Ram Yalamanchili: Hi, Dr. Chen. Welcome.

Dr. Chin Yee: Thank you for having me Ram. Always a pleasure to meet up and have a great

Ram Yalamanchili: discussion. Yeah, absolutely. Looking forward to talking to you. Um, so to start off, I'd love to get a quick introduction, uh, about you and what you're doing with, uh, um, the program, uh, with. Well,

Dr. Chin Yee: as you mentioned, I'm David Chin Yee.

I am the research director at Georgia Retina. Um, we are a private practice retina group that somewhat recently have been acquired a part of private equity. So our, um, organization is called ISO Partners and I'm specifically in charge of our site at Georgia Retina. We've been around for over 25 years.

You know, within the practice we have over 25 retina specialists. Um, we've had a robust clinical trial, um, team for quite. Some time, quite frankly. Um, we've been involved in all the pivotal studies that has gotten many of our current, um, treatment available that we're currently using. And more recently, over the past, uh, year and a half, I've now research director.

And the reason for that, quite frankly, is we've had a large turnover. Some of my, um, more senior partners have decided to maybe take a slower pacing regards to the clinical trials department, and I was very eager to get involved. As I see so many opportunities and treatment modalities coming to our field, and it was intriguing to me to get more involved.

And so I've now spearheaded, um, the challenges, but also hopefully the, the fruition of being able to provide access to our patients, to some of these new treatment modalities that are coming to our field.

Ram Yalamanchili: Absolutely. And if I'm not wrong, uh, your practice is one of the largest practices in Georgia. Is that correct?

Not only in Georgia. Probably in the southeast at this. Yeah. And, um, um, you know, just, just a quick introduction on my end. I think, uh, uh, you know, we've met through a, uh, common connection, if I'm not wrong, through, um, through another retina physician. And what was interesting when, when I, uh, first saw your practice is that just the volume share volume of patients you're seeing on a regular basis.

And also I would say you are forward thinking in terms of adopting new technology or new, new ways of essentially managing your research program. So I think it'll be great to have, um, you share more thoughts about that. And, uh, you know, really looking forward to this discussion, right? I think we've had really strong discussions around this topic.

Uh, you're, you're clearly passionate, you're interested in, um, uh, in the, uh, sort of like the next generation of how things should be, uh, or things will be in research. So let's get started. I, um, um, I think to begin with, uh, let's talk about some challenges at the site level, right? Uh, you know, you've, you've, you've, uh, like you said, you've had a, uh, a, a robust pipeline.

You had some staff turnover. Uh, uh, you know, you're, uh, you're managing a fairly large, uh, program as well. Uh, so yeah. Tell us a little bit more about your sort of challenges which you are seeing or have seen. Uh.

Dr. Chin Yee: Yeah. You know, as I said, starting off with turnover, right? So whenever we need replacement, you know, getting staff up to speed and having all the holes filled in different areas can be somewhat challenging, right?

Just having, if you're already a part of a clinical trial, having someone else filling on get up to speed on those roles can be, can take some time. Um, unfortunately, you know, you may have someone that has the experience in ophthalmology, right? You know, the terminology and ningo, but they may not.

Understand the regulation and the documentation that is required to process a clinical trial. And on the reverse, you may have someone who's well versed on clinical trials, right? They know, you know the documentation, what is involved, how to consent, but they don't understand the language of ophthalmology.

Right? What does it mean for an OCT? You know, we are somewhat unique in that the field itself, the language, it's like learning a new language, being able to get up to speed on the terminology, the technology in. That we're using for clinical trials is not, um, is unique to our field. And finding that symbiotic balance where someone has clinical trial experience as well as ophthalmology experience, I gotta tell you, it's, it's very rare now.

We primarily will take someone, you know, from our. Site as a technician, um, who has already had experience, but again, getting them somewhat up to speed, getting the certification. And it's not just taking a a picture, but it's, you know, set standard in terms of the quality of picture. It's not just checking vision, right?

There are specific standards and how do you get good visual acuity testing that's performed. And so, um, the biggest hurdles that we've had is one. Getting up to speed, getting to staff, training up to speed, knowing how to document data entry and being able to make sure we're not having any missteps or anything missed so that we don't have any protocol deviations.

And so, um, those have been some of the, the, the largest ha hurdle and challenges. And so for me, you know, finding systems in place that can kind of help narrow that gap and get us up to speed a little bit quicker is extremely important and helpful. Right. Whether it's a training protocol. You know, a booklet for, for our staff to be able to get up to speed, you know, things that can help them get to where we need to move forward as quickly as possible.

You know, I didn't mention earlier before, but as you said, we are a large, you know, site. We have over 15 office locations and primarily right now we only have one study side. But one of the reasons for me stepping in is again, also expanding, right? Wanting to have another study side on the south side of Atlanta and be able to.

Have more studies involved and therefore we need systems to be a little bit more efficient.

Ram Yalamanchili: Yeah, absolutely. In fact, you touched on quite a few points here. Uh, maybe let's start with the staff, uh, training or onboarding aspect of it. So you mentioned something interesting, which is I think your preferred router, at least the path you've taken, is, uh, bring on technicians who have some experience clinically and then training them to help you on the research side.

Um, what's your experience been in that regard? Like, you know, have you noticed things which went well versus didn't go well? Uh, anything you could share in that process?

Dr. Chin Yee: Yeah. You know, I think you need to find someone that is on the same wavelength, um, or same passion, right? They have to understand the importance of clinical trials.

Why are we doing. Right. They have to have the same vision and mindset that I have, which may be including the involvement of technology things to way be able to get us, you know, more up to speed to the future. Um, so it's again, identifying individuals, not just with the capability, but an open mindset that's super important to me.

And also having good communication skills. Part of what we're doing is not only communicating with patients, but you know, con communicating with sponsors, CROs, and so that. Those are the things I want to highlight that if I ask or doing an interview with one of, uh, my technicians is making sure that they understand those are things that are super important and is identifying the right person to be able to fill those roles and needs.

Um, unfortunately the reality again though is, you know, if you're in a smaller organization, you may not be having a whole abundance of individuals that are applying for this role, and so you may not have that, um. Flexibility to have that ideal candidate. And so you may have to, so that's where some of the pitfalls I may say that I found where I find that I want someone with great communication and an open mind, but I may find someone with open mind, but maybe not great communication or vice versa.

And so kind of have to guide them to get them up to speed.

Ram Yalamanchili: Yeah. Um, can you tell us a little bit more about the, uh, turnover issue, which, uh, you, you brought up? Uh, what do you think contributes to that? Because I, I hear this pretty often, right? Not just in your case, but uh. I've heard this in many other, um, you know, sites we work with.

I think it commonly comes down to also, uh, use of the word burden, uh, or some sort of burnout. Mm-hmm. What are your thoughts on it? Like Yeah, how do you

Dr. Chin Yee: look at it? I, I definitely think that's a big part, right? You know, the amount of workload stress that comes with in it. But again, I think what you find is in life, everything is supply and demand.

There's no question. There's a larger demand for ophthalmology clinical, um, research coordinators, research assistants, and we don't have as many, you know, the supply is not there. We don't have A-A-A-A-A-A school or a system set up in place to get individuals set up to be able to. Meet the, the demands that we have.

So we have, uh, limited supply, a large demand, and then when you have that rare bird, as I mentioned, right, ophthalmology experience and clinical trial experience, they're getting snagged by maybe some of, you know, the, the, the, the CROs, right? Uh, whereas they're looking for bigger, better opportunities, maybe less stress, better pay, and so.

You tie all those, um, that put yourself in that environment, and I think that's why we're facing the high turnover. But something that you did mention as well is Yes, the burden and the, the, the, the time to be able to get successful within the system, it takes long, right? There's so much inefficiency within doing, um, studies in clinical trials that to get from point A to point B.

There are lots of loops and hurdles. There are lots of challenges that are faced on a daily basis, and all too often I go in and I see the staff are maybe not as enthusiastic as I would like them to be because they're overwhelmed and burdened. We, whether it's, you know, communicating to a, to a, that, you know, a sponsor, CRO on a day-to-day basis, trying to get back to patients in terms of answering questions that they may have in terms of wanting to get into a clinical trial.

And so. The manpower to be able to fulfill all the needs and tasks at this point is somewhat limited.

Ram Yalamanchili: Yeah, no, absolutely. And what I find fascinating is, you know, as you, as one of my own personal, um, route has been, came from a technology background and, uh, you know, went into a biotech startup with a couple of physician founders.

And, uh, you know, we had an exit of that, uh, startup. And, uh, then I essentially came into the research side of things from a site perspective because I, I have seen the sponsor perspective of what clinical research looks like. And it's interesting because everything you've set in terms of the burden, the inefficiency, it's the exact same conversations you would have from a biotech perspective.

So it's not that, you know, one end is efficient and the other is inefficient. It's literally the whole spectrum is inefficient, right? The whole, the whole ecosystem is inefficient.

Mm-hmm.

Ram Yalamanchili: So, uh, and I certainly saw this when I, uh, started Tilda it, it was one of our first thing was, let's go really like, see how a operating site business looks like.

And that was one of the first things we did. We actually went and started our own site. I started coordinating in the site for a handful of days a week, uh, while building this business. And, uh, really, you know, from a product perspective and, you know, just in terms of where our focus is today, how to bring technology, how to bring, uh, AI into this whole industry, I, I really feel, uh, the coordinator role is an unsung hero type of a role.

Uh, you know, they can make or break the entire program, uh, at a site. And frankly, there's quite a bit of risk also involved if, if you don't have the right people and the right oversight. And that could be financial, that could be regulatory. There's many different types of, um, you know, downsides out here.

Right? So, um, yeah, like we'd love to sort of, let's explore this a bit further on these topics, right? So I think what I'll first start off with is, you know, you are using our platform and our AI team Mets in your clinic, and maybe the first thing I'd ask you is what, what got you interested in even exploring something like.

An ai, uh, you know, teammate or an assistant or whatever you wanna call it, from your perspective, right. How, how did that come to you from, from just an evaluation perspective?

Dr. Chin Yee: Well, you know, as we've mentioned before, you know, in our prior discussions, one, I do think and know AI is the future. It's already here.

And so I have a strong belief in artificial intelligence and where it can take us in terms of improving efficiency. For me, I thought that would be one of the easiest ways to cut back on some of the inefficient inefficiencies that we're already facing and some of the challenges. Um, and again, that could be in regards to training, getting staff up to speed, that could be in regards to getting data entry points, um, removing redundancy, you know, helping to make.

And create less errors so you don't have to go back and repeat it. Wasting time. Right. Um, maybe simplifying a process, right? You have a problem. Or, um, a, a developing a guidance or a workflow system, which is some of the things that you guys have done extremely well. And so I think I envisioned the idea that this was important and needed, but that I didn't have the capability and the bandwidth to actually create this for ourselves.

And so the, the knowing one that this. Identifying the problem which we cannot discuss, and having an idea that, well, there are things already that are out there that could help to get us up to speed, maybe help to make us, um, more productive, more efficient, and searching out and seeing what would be the best fit for partnership with our department was very important.

Increment, you know, incremental. Um,

Ram Yalamanchili: one question I have, which brought up is on the data side, right? So. I kind of look at data and quality as sort of like two sides of the coin. You know, they both go hand in hand and, um, you know, frequently, you know, if you kind of look at the other side of the ecosystem, the whole mechanism of how CROs are set up, how the industry is set up is really like quality focused, right?

Mean you have monitoring, you have CRAs who are traveling, coming to your site. I always believe that if you don't have great quality at your end no, which is basically at your site level, then you're, you're moving up this like quality burden, you know, through the stack right up, up into the CRO level and then ultimately the sponsor level.

So. Tackling quality in a, in a way where you can, you can do it in a much more streamlined way, maybe at a more predictive way, I think has great benefits for the overall industry. I mean, not just at the site level, but I think, you know, we as a humanity would probably benefit quite a bit by, you know, building these kind of systems and making them more ubiquitous.

And of course from an AI perspective, that is the most efficient way to do it. Um, right. Like, like you said, there's not enough supply of great, talented individuals who can manage this at scale. And one thing I do see is we probably should be at a place where we're. We're managing 10 times the volume of trials we have today.

I mean, uh, maybe you can tell me a bit more about this, right? But, but is there opportunity where you can see there's enough disease criteria or there is enough patients in your own practice where you see that, hey, there should be more for these patients and we just don't have it because of many, many reasons, right?

Maybe there's not enough trial volume, maybe there's not enough.

Accelerating at this point, discovery accelerating. So the bandwidth on. Has to be a place where we have to innovate and we have to move forward faster. Um, because that's really important. Right. I'd love to get your thoughts from a clinician perspective, like how, how, how do you see that, like evolving in the next five, 10 years?

You know, just, yeah. You

Dr. Chin Yee: know, I think you hit the nail on the head. One of the bottlenecks, right, is the, the, the ability to get the study patients, you know, yes. Identifying the patient's recruitment, but then processing and getting them through the. The, the actual study protocol, getting the treatment and then the continued follow up.

And if you don't have an efficient system, having that patient come through or the the individuals, um, coming through, um, can slow things down, that's your rate limiting step, right? And so, yes, having these processes kind of somewhat streamlined, and as you mentioned, having good quality data, it's one thing you don't, you know, it.

Poor data in you get poor data and informational, which is not gonna be beneficial for the patients ultimately, which is the end game, right? We want to be able to see how effective and how relevant or non-inferior or whatever your marker is that you're trying to achieve. Um, you want to get good quality data and information.

And besides the point, again, remember if you're not doing. What's the point if you're not doing high quality, um, work because then you put yourself at risk of getting into to problems and, and trouble in, in terms of, from a regulatory standpoint, right? So again, you definitely want to avoid any of those hurdles or pitfalls if possible.

Um, but as you said, I think one of the largest bottlenecks that I'm seeing, um, we already talked about the supply and demand, but again, tie that into the fact that. The churn of being able to get these patients through the study protocol can be a lot more time consuming and burdensome. And if there are systems and ways, which we know they are, right, it's implementing it, um, in the current ecosystem we have, right?

We're not trying to reinvent the wheel. We already have somewhat systems in place. I can't tell you the systems are the greatest, but. We already have systems in place and it's to work within that system and find out how can we become more efficient? How can we minimize that? Curve or that stepladder and flatten it to get us to that processes a little bit faster and sooner, and thereby allowing us to one, have more patients, um, included in this, in in studies.

And then also lower the barrier or entry level for me, for example, wanting to start a new site. Again, if the system is in place, it's a little bit easier to streamline. I can then open up other sites or even other. Um, practices can start to inherit other, um, clinical trial sites and a bit easier, right? So lowering that barrier or burden to enter into the system in place, and again, we, you talk about that not only in clinical trials, but you hear it.

What is the benefit of artificial intelligence from a day-to-day perspective? I think small business owners, small practices, right? Allowing them to be able to be as efficient or get to where we potentially are with lower entry points.

Ram Yalamanchili: Yeah. And you know, touching on two points there, right? One is the administrative burden.

I think we're all so used to in this industry, in the clinical research industry to manage, I would say on a ratio basis, a fairly large administrative burden to productive burden. Um. And productive is more like, you know, you're seeing the patients, you're managing the, the actual day-to-day with the patient, that sort of a thing.

But it's not uncommon for us to go and talk to coordinators and they say, well, I spent all of my Monday on administrative day, right? I only filed papers, I only entered data or enter, you know, caught up on my queries or I've got a monitoring visit coming in, I've got, you know, something else coming in.

It's sort of like become normalized, which I find really interesting because, you know, it shouldn't be the way it is, right? Like I think, uh, the industry should have been the other way, which is let me try to do everything possible to reduce the burden. Mm-hmm. And I want to give you as much time as possible so that you can actually spend it on, you know, either working with the patients, providing that, uh, you patient clinical, uh, clinician interaction, um, or recruitment.

You know, these are all areas where you can meaningfully improve bandwidth of a clinical study. But just having these additional burden of, uh, you know, I'm, I'm just seeing like even from, you know, where we, where we were, uh, when we first started working together. Uh, same team, set of team members were managing multiple studies, tens of studies, um, you know, regulatory quality, data management, uh, finance, um, you know, and it's all intertwined, right?

Your finance cannot be accurate without great quality. And your quality cannot be great without good, you know, workflow management, data management. Mm-hmm. Uh, regulatory. So it's very closely intertwined. And um, you know, like you said, if you don't have the right people or if you had a turnover or, or a burnout, you, you sort of very quickly run into these issues where things start to like unravel and like you.

Um, concern is, you know, are you then running a quality research program or are you then spending time catching up on all the things which you've probably had to from the past? Right. Um, and one thing I've noticed, which, um, maybe I'd love to hear your perspective, is I've heard something like 95% of the sites bill under the, the amount of work they perform.

So you budget quite of invoice structured. Uh, you know, your negotiation is dependent on how you bill for it, how you bill for the, the work you've done. And unfortunately, the systems that are not mature enough today, uh, you know, to, to capture the sort of financial intelligence and place it in a, in a form where you can actually accurately capture all the value of delivered to your partner.

Tell me a bit more about that. I mean, I think, I think you've, you've gone through quite a bit of that experience, so I'd love to hear your, your own, um, uh, story on this, right.

Dr. Chin Yee: I think first off, just to, to kinda reinforce what you said before, I think as you said, each staff member, they have too many hats to fill.

Right. So they have too many different functions, and so it makes it a little bit difficult to focus on one thing or the other. And so then you try to prioritize. And when you prioritize, some things get left in the wind. And one of that, one of those areas, unfortunately, is this billing part. And the biggest reason for that, I think, is, well, again, the most important thing that, that the coordinator is focusing on is the patient care, making sure that the data is intact so you don't have any regulatory issues, um, that you're not making any mistakes.

So then what falls to the wayside potentially is this reimbursement or the financial perspective. Not only that, but a lot of times billing and, and how do you invoice for each, um, study could be completely different. So it's not streamlined at all, which to me just, I mean, it seems kind of ridiculous, but it is what it is.

Um, and so you know, the system, you know, the game that's played and then unfortunately. You know, invoices, invoicing, takes a backseat to some of the other things that are prioritized, and so that's why things don't get invoiced and billed because it's not a priority, unfortunately. Right. We don't have, unless you have a staff member or someone that's focused on that, and if you're just starting up, I gotta be honest with you, you're not putting so much.

The reality is you probably should because to be able to continue to grow, you need to have the, the, the income coming in. 'cause that's a major part and reason why we're doing clinical trials. Yes, it's to help the patients provide new technology and, you know, capabilities and, but it also is a financial benefit from a, a group and a study standpoint.

And, and so therefore it is important if you're not collecting and you're not invoicing, you're running into problems. And so. We found when someone left that they didn't have the, the backlog information to be able to then invoice correctly. And so if, if you don't have a good system to be able to track, make it more automated and also be able to check and reinforce that you're getting the actual payment because when you get the payment.

As I'm sure you're aware, a lot of times you get a lump sum payment and you have no idea what this payment is for, right? It's not itemized to say, all right, this is for this invoice. This is for this invoice. It's a lump sum, and then you have to sit there on the backend to try to reconcile that. So it's kind of like you need another account or an auditor to basically implement this system in place.

And so again, all these um. Identifying the issues, but then therefore, that's why you're not getting the, the, the, yes, the budgets are large, but how much, as I think you mentioned, only 95%, um, is being invoiced. And then again, let's be honest, the CROs, they don't mind if we don't send an invoice and they don't wanna pay.

Right? So you set yourself up for an environment, right, where you're gonna get underpaid. You have under billing. And we need to do a better job at that. And that's one thing that we want and are happy to kind of partner with you, to be able to have those checks and balances in places, right? Those reminders, those kind of reconciliation to kind of say, Hey, we did get reimbursed or get paid for this invoice.

And you know, removing that added. Task or hat, so to speak, on a coordinator, frees them up to do and focus on more important things that they find, uh, a priority in the first place.

Ram Yalamanchili: Yeah, no, it, it's such an important aspect, right? And, you know, just my view about this has always been, I mean, you touched on many great points.

It, it's the idea that we have to work within the ecosystem we have where, uh, you can bring value to the. The research program on an immediate basis. And our view just has been that, you know, let's not do this by adding even more layers of software, like, you know, things like this, right? Which is very typical for most technology companies.

They come in, they say, here's a new software, which, which will basically change everything, you know, uh, for you. But then you're adding one more system in addition to the 20 others, which the coordinator or you might be already dealing with. Systems has been, we're a. Essentially an AI driven service. We help you off burden or take away some of those hats you just mentioned, and we give you a much more streamlined process because we have trained and we have, uh, automated away quite a few of these workflows, which would otherwise be manual, uh, in your case.

And the benefit of doing something like this, using today's cutting edge AI is that you get much higher quality, reliability and consistency across whatever that. So whether it is data management, whether it is, uh, you know, our ai, helping you take your source data and then enter it into your EDC, for example, and you might have 20 different studies and we can do it across all 20 using the same exact systems your sponsors have, uh, provided.

Same thing with regulatory, right? You might have. Or hundreds of documents you're managing on a regular basis. And I find it, um, you know, just so much easier to train an AI teammate to basically say, okay, I can take these documentations. I already know what Dr. Chin practice looks like. I already know exactly where, what, what, uh, what address you're at or what's your past, uh, study histories been like or what, what type of equipment you have.

There's a lot of things you can do from all this information from an AI team member who can say, okay, I'm just gonna prepare all these documents and give it to you for review. As long as you sign off, we're good. Right? We're going from there. Uh, and I think this sort of a augmentation of ai, I feel is a, is gonna be a big part of our future.

Uh, it's already here and it'll accelerate, right? This is where the world is going. Um, and I think you and I spoke about not just on the research side, this is probably going to be the case even on the clinical side. Um, yeah. So just from a. Experience perspective, like do you see this sort of a thing accelerating?

Like have you seen things outside of, you know, our relationship working with, uh, Tilda Right. But, you know, any other areas where you're excited about? Um, maybe just for the general field?

Dr. Chin Yee: Yeah. I think, um, you know, just within the clinic, whether it be for scribing and charting for a patient, um, encounter.

Right. Being able to patient comes in with a diagnosis and then usually it can kind of help, it's smart enough or intelligent enough to identify what are some expectations that you would expect undocumentation with a patient with say diabetic retinopathy or a patient with macular degeneration. Um, so, you know, assisting be scribe and documentation for that encounter visit is going to be tremendous.

In addition to that, in terms of AI technology for imaging, um, diagnostic evaluation, um, you know, we have treatment options for geographic atrophy. But one of the challenges that we have to date is being able to assess how well are these medications are doing for our patients. And I think that we're developing, you know, artificial intelligence, imaging modalities that kind of further assess the potential.

Impact that these medications are having for us that will do a better job than I may on a routine basis, right? To better potentially predict the outcome for these patients. We also see this in home monitoring. We have the home OCT that uses an AI based algorithm to kind of help us to have better monitoring and control on how well our patients are doing well.

We're not seeing them within the office, right? These are technology they can use at home, and that algorithm uses AI to basically determine is this a reason to be? Worried or concerned for the patient and therefore alert the, um, doctor to say, Hey, we need to come in and, um, have treatment a little bit more frequently or sooner.

So all these different tools that are coming is, is definitely here and super important. I think one thing that's important to, to note to differentiate your system as well, it's not only a AI based platform, but you have staff and experienced individuals such as yourself, right? That also provide input.

To be able to help streamline and get things further up to speed. So I, I think it's also important to, and I, I found that extremely helpful, that it's not just a, you know, a software system and platform, but it's a partnership with your team that also bring along experience within, uh, clinical research and also ophthalmology.

Ram Yalamanchili: Yeah, absolutely. I think, uh, that's really key, right? I think having a strong partnership driving value for, for you and your program. I mean, that's, that's really, uh, you know, critical and, and non, non-negotiable really. , another question I have is, you know, I think most, like, like you are seeing, we're, we're all grappling with this new reality that AI is gonna be a big part for life. Uh, great things are coming and they're coming on a regular basis.

How do we get started? Where, where do you think that starting point will be and what is, what are the right environment or the variables which you have to consider before saying you.

Dr. Chin Yee: I think what I've come to find is you can sit there and analyze and take so much time before pulling the trigger and doing something right, which is, I think, one of the biggest challenges and burden in life. We're talking about just, you know, getting up and saying you start the New Year's, you wanna start exercising, right?

You, you kind of go through the research, what exercise program, what diet? The best thing to do is to get up and do something. And so I would tell people, or anyone reach out and communicate with someone like yourself or any of these, um, AI platforms and see which one may work best for you. Right? Um, the first step is making the action and actually reaching out and seeing what are the next steps to implement.

You know, from my experience working with you, it's quite actually easy, right? You kind of develop a, a framework. What are your needs? You know what. Parts of the system would help, you know, my department to achieve the metrics that I'm looking to achieve, right? So it's having a clear idea of what your goals and your your plans are, and then being able to identify what tools may be available currently or systems that can be in place to be able to help.

To implement in our current setup or even changing, right? Being open-minded to know that maybe what you were doing before, what systems were in place before, some of that may need to be changed to become better equipped at providing you where you would like to end up going. And so that's what I think is gonna be the most important thing, is again, realizing that this is available, realizing that you can implement it today, tomorrow, or even next week, right?

Don't delay. Um, learn, reach out and see what would be the best system for you.

Ram Yalamanchili: That's, that's well said. Um, I, I, I would ask you when you said metrics or where you want to go, I know we touched upon this in various, uh, forms, uh, today, but can you maybe describe where, where would you like to take this program?

Dr. Chin Yee: Yeah. You know, my aspirations, you know, I'd love to tell you, um, I wanna take us to the number one clinical trial site where, I mean, to be honest, that is my goal where any study that's coming on board that I also find meaningful, right?

That we are sought out as. A place to be considered of quality and also of high recruitment that provides opportunity for our patients to be able to have access to cutting edge technology and treatment modalities. Um, I want us to again, be revealed or, you know, consider being considered one of the top sites, um, in terms of data.

Quality and communication to be able to continue to keep us at the forefront of clinical trials. I love nothing more than when a new medication, new treatment, new imaging modality comes to play. And top of mind is Georgia Retina was a part. Of that foundation to be able to get access to our patients and let individuals be aware that hey, we were apart from the beginning.

We saw that, we saw the impact that it could, you know, could make on our patients. And we were involved to make it, you know, the pivotal and incremental steps to be able to get access to a whole host of society, not only in Georgia, but across the United States. So that's where I see us.

Ram Yalamanchili: Yeah. And, and I think you'll get there at the pace we're going.

I think it'll be great. Okay. Wonderful. Um, no, that's, that's, uh, I think really helpful. Thanks for your time Dr. Jeanne. Cool. Uh, talk to you always as usual.