Name: Diagnosing Genetic Diseases Faster
Uploaded: 2025-05-06
Duration: 10 min 37 s
Description: Can AI help physicians accelerate the treatment of rare genetic diseases? GeneDx, a genetic testing company based in New York City, is applying AI to genomic analysis for children with autism, epilepsy, and other conditions.

Can AI help physicians accelerate the treatment of rare genetic diseases? GeneDx, a genetic testing company based in New York City, is applying AI to genomic analysis for children with autism, epilepsy, and other conditions.

Diagnosing Genetic Diseases Faster

Conferences

Mhm. Hi everyone, and thank you so much for joining me and thank you to Fortune for inviting us to be a part of this. Uh, my name is Katherine Steland and I'm president and CEO of GDX. We diagnose more children with rare diseases than anyone else in the United States, and thanks to a recent acquisition we just announced, we are going to be actually doing that around the globe. But today, I really want to talk about how AI can help us accelerate diagnosis of disease. Um, I think what's remarkable to me whenever I get a talk like this, somebody inevitably approaches me after, because the problem we're solving resonates. Usually they come up to me to say that they have a child who has unexplained symptoms and has had them for not months, but for years. They have another loved one who's struggling to get an accurate diagnosis, and they want to know how soon can they get an answer. And I'm always satisfied to be able to say, if it's a genetic disease, we can do it today. So there's a lot of reasons to be hopeful. We have the tools and the technology in order to diagnose any genetic disease right now. Um, and this is really the product of decades of work that predated me and predated the company. In 1990, the Human Genome Project was started and in 2003, the readout from that project really mapped 20,000 genes and explained why each of us are individuals. And importantly, it also helped give insight in terms of the genetic nature of what may be causing health conditions, everything from cancer to rare diseases to cardiovascular conditions. So we are the product of that. I think what was not anticipated back in 1990 and in 2003 was how AI would accelerate to a rate where we can now have such a massive impact to be able to eradicate what we call a diagnostic odyssey and be able to shift the diagnosis of disease from a reactive place to really getting ahead of symptoms manifesting. Today, if we think about the problem that we're solving. The healthcare system is failing us, and not just a few of us, it's failing many of us. Um, you'll hear me talk about rare diseases, but one of the things I want you to understand is that rare diseases are not rare. 350 million people around the world have a rare genetic disease. Uh, half of them are children. That means 1 in 10 people has a rare genetic disease. There's about 7000 of them, and in fact, last week I was at a conference and heard the latest number. It's actually more like 10,000 or 12,000 thanks to new gene disease discoveries that we're making on a weekly basis. So all of these diseases and think about them. Autism, that's considered to be one, epilepsy is another, cerebral palsy, all of these collectively are very common, and they're collectively a tremendous burden on the healthcare system. So in the United States, the burden of rare disease is about $1 trillion annually. And a significant part of that $1 trillion is the absence of knowing what's actually going on. So it's the absence of having an accurate diagnosis. Um, what's fascinating is today, if there's a child with an unexplained symptom, It takes on average 5 years. For them to get an accurate diagnosis. And during those 5 years, there's on average 16 different tests that that child is taking. None of them are a genetic test. Um, there's on average 3 misdiagnoses, not just a misdiagnosis, but then think about all of the treatment and medical interventions for those wrong diagnoses. And all of that is problematic today, and frankly it's unconscionable to me, given the fact that we can diagnose these children if the technology is used way earlier, and I believe, and I'm starting to see the benefits of this, that thanks to AI we'll be able to diagnose earlier, we'll be able to get this technology into the hands of families who need it sooner. And importantly, AI is going to be a really important part of how we take our data set, put it to work for biopharma companies, and ensure that we can get personalized treatments upon diagnosis. So our part in this, um, our, our vision is to diagnose any genetic disease as early as possible, and that's true if it's a child or if it's an adult. Um, we use two technologies today to do this. So one is whole exome sequencing, the other, the other is whole genome sequencing. In both cases we're looking at the entirety of the genome, all 20,000 genes. We are looking at the sequencing data. We're looking at additional data that we get from the clinic orders that come in about the patient, what symptoms have they had, what treatments have have they been on, and we're able to make a conclusive decision about whether or not there's an underlying genetic disease, and we provide that report. And so, the importance of this today is being able to ensure that we can maintain accuracy as we start to deploy AI in order to speed this up. Like one of the most challenging aspects of um of the industry that we're in, there's only about 1500 clinical geneticists. And so we have an entire problem to solve for that can't happen by just hiring more people. We have a limited knowledge base, and we need to be able to codify that knowledge base and ensure that their efforts are being deployed towards the highest and best use of their time. And we've been able to start utilizing some AI in order to ensure that. Um, exome and genome testing are already today, but the ability for AI to ensure that we can do this at scale is paramount to our success in helping each one of you and your families and loved ones be able to have the chance of living a healthier life moving forward. So how is AI helping us? So one, of course, Table stakes is helping us run our business more efficiently. We reached profitability last year. We want to continue to make sure that we can drive as much efficiency through the organization, but the next two is where it gets interesting and unique in terms of the world of genetics. So the ability to to scale our interpretation platform I just mentioned there's there's few genetics experts out there. We happen to employ a lot of them, but we have to be able to deploy AI to make sure that they can work more efficiently. So we just published data on a new feature called Multi-score, and Multi-score is able to read the order that's coming in. It's able to read the sequencing data. It's able to read the database that we have, which is 800,000 exons and genomes. It's able to read public databases and then come back to our geneticists to say, these are the top 5 genes that we think are causing this. Previously, and by previous, I mean about 6 months ago, all of that was done manually, and that is not scalable. So that's one example of how we're able to scale our interpretation platform. The next biggest opportunity is how do we take that data set and put it to work for biopharma companies. Today, fewer than 5% of patients have a treatment that's available to them upon diagnosis. Um, 90% of drugs in development fail. We want to be able to work with pharma companies putting our data asset to work to ensure that that 90% failure rate becomes a 90% success rate and ultimately then helps the patients have more and more treatment options available to them. So there's a lot of exciting opportunities as we think about the future of being able to really take the data that we've amassed and put it to work for each and every one of you and your families and loved ones. So I'll leave you with this, um, AI without a doubt is accelerating in its impact across every single healthcare sector. It's doing it in genomics today. We're in the very early stages, um, but there is a bigger problem at play here, and that's the fact that we need clinicians to really start ordering these tests. Um, there is an antiquated view of this that it is, it's expensive, that it takes a long time, and we've been able to drive down our costs, we've been able to drive down our turnaround times. We can now actually deliver a whole genome in 48 hours. And so what the, the, the job really becomes for each one of us is how do we become an advocate for your child? How do we become an advocate for a parent, for a grandparent, for a loved one. Um, I have many parent advocates who come to me and they are asking for access to testing. I'm always happy to be able to figure out ways to solve it, but at scale, we have to do a better job being advocates for our own healthcare. All you have to do is ask. Um, so I want to thank you. Um, I appreciate this. I, I most recently had a family member. Um, my niece's father-in-law passed away yesterday from Alzheimer's disease. So while I'm spending time talking about children with rare diseases, I just want to take a moment in his honor, um, to say we need to diagnose every disease early, and the best way to do that is to be an advocate for your loved ones. So with that, thank you.