum powder lawsuits, opioid crisis to deal with um COVID. Um you know, having your vaccine essentially be dismantled. How do you lead in those hard times? How do you encourage your team to not lose morale? Um Stay focused, stay focused on the mission when there's a lot of hardship around? Yeah, we do it with conviction, a conviction on the principles of our credo that by the way, this year is the 80th anniversary of the credo was written. And uh we do it by having a trajectory of uh more than 100 years in which we have always tried to do the right thing for the patient. When we uh make a mistake, we take responsibility and when the facts, uh the science and the law are on our side, we stand by uh our products and we have been able to manage this um this balance during many years. But the people in the company working at Johnson and Johnson have a genuine passion of doing the right thing. And we don't do it for the recognition. We do it because we have convictions and those convictions normally help an organization to manage change. I'm convinced that purpose driven organizations are much better in managing change. And our organization has a strong tradition of being a purpose driven one. We internally, we say we are the original mission driven company based on the fact that our work was written 80 years ago, 80 years ago, talking about putting the patient first, the employees, the communities. And then if you do the right thing, uh it's gonna be good for the shareholder was and very innovative, very different. So I think that that's part of the energy that people at Johnson and Johnson have in order to navigate the ups and downs that anything in life it's going to present you with. Quick question from the audience. Yes. Right over here. Uh uh I wondered with the new legislation. Um what impact that's gonna have on the ability to do the research you're talking about and whether you think that the advantage in technology, sorry, if you can hear me uh will help take a will help um address the efficiency side. So maybe there will be more resources. I just wondered how you looked at that. We always want to be a constructive actor when it comes to health care. The recent legislation that you are referring to. I'm, I'm I'm assuming you're referring to an Reduction Act, right? And the fact that now, uh, Medicare is going to be fixing prices for some products. Uh, on one hand, uh, we believe that this, um, this legislation is misguided, uh in as much that, uh, there's been a lot of, or a number of challenges constitutionally to the law and there's a number of companies that have present the lawsuits. On the other hand, it's gonna have a chilling effect on innovation without addressing the basic issue that we have when it comes to pharmaceuticals, which is the patient affordability and the patient out of pocket costs. So inevitably, uh this will have an effect on, on, on R and D investments because it would make it more unpredictable and it would be particularly acute, not in the big company, not only in the big companies like Johnson and Johnson, but in the smaller companies that are funded by investors because the return for those investors is going to be more unpredictable. At the same time, it's gonna be shaping the way we invest in R and D. So, you know, on one hand, it doesn't address the issue of patient affordability, which is real. And on the other hand, it, it's going to have a chilling effect on innovation. Um Thank you all so much and thank you so much for being here with us this morning. Thank you.

Regina Dugan, PhD, President and CEO, Wellcome Leap
Margo Georgiadis, Co-founder and CEO, Montai Health
Najat Khan, PhD, Chief Data Science Officer and Global Head, Strategy & Operations, Pharma R&D, Johnson & Johnson
Moderator: Dr. Lloyd Minor, Carl and Elizabeth Naumann Dean, Stanford University School of Medicine

Brainstorm Health 2023 - How Ai Is Advancing Healthcare R&D Today 

Regina Dugan, Wellcome Leap
Margo Georgiadis, Montai Health
Najat Khan, Johnson & Johnson
Moderator: Dr. Lloyd Minor, Stanford University School of Medicine

How Ai Is Advancing Healthcare R&D Today 

The health care system is ailing and some say artificial intelligence and machine learning could lead to the cure. Its applications fit many aspects of the health care space from the ground level of research and development all the way to patient care. The expectation and anticipation of what A I and M L can do are enormous with the belief that A I can help solve problems that are beyond the limits of human abilities. So let's talk about how the technology can be used at scale to help build better systems and healthier lives. Dr Lloyd Minor is Dean of the Stanford University School of Medicine, which is brainstorm Health's academic partner. Dean Minor will lead a conversation with Regina Dugan phd CEO of welcome leap, a nonprofit that works to accelerate breakthroughs for global human health through bold initiative, innovative programs, Margot, Georgia co-founder and CEO of Monte Health, which pioneers leading edge technologies to preempt and treat chronic disease. And Neat Khan PhD, Chief Data Science Officer and S V P and Global Head of Strategy and Operations for R and D at Jansson Johnson and Johnson. Please welcome them all. Well, good afternoon, everyone. I'm delighted to be with three outstanding innovators and leaders. And we plan to include you our audience in this discussion as well. But maybe we can get started Regina with you. And could you describe Welcome Leap, your organization and how you're using A I today and the work that you and your colleagues are doing and we'll go down the line with, with everyone for that question. Happy to Lloyd. So, welcome Leap is an organization that is designed to increase the speed and number of breakthroughs in human health. And we are using A I and machine learning across a number of our programs and they're very diverse. The applications of now. It's my sense that one of the reasons the life sciences have been a little late to A I and machine learning is two fold, one some initial skepticism, but also lack of data. And if we see now the explosion of data in life sciences, that's part of what creates the opportunity for A I and machine learning. And that's across computer vision for teaching and training systems in surgery, for learning how young Children develop language and so on. Fantastic. Thank you Margo. So just you know, building on that theme of the explosion of data, Monti health is really scaffolding off that to create um breakthrough therapies, small molecule therapies to help us stem the chronic disease burden. And the reason I got into this is two reasons, right? We've talked about it almost the last two days, right, two billion people around the globe suffering with these diseases. About half of them are inflammatory based and most of them don't have treatments that enable early intervention or long term use. And the R and D engines really aren't keeping up. Right, 30% of the therapeutics that go into the clinic fail because of safety problems alone. And that's $15 billion a year going down the drain. In addition, if we look at a lot of the therapies that are available, we have some amazing things like biologics, but most of those are only available at later stages of disease. And people only about 5% of the people who have these diagnosed conditions can get access to those because of the safety issues as well as cost. So we really took on this challenge of how could we use A I to reimagine, how we could create safe small molecule therapeutics, do that efficiently, rapidly and repeatedly so that we could get solutions to as many patients as possible. And it's actually really personal for me. I have a son who's spent the last 20 years suffering with several really debilitating chronic diseases. And when you watch what happens in someone's life, when they wake up every day in pain or they wake up every day with severe health issues, it motivates you to say there's got to be a better way to tackle some of these things. And I'm excited about the possibilities in A I to enable us to decode the language of chemistry, which is what we're doing and then building it scale for the first time, the largest understanding of what we call answer molecules. These are human qualified molecules, these are molecules that have coexisted with humans for hundreds of thousands of years in our food herb supplements other places. And we're actually understanding and using this ai capability to survey that landscape as never before essentially industrialized scale. So that we can identify the best possible keys that exist within the products of nature that are human qualified, that we can actually use as potent therapeutics. And we've demonstrated we can do this in a wide range of application areas. And we're excited to be advancing therapeutics to the clinic. You know, I might add Margot that in one of our programs that's focused on RNA. What we know is that for an RNA based vaccine like the COVID vaccines, there are approximately 10 to the 6/100 power different ways to encode the instruction set. We can't computationally solve that. So we're using A I and machine learning to address that problem. That's another example in the drug development side. Yeah, a great example, for example, in any molecule, there's roughly a million permutations of structure and function in a single model, every edge of that molecule, which really makes the drug, some of it would say this is bio and other people would say how soluble it is permeable, how toxic it might be. And so without compute capabilities, we can't disentangle that language. Just like chat GBT learns the English language. We have to learn the language of chemistry and then use compute to enable us to solve these really hard problems. Yeah. Now, first of all, great to be here. So how we're using data science A I machine learning, you know, the core of what we do is how do you actually develop medicines, right, that are effective and safe. And if I start from the inception of how you figure out what's going wrong when someone has a disease is what's driving that disease, right? That's the first order problem that you're trying to solve. And if you look at so many diseases today, let's take Alzheimer's Parkinson's, it's named after the physician that figured out the syndrome that has nothing to do with the biology or the disregulation that's driving the disease. So that's step one, right? And a lot of the data sets that are being developed multi omics, let's just call it genetics transcript omics so forth, helps you in leveraging machine learning. We're finding out like depression. Actually, there's several subtypes of depression, it's not one disease. Um You know, look at Parkinson's, there's actually various drivers of Parkinson's and more and more that we are learning. Why is that important? Because if we can know what's driving the disease, then you have a much better chance of treating the right patient with the right medicine at the right time. So that's problem. One, the second area that we're using it quite a bit is around precision medicine, right? So, um you know, one of the aspects, let's say in oncology, even if you know what driver mutation is causing the disease, you look in the real world, most people are not getting sequenced. So, yes, you know what's causing the disease, but you're not finding the patients, you got to find the patients. And we heard other panelists say that. So we are using machine learning and A I on data that's collected routinely histopathology images E C G echo to be able to diagnose diseases earlier. So for instance, it just came out today, we just got breakthrough device designation for an A I algorithm on echoes that can pick up a amyloidosis, which is a rare disease years in advance, right? Um The other example is for instance, different mutations like F G F R E G F R, you can actually predict the mutation from the biopsy image. That makes a huge difference because when the patient gets a biopsy, you actually know what mutation they have. So then you can direct the right medicine at the right time. And then the third area, I mean there's many areas. The third big area that we're leveraging machine learning I would say is in creating better end points. The thing about it, you have a medicine, you understand what's driving the disease, then you start a trial. But if your end points are not specific enough, if it's just a composite, you know, pen and paper, you're not going to be able to understand the signal to noise you really want to see is someone benefiting from it the way you want to. So, you know, Margo, you talked a little bit about inflammatory diseases. Let's take and Crohn's IBD, only 30% of the patients actually respond. What that tells you is that we don't know how to stratify the patients mechanistically as well as we should. So we've developed an algorithm basically where instead of scoring how severe the disease is the way it's done today, which is if I have one flare in my large intestine versus you have seven, we get the same score, right. So it's not localized, it's not sensitive enough. So we have end points now where you're looking frame by frame thousands of frames as the endoscopy video is done. And you can actually get a full representation of the severity at such a granular level. So then you can figure out who's feeling better versus not. And then the last thing is clinical trials, we talked about diversity. We talked about, you know, being patient centric, we're using machine learning to say, OK, where are the patients in a de identified way? So it's all with the right privacy, et cetera where are my eligible patients. And how do we open up sites to where they are? Two benefits. One you go to where the patients are, you can recruit faster and get that medicine to patients faster. But the second is in a lot of cases, people of color, people with like tougher socioeconomic status are in areas of more remote areas. So then you can actually leverage this to get more diverse patients. And we have many examples where we have done that um doing both machine learning and using decentralized trials. So put it all together machine learning is being used at every single aspect. It's not an idea anymore across R and D. And that's how you capture the entire value, not just doing point solution but compounded impact and effect by improving the probability of success that all this hard work that we do is actually going to be a good medicine for the patient, right? Maybe one other quick question and then we'll open it up to the audience. But of course A I covers a variety of different disciplines and approaches, probably the newcomer and maybe the most transformative of all are the large language models and generative A I based on transformers. And I'm wondering how you're thinking about how you're going to leverage uh generative A I and approaches derived from generative A I in the work that you're doing in your companies and in your endeavors. Regina. Do you? Yeah. Well, I mean, I think, look, I think we've hit a real inflection point with, with a generative A I, I think we've been waiting a long time for it and it's early days still, I think the applications are opening up particularly in the health sciences and the other sciences. From our perspective, it will be one of the strategies that we use, mixed with other technological advances to get the kind of breakthroughs that we need. And I think, you know, Najat touched on the various measures that we're using and how A I and machine learning are playing in those areas. But there are also opportunities to intersect across those different measures. And we're seeing those opportunities emerge quite effectively. Depression is a very good one. So still after 20 plus years and $22 billion of investment, we have one out of three patients responding, it's just not good enough. And what we're seeing in one of the programs we're running multi channel psych is the opportunity to use A I and machine learning across the various measures from genetics all the way up to the digital phenotyping to get to better predictions for the medicines so that more people can be treated effectively on the first try. And, and what I think is generative A I is going to be a very important part of each of the lanes and in crossing the lanes as well. Yeah, I agree with that completely. Um I think we've had this conversation over the last day, which is we get the most accuracy when we start constraining the problem. So we see it in enterprise, right? If you go and ask chat GBT, a generic question, they're going to be not right, a lot of the time. But then if you break it down and you go and you go after a chat bot opportunity that enables you to get the return rate data at a scale where you can actually be precise. So I think that's what's exciting is to try to find those pieces. And that's really what we've done at Monti is we've set. If the most important thing we need to do is rapidly and efficiently find efficacious and safe therapies, we can strain the space. So we used a cousin of those large language models which is really scaled graph, keep learning models to understand this language of chemistry and enable us to make it searchable and understandable. In the same way you can do the English language, we just do it the language of chemistry and all those structure function relation ships that make up a molecule that becomes a drug. But then we attach and constrain the chemistry set to say the chemistry set has to be human qualified because we could use infinite types of chemistry and understand that. But then we have no understanding until we get much, much further in the drug development process. Is this actually a molecule that can coexist in the human body. And so by constraining, that gives us much faster feedback loops and a much greater understanding of data. So for example, there's like 2700 approved therapies today, but we've already created Anth grass of 100,000 of these much more diverse molecules that have coexisted with us. And we know from that last panel that food is medicine, we've just never understood it at the molecular level. And so what A I enables us to do is decon that chemistry and human biology connection so that we can rapidly and repeatedly for any known biology come up with powerful therapies. And in our case, we focus on the most powerful as you talked about pathways that truly underlie these diseases. And by using these safer molecules that have this history of human consumption that enables us to efficiently land in severe stages of disease from a development perspective, but then have the highest probably of success to be able to back those molecules up into earlier stages of disease with alternative dosing levels or formulations so that we have this chance to intervene earlier. When we have those great signals that we have the onset of these diseases, we have to think differently because otherwise, when we talk to our farm, you're not willing to take on those large scale clinical trials in those earlier stages of disease because the safety failure rates have been so high for so many of these therapies. And so we've got to find a way because we all want health care, not sick care. And if A I can enable us to take the serendipity of where drug discovery started, right, finding any fungals and any virals. And we can now industrialize that and make serendipity predictability. That could be transformational as we think about the future of developing safe efficacious medicines. And so that's why I'm excited about it to answer the question. I'm like, you know, and I think that's a great point. You raised Margo in terms of how we're using large language models in generative AI I'll maybe structure it in like three ways. One is really around, you know, understanding the language of chemistry. And I would say biology, why is that important? I remember when I was in grad school, it would take and I was doing in modeling, by the way, it would still take months to make a molecule, right? And you say, OK, I think this is a protein. This is what I want to design. Now, you can actually use these generative A I algorithms to say this is what the protein probably looks like. And I'm going to say what the molecule should be and back into it. The difference is you improve the starting point and if you improve the starting point, your probably a success of what would become a medicine is much higher. However, it's not important, it's not sufficient to just make it a tighter binding. You have to make sure it's safe, you have to like make sure it's not immunogenic. There's so many things you can do all of that in parallel. So that's one and I think that has, it's not prime time yet, but there's a lot of promise there. The other end of the spectrum is think about when you're actually starting a program, you're going to all these papers and trying to figure out who's done what we have that version internally, we call it met dot A I ask, but essentially like a bio GPT for where you can quickly form hypotheses, right? That searches all of the omics data, the essays we've done internal and external super super important. And then the last thing in the middle and we talked about depression. How is it that a patient who has depression today? How do we figure out if they're better or not? Again, you answer a questionnaire. How subjective is that quite subjective? Instead what we're trying to do and actually deploy in our trials is use speech, acoustic, right? Use speech, how you're typing all patient consented? And then we use large language models to transcribe that into a sentiment uh ranking. So is your response something that is more indicative of depression? Why are we doing that? You make it much more objective? Number one, number two, you personalize it to every single person because everyone's type of depression and how you, it is not the same. So again, all of these helps you bring together precision medicine. You know, the last thing I'll say, no matter what approach or technology or whatever you have, the most important thing is to answer a question that matters to make of medicine. Everything else is just an enabler. That's great. Well, this has been a wonderful discussion and we could go on for a long, long time. I think you could see why, you know, truly, thank you for your leadership. Each of you is doing such remarkable work in leading amazing organizations. Um And we have to do this again soon. Thank you. I'm sorry. We didn't get to questions, but this has been fascinating. Thank you very much.

Dr. Hala Borno, Founder and CEO, Trial Library
Vanessa Broadhurst, Executive Vice President, Global Corporate Affairs, Johnson & Johnson Dr. Aditi Mallick, Chief Medical Officer, Medicaid and CHIP, Centers for Medicare & Medicaid Services
Moderator: Rachel Lobdell, FORTUNE

Brainstorm Health 2023 - Dollars and Sense of Health Equity 

Dr. Hala Borno, Trial Library
Vanessa Broadhurst, Johnson & Johnson 
Dr. Aditi Mallick, Centers for Medicare & Medicaid Services
Rachel Lobdell, FORTUNE

Dr. Hala Borno, Trial Library
Vanessa Broadhurst, Johnson & Johnson 
Dr. Aditi Mallick, Centers for Medicare & Medicaid Services
Moderator: Rachel Lobdell, FORTUNE

I've been so personally impressed with the speakers we've had here over the last 24 hours and the leadership that they're bringing to health care, but really to the world, we obviously need more of that leaders who act with a sense of purpose. What Apollo Ono called Iki Guy and have a positive impact on all their stakeholders. Fortune is doing its part to help develop those leaders. It's, it's led to the creation of our membership driven community for next generation leaders called Fortune Connect. The goal is to create truly purpose driven leaders to help them understand what stakeholder capitalism is really about to help them understand what it means to lead truly equitable and inclusive workforces. The program is designed for mid career professionals who are rising fast on the executive track. I'm sure all of you have folks like that in your organizations. I would encourage you to check it out. Fortune Connect dot com or come to me directly if you'd like to get more information on it. So now let's continue our conversation here today where you're born, where you live, your age, your economic status, and of course your race all of those are just a few of the factors that figure into health equity. They're the so called social determinants of health. They can make the difference between a long relatively disease free life or conversely lead to excess morbidity and premature mortality. Inequities in health care have long been a chronic issue. We've talked about it on this stage before. It's a massive problem that will take a dynamic and multipronged approach to resolve. Uh Today. What we want to focus on is the economic impact of health inequity. There's data from Deloitte. New data that shows that the US US health system cost approximately $320 billion in equity costs. Approximately $320 billion could eclipse a trillion dollars in annual spending by 2040 if nothing is done to fix the problem and that's clearly not sustainable. Joining us now to talk about that, how equitable health can lead to better outcomes across the board are Hela Bono, Hela Bono, a former CEO of Trial Library, Vanessa Broadhurst, Executive Vice President of Global Corporate Affairs at Johnson and Johnson. Uh a male doctor, a male chief, medical Officer of Medicaid at the Centers for Medicare and Medicaid Services. All of them in conversation with Fortune's Jeff Colvin. Please welcome them to the stage. Ok, let's have a seat so much to talk about here. I want to start by asking you all for your views on the same question. Uh The pandemic changed everything is the United States as after the pandemic is the United States ahead of where it was on health care equity behind where it was pre pandemic or no change. I think all of us can recognize that the pandemic put a spotlight on health inequities in the United States. In the early days of the pandemic, we saw that racial, ethnic minorities were disproportionately impacted by the condition. It places an imperative on us to make sure that as we're developing vaccines, something that opened up society allows us to be in this room today, that we actually include the populations that are disproportionately impacted by the condition that imperative has led to a lot of innovation. I'm really excited about the innovation that we're seeing in improving and advancing access to clinical trials. It's also led to a lot of accountability. There's increasing regulatory pressure to make sure that study sponsors those supporting the implementation of clinical trials are actually fulfilling measures, mechanisms that are evidence guided to include diverse populations into studies or that will impact their ability to bring their drug to market. So that really shows this clear linkage that we've always recognized that doing the right thing, including everyone in clinical research is also good for business and that is a good outcome that has come out of the context of our pandemic. The innovation has also impacted the conduct of clinical research where we've seen a lot more decentralized models you know, using technology to access patients where they are engaging them, where they are to reduce the burdens that we're placing on them because we know that including everyone in clinical trials is actually good for all of us. Yeah, Vanessa, did we make progress on this during the pandemic? Listen, I think we did. I think what he said was true that it really exposes, you know, the underbelly of what was going on and COVID just amplified the problem and brought it front and center to everybody's attention which you know has good. Um I think that the the also the good thing that happened from a clinical trial approach, we had to do things very differently. We had to use A I to find out where the disease was going. We had to use predictive models. We had to think of different ways of recruiting patients that maybe were not as face to face intensive. So I do think that the industry is starting to change for good and just the critical nature of that need was exposed through the pandemic. What do you say? Totally agree. I think the bright spots I would highlight are to just foot stomp and echo what's been said, igniting a national conversation that centers health equity. Literally, I mean, you would be hard pressed now to find a health system and ensure any any entity that touches health care that doesn't have a diversity equity inclusion type of office if not entire sets of initiatives. The other thing that I highlight from a policy perspective is massive coverage gains. We are now in this country at historic levels of uninsurance. So a 30% increase in Medicaid enrollment or 21 million people that now have coverage through Medicaid and chip that didn't as of February 2020 right? And we know I will just add that that is disproportionately communities of color, right? So when you look at Medicaid expansion, both in the context of the AC and Medicaid expansion in the context of the Coronavirus Relief Act funding disproportionately that impacts people of color to have the peace of mind really that comes from having health insurance coverage. One of the other great things is just the massive amounts of partnership that it took to get through the pandemic. When you look at, you know, the governments, private corporations, health care providers, there was such a stress on the system that it really created a very unique environment where everybody was really forced to think about how we work together to solve big problems. Audie, I just can't help thinking. You, you mentioned all the people who got on to Medicaid among other things during the pandemic right now. Of course, that's coming to an end and a lot of them are going to be pushed out of Medicaid. What's going to be the result overall, I will say, I wish I had a crystal ball to know, I will say tremendous effort underway to ensure that every eligible person retains health care coverage. Whether that is in Medicaid through the exchanges for folks that are able to access employer sponsored insurance. The estimates are somewhere between 15 to 18 million people with of confidence intervals on either side are subject to coverage loss and about 50% of those people might be for administrative reasons, didn't have the right address, couldn't get a hold of them return mail, things like that, which suggests that they may, they may in fact be eligible and they may not know it. That's right. That's right. And so, you know, to everyone in this room, I think there are things that anyone everyone can do from your vantage point to make sure that people know where they can access coverage. It's check out this website, call, this phone number, go to this address. Um but we are um staring down the pike of what promises to be the single biggest coverage transition event since the launch of healthcare dot gov. Well, I can tell you what to say so. Well, I mean, I I'm concerned of course, that loss of coverage means that we're going to see unnecessary deaths. It's pretty well published that when patients cannot access preventative care, they present with more advanced disease. If they present with more advanced disease, they're less curable. And so that's a reality that we really need to think about and to and to put pressure to ensure that we don't have those unnecessary deaths in the United States. Yeah, there have been mentions of the clinical trials that were done in the uh development of the vaccines for the pandemic trials. Are your specialty? Uh What did we learn with regard to health equity about the clinical trials of these vaccine candidates during the pandemic? Well, the pandemic certainly showed us that clinical trials are a social good with vast benefits to society and an inclusive approach is worth it. But it takes effort. It takes community engagement and ear on the ground provider activation, activating the providers who are seldom offering these opportunities to their patients. So we've learned a lot about the ways that we can innovate to actually do the hard work to achieve inclusivity in clinical trials. And when you look at the demographics of patients that participate in the COVID-19 vaccine clinical trials, they were remarkably diverse and much better than what we have been doing for decades. We have known about a lack of representation in clinical trials for many decades. And there's been legislation around this since 1993. But now we're seeing this shift this real shift towards accountability and intention and actual investment in the innovation that's required to make the difference and continue this inclusivity. And I think importantly, getting out to the community centers, right. So when you look at, for example, cancer, uh if you take multiple myeloma it affects 20% of multiple myeloma patients in the US are African American. Now, they usually have a less severe form of disease, but they actually die earlier and that's because the diagnosis comes later and they aren't always afforded the opportunity because of, you know, inequities in the system to get the most infectious or recent medication. So when you look at how you change the clinical trial process and get um underrepresented minorities into the clinical trial process. You can't just go to the same institutions, talk to the same K O L s. You really need to expand the audience of who you're talking to in a culturally um with a health care, culturally appropriate dialogue uh to, to get them to seek care in that way. Uh We can't talk about any topic. Uh It seems these days without asking what's the effect of A I uh which has become so much more prominent in the past few months, Audie, I'll start with you. But uh what do you see happening? Uh One would suppose that a tremendous advance in technology must be good. Is it going to be two thoughts? One is, it's only as good as what goes in, right. So L's large language models are only as good as the data that they are trained on, right? We are all keenly aware of existing systemic biases. Certainly on the medical side, things like how we calculate kidney function, how we calculate heart function. Right. There are a variety of things that we think of as bread and butter. Certainly, I did as part of medical training that actually have race based adjustments to them. Um, garbage in, garbage out. Right. And so if that's what you are feeding an L L M to do, um, we, you know, it stands to reason that if we have trained it to be biased, the output will be biased. Um, And that's a, that's a solvable problem. So I don't mean to paint that as doomsday, I mean to paint that as let's all be keenly aware of what it means to make them equitable engines of innovation as opposed to perpetuators of inequities. I think the other thing I'll say is I think less so from uh well, I think this also has health activity implications around who exactly do, do A I tools sort of replace in the future of work, right? And I think generally speaking, um it tends to be the, I will say lower tendered or lower less skilled parts of the workforce. And so I think there is not just intentionality that needs to be put into how those LMS are trained, but also how they are deployed in such a way that is conscious of what that means for the future of work re skilling, upskilling. How do these models actually enhance productivity and not lead to uh employment and labor market implications that would disproportionately impact marginalized populations. I I think this is, this is critical because part of health equity and the bias there has to do with trust and has to do with historical trust within the health care system. So if we, we have to be really be careful um as we input data, garbage and garbage out to make sure that that trust is foundational because we could take a, you know, unit system and potentially um make it, you know, we need to use caution. Well, I totally agree that A I can perpetuate bias. If you're using biased data to train your models, you're gonna get biased recommendations. I think all of us understand that theoretically. But what does that mean in clinical application? I continue to see patients. I'm a medical oncologist at the University of California in San Francisco and I use risk risk scoring systems all the time, especially for patients with early stage disease. I'm trying to determine, are you at high risk for recurrence or are you at low risk? Should I give you more treatment now or should I put you on surveillance? So let's imagine, I have an African American woman with early stage disease where the model which was trained on non Hispanic white women with breast cancer tells me she's on, she has low risk and she recurs with metastatic disease. The next year I have failed her, I have failed her because I used biased data that gave me biased results that is a real harm. Let's think about the other scenario where we have a patient where we say she's high risk and I give her a lot of chemotherapy. She now has debilitating neuropathy and is on disability. She didn't need that chemotherapy again. I have failed her because I overt treated her based on biased data. So I am really concerned that if we are not, if we are more casual rather than cautious in our integration of A I in clinical practice, we can do harm. And that keeps me up at night. Uh I'm going to invite questions here in just a second, but just following up on this, uh if if we can get the bias out of the A I, I would think that it still could be a tremendous plus for equity in health care. Fair enough. I I think yes, of course, um technology can make a vast difference and we should be rapid adopters of technology. But we also need to look at the implementation of this technology which health systems in the United States are actually using these amazing technologies to deliver individualized treatment recommendations. Is it the same have and then we have the have nots. So really thinking also with an implementation lens to make sure that we have equitably distributed benefits of these technologies. But that's the same thought if we can get past the bias thing, which is gonna be a lot of work. But if we can do it then what's the issue? Well, I think that just like any other technology, there is also um non equitable, you know, resourcing of technology. So even if you think about, you know, a a medical center, a teaching center versus a community hospital, you can still get inequities of care if the same technology is not available everywhere. Um there are systemic issues that you know, the health care system in the United States is still trying to fix. For example, just having your records, you know, transfer and be visible throughout the medical system. So I think there is enormous hope here, but I think there's a lot of work to do before we get the great end state that we will be at someone who pays for it. Yeah. So like you can solve all the bias but like somebody's got to foot the bill comments, questions. They're so brilliant that there's really nothing we Yeah, I think so. Um Yes, uh a microphone will get its way to you very shortly. Yeah, there we go. Uh Please, if you could stand up, say who you are and hold the mic close to your mouth. I think, I think many folks who know me by now. I'm hi everyone. Um A general partner at X Capital. I'd love to hear a little bit more. We talked about A I but in the context of clinical trials, how you know, it's a crowded space there are a lot of companies doing, you know, trying to innovate and accelerate here. How can technology now actually change the game in a way that generations of companies have not been able to achieve earlier? Yeah, absolutely. Thanks for that question. So I am primarily focused on the oncology, therapeutic area that is the largest therapeutic area in research and development. And we know that in the United States, we see inefficiencies in recruitment, the vast majority of studies close early due to inadequate recruitment. We also see inequities, right? Um But what we also know is that only 13% of oncologists in the United States participate in research and there are a variety of pain points that are driving this and technology has a role to really activate providers to engage with them to make their lives easier so that they can see that research is an opportunity that they can implement into their actual care delivery. Yes. Yeah, I think that a lot has been tried, but the industry is really starting to see some successes and we saw that we see that in terms of a few things, one is the technology that we use, whether it be, you know, through partners or through our own organization to make sure that we are inclusive and and predictive of sites where they are, they're going to have diverse and qualified patients for clinical trials. So I think the application of using data sciences and A I to clinical trials is critically important in drug development and it's use that I have seen be most effective is expanding and to find the patient populations that we need to get into the trials. Personalization. Personalization. Yeah. Right. The ability when you've got billions and billions of records, you can be much more precise about this person. This treatment in a way that I don't think was possible before. Yeah, it's a great point. Uh, aggregating all of the data that's available has been this holy grail for a long time. We're actually apparently getting closer to it. Sound right. Yeah. Ok. That's great. Uh, our time has flown past but we're out of it now. So, uh, all I can say is to each of you. Thank you so much. Thank you. Thank you.

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