It was the night before April Fools’ Day, 2021, when Dr. David Fajgenbaum received the text:
President Clinton read your book and would like to talk.
Despite the outpouring of praise for his bestselling memoir, Chasing My Cure – an astounding chronicle of Fajgenbaum’s five near-death experiences from Castleman disease and his successful search to find a drug to treat himself – the Penn physician wrote off the text as a joke, spam.
Then he received a phone call a few days later – from the former President’s Chief of Staff. The request was indeed valid.
Naturally Fajgenbaum immediately cleared his schedule. He settled in for an hour-long call with Clinton that wound up being transformative.
There’s no one in the entire healthcare system whose job it is to make sure that drugs are used in every way possible.
Clinton, it turned out, had a series of uncanny connections with the young doctor. Both went to Georgetown University as undergrads, and Oxford University for graduate school. Clinton was a big Georgetown football fan; Fajgenbaum had played on the team (go, Hoyas!). Clinton calls Arkansas home; University of Arkansas for Medical Sciences (UAMS) is where Fajgenbaum’s life was saved — on multiple occasions.
But the most meaningful connection Clinton felt to Fajgenbaum ran deeper: Moving throughout the world as he does, Clinton has met countless people whose diseases went uncured – and left families and communities bereft. He was fascinated by Fajgenbaum’s methodical identification of an existing drug to manage his own, Castleman disease. And he told Fajgenbaum that if he ever thought about taking that approach to a larger scale, he would have the full support of the Clinton Global Initiative (CGI).
The Clinton Global Initiative has had a staggering effect on healthcare around the world, touching the lives of 435 million people through its 4,000 projects. To have the support of CGI could unlock international awareness, and major funding.
As it turned out, Fajgenbaum and his friend and former med school classmate, Dr. Grant Mitchell, had been talking about launching such a project for years. Clinton’s offer, and his subsequent follow-up calls with Fajgenbaum over the months that followed, helped all the stars align.
And so on September 19, 2022, the Clinton Global Initiative Meeting in New York opened with a powerful presentation by Fajgenbaum, introducing the world to his new nonprofit: Every Cure, which he co-founded with Mitchell and Tracey Sikora, whose expertise lies in overseeing clinical trials.
The goal of Every Cure: to harness the world’s medical data to systematically repurpose the 3,000 approved medicines in the world to treat the 12,000 known diseases.
Here, Fajgenbaum, assistant professor at the Perelman School of Medicine at University of Pennsylvania, who’s been in remission from Castleman disease for nine years thanks to his own groundbreaking research, explains why Every Cure is needed, and what you can do to move its mission forward. This interview has been edited and condensed for clarity.
Jessica Blatt Press: Can you explain the healthcare landscape that makes an organization like Every Cure necessary? Why wouldn’t we already be repurposing existing drugs to treat other diseases when possible?
David Fajgenbaum: A drug company’s job is to get a “first use” for a drug. Basically, they have to figure out what is the disease that makes the most sense for us to go after first? That’s a tremendous amount of work, and the likelihood of getting a drug approved is actually very low. A lot more drugs are studied than ever get approved. So you have to pick this first disease, you have to put in a lot of effort, and the FDA’s job is to say yes or no.
Once that drug gets approved, that drug company now needs to start thinking about other diseases that it might be helpful in, but there’s no one responsible for making sure that it’s used in all diseases it can be helpful in. So there are circumstances where it doesn’t make [financial] sense for a pharmaceutical company to go after a disease area. If the disease population is so small and there are so few patients, it will actually cost more to do clinical trials than they can expect to make back in profit. From a dollars-and-cents perspective, if it costs more to do the clinical trials than you’re gonna make back in profit, as a company it’s hard to justify doing that.
Another factor is that in the U.S., it’s illegal to price drugs at different prices for different diseases. So let’s say your drug is approved for one disease and it costs $10,000; if you were to do clinical trials and prove that it works in other diseases where the existing alternative treatments cost $5,000, no payor [insurance company] would ever pay for your $10,000 drug if there’s a $5,000 drug that’s maybe not as good, but maybe kind of good.
“The bottom line is that companies are basically disincentivized to go after some new uses for their drugs,” says Fajgenbaum.
So you have to consider the disease area market — which I understand conceptually, though as a patient and a researcher I’m on a mission to unlock the full potential of all treatments. The bottom line is that companies are basically disincentivized to go after some new uses for their drugs.
And a third factor is that the more you study a drug, the more risk there is that side effects could be observed that are maybe specific to that disease. So let’s say you study a drug in a rare disease and you find out that the drug causes a side effect in that particular disease — that actually may cause the drug to be taken off the market for another disease where it doesn’t cause that side effect.
So for many diseases, no one knows if a drug can be useful in a new way. But there are no incentives for people to actually figure out if it can be used in a new way. And then there’s the responsibility issue: There’s no one in the entire healthcare system whose job it is to make sure that drugs are used in every way possible.
How is AI, artificial intelligence, a key factor in unlocking what you’re trying to do?
There are 3,000 approved drugs and there are about 12,000 human diseases. So there are 36 million theoretical drug-to-disease combinations. And there’s exponentially more data, tremendous amounts of data, on every single one of those possible combinations. You’re talking about dimensions and numbers that are impossible for a human to be able to even consider. And so you really do need the power of the incredible advances that have been made with AI and machine learning.
Think of it like this: Those tools that tell you what you might like on Netflix are matching a lot of information to say that, based on a lot of things, this show might be a match for you. It’s the exact same thing that we’re trying to do with drugs and diseases. We’re saying, based on all of this information about this drug and about this disease, we think this drug might be a match. And so instead of just using it for Netflix to lead us to that show, let’s use that same technology to find a drug that can save our lives or save the life of someone we love.
What you’re doing requires a tremendous amount of coordinated collaboration. Did all of the collaboration we saw come out of Covid change things for you?
Actually, the reason we created Every Cure is because after discovering a number of drugs that can be useful in new ways for Castleman disease, we launched a project called The Corona Project, to see if we could identify drugs for Covid and track which ones were working and which ones weren’t working. And the two drugs that saved the most lives during the pandemic wound up being two repurposed drugs. They’ve saved literally hundreds of thousands, millions, of lives. But as we did our research, it became so clear so quickly that there were real issues of data centralization – there had been no central databases tracking all of these drugs being used and whether they work or don’t work, and that was just for Covid, where everyone’s attention was at the time.
We said, Wait a minute, if no one was doing this for Covid and it’s so helpful and we’ve really changed the pandemic by doing this, maybe we should do this for other diseases.
And so we said, Wait a minute, if no one was doing this for Covid and it’s so helpful and we’ve really changed the pandemic by doing this, maybe we should do this for other diseases. So I think there were lessons learned, in addition to the fact that there were these amazing collaborations that were launched where companies contributed data, contributed ideas, with no expectation of a return on their investment, which we’re trying to leverage now to say, Hey, you guys built this for Covid and it was massively helpful for society – can we build something similar to it, using your data that’s gonna be again massively helpful to society?
In addition to the many connections you and former President Clinton share, what do you think it was about your approach to Every Cure that motivated him to support your team’s work so wholeheartedly?
I think it fits with the way he tries to solve problems. He describes himself as a horizontal thinker, which means that when he sees a problem he asks, What are the solutions in either similar industries or similar areas that could maybe fix this problem? And that’s exactly what repurposing is. You have a problem in front of you, and you can either dig really, really deep into that problem to try to create a new drug, or you can ask, What’s next door? What’s neighboring, nearby, that maybe we could utilize that can fix this problem? So for a lot of reasons I think it really resonated with him.
There’s often a misconception that once an organization gets a big-name funder the problem is “solved” – but that’s not the case with Every Cure, correct?
Correct. We’ve got a really, really ambitious agenda and a huge problem we’re solving. Basically drug development has really been neglecting this opportunity for decades and there’s a lot of catching up to do and a lot of lives to be saved. And as a result, this is an expensive problem to solve. So, yes, we still very much need funding both from big partners but also from individuals, even on a smaller level. Just building the engine, what we’re calling the MATRIX (ML/AI-Aided Therapeutic Repurposing In eXtended uses), which is the tool that draws all this data, costs a significant amount of money.
And then once you’ve done that, you have this tool that you can direct to any disease, any drug, to find the best drugs for diseases in perpetuity. But as you continue to add data to it, as you find these drugs that can be used in clinical trials, you now have to pay for the clinical trial. And it costs anywhere from $1 million to $5 million for every trial that you run. The more you find, the more it costs. It’s a significant amount of money to build this engine, this team, which we’re in the process of raising for right now.
Tell me about the extent to which Philadelphia has been a supportive ecosystem, or not. How has Philly rallied around you, and how could we do even more?
It all starts at Penn. This is a place where discoveries are translated into patient impact better than any other place in the world. There are places around the world that are better at making basic discoveries in other ways, and maybe others that are better at performing clinical research — but I don’t think there’s anyplace in the world that’s better at taking an early discovery and turning it into something that helps patients. And that’s really what we’re all about. It’s about taking these discoveries that are out there, that are on the internet, that are in published literature, that are in people’s brains, and taking those concepts and discoveries and helping patients directly.
In terms of other Philly support, groups like Brownstein Group and people like Marc Brownstein have helped us with early marketing to figure out what our name’s gonna be. Ajay Raju [The Citizen’s board chair] has been a great thought partner in raising awareness and helping to get us in front of the right people.
And then there are companies like Eversana, a massive data aggregating company that we are formally partnering with to utilize their data to help patients. Companies like [research analytics firm] Elsevier, which we’re hoping to formalize a partnership with – these companies have massive footprints in the Philadelphia region. And of course there are big pharmaceutical companies in the area that we’re engaging with.
We want this to be about centralizing the world’s knowledge on how drugs can be used in new ways. In order to do that, it can’t just be what’s in the published literature, medical journals; it can’t just be what is within a pharmaceutical company, within a company that maybe isn’t public. It can’t just be work done at labs at Penn and other places. It’s gotta be everything.
So really it’s a three-pronged part: bringing together centralized, publicly available data that anyone can access; establishing partnerships with companies, pharmaceutical companies in particular, to understand what do they know about these drugs that is maybe not publicly available, that they’re willing to share so that society can benefit; and then it’s also working with companies like Elsevier and Eversana who already have access to these amazing data sources.
And so we’ve got people in the Philadelphia region who are helping in each of those areas and we’re hopeful to also establish a partnership with Independence Blue Cross. They’ve been helpful for us as we’ve thought about the model a little bit further.
You have juggled so much since your diagnosis of Castleman disease: You’ve written two books; overseen the expansion of AMF, the nonprofit you launched on college campuses to create networks of support for grieving students (named for your beloved late mother’s initials and the idea of “Always Moving Forward”); founded Castleman Disease Collaborative Network (CDCN), which just celebrated 10 years; gotten married, had two kids…how are you balancing it all while minding your health?
Yeah, it’s been busier lately than it’s ever been because we’ve got the CDCN that’s driving forward Castleman’s work on a global scale; we’ve got my Center for Cytokine Storm Treatment & Laboratory at Penn, CSTL, which we call “The Castle,” that conducts Castleman’s research and also related diseases; and then now we have Every Cure, which of course is independent from Penn and its own separate nonprofit organization, but thinking about driving forward repurposing across all diseases. And then from the personal level I’ve got two sweet little children, and my incredible wife, Caitlin.
There’s more than ever, but I also have better and stronger leadership than ever in terms of the various divisions and everything that’s going on. So that enables me to feel comfortable focusing on the really big-picture stuff, and making sure that I’m maximizing time with my family and kids.
My mom, who died of brain cancer when I was in college, she was busier than ever doing things when some would say she didn’t have to do those things – the volunteer work that she did all the time, she felt it was her responsibility to do it, and she loved it. And that’s the feeling that I have right now. We’re doing more than we thought was possible. But we’re making a bigger impact than I think we ever could’ve dreamed of – and we’re loving it.
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Photo courtesy of Every Cure