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SriniVas R. Sadda, MD, discusses being president-elect of ARVO, as well as AI research being conducted at Doheny Eye Institute.
Editor's note - This transcript has been edited for clarity.
I'm David Hutton of Ophthalmology Times. At its annual meeting earlier this year, the Association for Research in Vision and Ophthalmology, named Dr. SriniVas Sadda, president-elect of the organization. He joins us today to discuss his term, as well as his research work at the Doheny Eye Institute. Thanks for joining us. When you begin your term as president at the end of the 2024 annual meeting, what will you focus on?
Well, thanks very much, David, it's been a great honor for me to be able to be selected and trusted by ARVO in the membership and this role. I've been attending ARVO board meetings since 1992. So I'm really a veteran of ARVO.
Really, you know, my role in terms of president is really to facilitate the great work of the tremendous team that we have the entire board of trustees, and the staff at ARVO who do a tremendous job of not only organizing our meeting, but all of the other activities that ARVO supports.
I mean, ARVO was really established to try to bring together scientists worldwide, who are engaged in vision science research to really further advance the field and really provide that collaborative environment. So really, my role as president, it's really, you know, what can I do to facilitate that. To encourage our membership, grow our membership.
Again, one of my responsibilities as president will be to establish the theme for the next meeting, in terms of what we'd like to highlight, as some of the hot topics or the hot areas in vision science research. And so, you know, I look forward to that. I think that we're very proud at ARVO of being a very diverse organization. That's also a focus. I think going forward is continuing to develop our international presence and the diversity of the organization, and I look forward to sort of really focusing on those types of efforts during my term as ARVO president.
What can the work you do in this role mean for ophthalmologists?
Well, I think that my role is specifically small, relative to the importance of ARVO, I think, as a forum for exchange. And I think that there are really few opportunities like this, where you can bring together the best in the world.
But it's not even just necessarily the best in the world. It's also all of the young people who really, I think, are the life force for the future of ophthalmology. They have an opportunity to come to this meeting, and to interact with people who are real leaders, or experienced individuals in the field.
I view my role, David really as more of a facilitator. And again, I don't do this in a vacuum at all, obviously, it's entirely dependent on our board and our staff. But really, I view my role as more setting the tone, and facilitating that. But again, really enabling what the next generation can do, I think is is a big point of focus that we're able to achieve by bringing everyone together at a meeting like ARVO.
How will you measure success of your tenure?
Oh, well I think that a big part of what we do is the annual meeting. And I think one aspect will be the attendance at that meeting. Where people are coming from, because as I said, we really view ourselves as an international organization.
And also, what we're doing in terms of promoting people, our focus on diversity and equity. And seeing that they're more diverse representation of individuals at leadership levels within the organization, on the podium, receiving awards. I think those are important metrics to measure what I would look at as success for my year in office.
Shifting gears, let's talk a little bit about your latest AI research at the Doheny Eye Institute. Tell us a little bit about what you're working on.
So yeah, so we're engaged in many different areas of AI. And it's actually interesting, I'm glad you asked this, because there's a lot of fear about AI I think. The latest in the press is how AI is going to destroy the world and the like. And there's no question that we have to have regulations and safeguards to make sure that we don't take missteps.
So I think that's the case. But in terms of what we're doing, our focus is really on how we can assist in better diagnosis and management of patients. And so we've had a long history of AI. We've had a long history of NIH sponsored collaborations, for example, even with industry partners. One of the diabetic retinopathy screening softwares, the second one ever approved by the FDA from Eyenuk, the EyeArt system was something that we helped to train with our grading team at that Doheny. But we do we have a big program internally, in AI development.
A lot of it is currently focused in AMD and identifying biomarkers that can help us identify patients who are at risk for progressing or who may benefit from treatment. And, David, as you know, recently, we've had approval of a therapy for treatment of geographic atrophy, which is an advanced form of dry macular degeneration. And so, you know, how do you best find patients who would benefit from that treatment, who may be at greatest risk for for regressing? That's where I think AI can play a big role, in really helping us identify these patients who may not be coming into our ophthalmology practices, by having these tools out there and other vision care providers.
And then actually be able to track them precisely, identify who is getting worse more rapidly. That might be the ideal candidates for treatment. And so one of the buzzwords I think we'll all get used to in the future is the fact that we're entering this era of personalized medicine. Which means that you know, rather than think about just, while this treatment is approved, just use it willy-nilly on all patients with the disease. We sort of figure out; No, well, this treatment may work best for this patient at this time. And that's what I think, AI has a great potential to facilitate that, and that's really the area of focus for us in terms of our research.
What can this mean for ophthalmologists and the patients they treat?
Well, I think our patients will benefit from having this sort of more individualized type treatment plans. I think that's something we can expect in the future. There are a lot of pressures on us as ophthalmologists, as reimbursements decline. And we feel a challenge to see more patients, but also there are many more patients to be seen as our population ages.
And that means that there are certain things that we have to be able to do more rapidly. And this is where I think AI has a real opportunity to potentially streamline some of the activities of our practice. And you know, the implementation – I mean, our focus has been on image analysis, but there are many other implementations of AI [like] potentially helping us with documentation, and things of that sort, which currently occupy a lot of our time. And I think as physicians, we'd like to spend more of our time really interacting with patients, and less of sort of the busy work. And I anticipate that AI could play a role in our future clinical practices in streamlining some aspects of our practice so we can spend more time actually caring for patients.
Where would you like to go next with your research?
Well, I think that one of our first experiences [we] had, we actually took something we were involved in the development in and saw it through with the help of obviously a company. Eyenuk was the company that actually brought this forward. But the point is that I think as physician-scientists doing research, we'd like our research to actually translate to make a difference for patients. So really, I think that where we'd like to go is – yes, we're building a lot of different AI tools, a lot of AI tools related to AMD biomarkers, as I mentioned, but then how do you actually get them to patients to actually make a difference. And that's one of the challenges in AI.
A big unknown is ultimately there has to be a commercial, there has to be commercial viability, there has to be an opportunity for if there's a company or someone to bring the bring a product to market, they have to find a way to to make money sustainable. And those are still open questions in AI. So we'd really like to figure out what I would consider to be the end problem, which is really how do you take the technologies, get them approved by regulatory bodies in an efficient manner that we could afford to do and in terms of the studies, and then actually get it out to patients. So that's really going to be a point of focus for us going forward.
Lastly, if you could dust off the crystal ball, where would you see AI in ophthalmology in the next, say, 3 to 5 years?
I think we're going to have more tools. I think one of the next applications that we'll see rollout will be home diagnostics, such as home OCT. And and I think that's going to be powered by AI. So I think we're gonna see more and more. Because we have more and more patients to take care of, and we really want to make sure that our time and our clinics are spent focused on patients who would most benefit from our time and our care.
You can imagine if some level of screening could occur at a patient's home, they could use an app or some device, maybe take a picture of their eye with their smartphone, and then have AI provide some initial analysis and say, "Yeah, this looks totally fine. You don't need to go see your eye doctor," or "No, wait a minute. There's something going on here. See your eye doctor." I think that that is something that I think is going to have an impact on our practices. So it's figuring out how we manage our practices, incorporating AI tools, and these sort of like this new sort of era of home diagnostics I think is going to be something that's going to happen. I think it's going to be a big part of ophthalmology practice and it remains to be seen exactly how smoothly we implement these new tools.