Ram Yalamanchili (00:04.568)

Hi, Dr. Chin Yee. Welcome.

David Chin Yee (00:07.29)

Thank you for having me Ram. Always a pleasure to meet up and have a great discussion.

Ram Yalamanchili (00:12.034)

Yeah, absolutely. Looking forward to talking to you. So to start off, I'd love to get a quick introduction about you and what you're doing with your program, with your practice. I'd love to hear little bit more about that.

David Chin Yee (00:27.222)

Well, as you mentioned, I'm David Chigny. I am the research director at Georgia Retina. We are a private practice retina group that somewhat recently have been acquired a part of private equity. our 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. know, within the practice, we have over 25 retina specialists. We've had a robust clinical trial team for quite

some time, quite frankly. We've been involved in all the pivotal studies that has gotten many of our current treatment available that we're currently using. And more recently, over the past year and a half, I've now started to be the research director. And the reason for that, quite frankly, is we've had a large turnover. Some of my more senior partners have decided to maybe take a slower pace in 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 the challenges, but also hopefully 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 (01:44.662)

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

David Chin Yee (01:51.956)

not only in Georgia, probably in the southeast. That is

Ram Yalamanchili (01:55.04)

Okay, Yeah. And just a quick introduction on my end. think we've met through...

a common connection, if I'm not wrong, through another retina physician. And what was interesting when I 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 your forward thinking in terms of adopting new technology or new ways of essentially managing your research program. So I think it'll be great to have you share more thoughts about that.

And really looking forward to this discussion, right? I think we've had really strong discussions around this topic. You're clearly passionate. You're interested in the next generation of how things should be or things will be in research. So let's get started. I think to begin with, let's talk about some challenges at the site level, Like you said, you've had a robust pipeline. You had some staff done our work.

and you're managing a fairly large program as well. yeah, tell us a little bit more about your sort of challenges which you're seeing or have seen in the practices.

David Chin Yee (03:14.456)

Yeah, you know, as you 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. Unfortunately, you know, you may have someone that has the experience in ophthalmology, right? You know, the terminology and lingo, 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.

that we're using for clinical trials 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 very rare. Now, we primarily will take someone from our site as a technician who has already had experience, but again, getting them someone up to speed, getting the certification.

And it's not just taking a picture, but it's 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 the biggest hurdles that we've had is one, getting up to speed, getting the 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...

Those have been some of the largest hurdles and challenges. And so for me, 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, a booklet for our staff to be able to get up to speed, things that can help them get to where we need to move forward as quickly as possible. I didn't mention earlier before, but as you said, we are a large

David Chin Yee (05:34.446)

you know, so we have over 15 office locations. And primarily right now we only have one study site. But one of the reasons for me stepping in is again also expanding, right? Wanting to have another study site 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 (05:54.658)

Yeah, absolutely. In fact, you touched on quite a few points here. Maybe let's start with the staff training or onboarding aspect of it. So you mentioned something interesting, which is I think your preferred route, or at least the path you've taken, bring on

technicians who have some experience clinically and then training them to help you on the research side. What's your experience been in that regard? you know, have you noticed things which went well versus didn't go well? Anything you could share in that process?

David Chin Yee (06:26.618)

Yeah, you I think you need to find someone that is on the same wavelength or same passion, right? They have to understand the importance of clinical trials. Why are we doing it? Right? They have to have the same vision and mindset that I have, which may be including the involvement of technology, things to be able to get us, you know, more up to speed to the future. 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 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 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.

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 flexibility to have that ideal candidate. 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 to great communication and an open mind, but I may find someone to open mind, but maybe not great communication or vice versa.

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

Ram Yalamanchili (07:54.126)

Yeah. Can you tell us a little bit more about the turnover issue which you brought up? What do you think contributes to that? Because I hear this pretty often, right? Not just in your case, but I've heard this in many other sites we work with. I think it commonly comes down to also use of the word burden or some sort of burnout. What are your thoughts on it? Like, how do you look at it?

David Chin Yee (08:17.968)

Yeah, 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. And there's no question, there's a larger demand for ophthalmology, clinical research coordinators, research assistants. And we don't have as many, you know, the supply is not there. We don't have a school or system set up in place.

to get individuals set up to be able to meet the demands that we have. So we have limited supply, a large demand, and then when you have that rear bird, I mentioned, right, ophthalmology experience and clinical trial experience, they're getting snagged by maybe some of the CROs, right, was looking for bigger, better opportunities, maybe less stress, better pay. And so you type all those 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 time to be able to get successful within the system. It takes long, right? There's so much inefficiency within doing studies and 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 or maybe not as

enthusiastic as I would like them to be because they're overwhelmed and burdened with whether it's communicating to a sponsor or 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. so the manpower to be able to fulfill all the needs and tasks at this point is somewhat limited.

Ram Yalamanchili (10:14.166)

Yeah, no, absolutely. And what I find fascinating is, one of my own personal route has been came from a technology background and went into a biotech startup with a couple of physician founders. And we had an exit of that startup.

And then I essentially came into the research side of things from a site perspective, because I have seen the sponsor perspective of what clinical research looks like. And it's interesting because everything you've said 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 one end is efficient and the other is inefficient. It's literally the whole spectrum is inefficient, right? The whole ecosystem is inefficient.

David Chin Yee (11:03.216)

Mm-hmm.

Ram Yalamanchili (11:04.442)

And I certainly saw this when I started Tilda. 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 while building this business. And really, you know, from a product perspective and, know, just in terms of where our focus is today, how to bring technology, how to bring AI into this whole industry, I really feel the coordinated role is an unsung hero type of a role.

they can make or break the entire program at a site. And frankly, there's quite a bit of risk also involved 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 downsides out here. So yeah, I would love to sort of let's explore this a bit further on these topics. So I think what I'll first start off with is...

You are using our platform and our AI teammates in your clinic. And maybe the first thing I'd ask you is, what got you interested in even exploring something like an AI teammate or an assistant or whatever you want to call it from your perspective? How did that come to you from just an evaluation perspective?

David Chin Yee (12:29.268)

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. And for me, I thought that would be one of the easiest ways to cut back on some of the inefficiencies that we're already facing and some of the challenges.

Again, that could be in regards to training, getting staff up to speed. That could be in regards to getting data entry points, removing redundancy, helping to make and create less errors so you don't have to go back and repeat it, wasting time, right? Maybe simplifying a process, right? You have a problem or 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. so the knowing one that this identifying the problem, which we kind of discussed 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 more productive, more efficient and searching out and seeing what would be the best fit for partnership with our department was very important.

incremental.

Ram Yalamanchili (13:56.494)

One question I have, which you 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. They both go hand in hand and 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 set up is really like quality focused, right? I you have monitoring, have CRAs who are traveling coming to your site. So I always believe that if you don't have great quality at your end node, which is basically at your site level, then you're moving up this quality burden through the stack, right? Up into the CRO level and then ultimately the sponsor level.

So tackling quality in a way where 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 we as a humanity would probably benefit quite a bit by building these kinds of systems and making them more ubiquitous. And of course, from an AI perspective, that is the most efficient way to do it. 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 managing 10 times the volume of trials we have today. mean, maybe you can tell me a bit more about this, right? 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 capital available to do this. But I do believe science is accelerating at this point. Discovery is accelerating. know, target discovery is accelerating. So ultimately, the bandwidth on the clinical trial side has to be a place where we have to innovate and we have to move forward faster.

David Chin Yee (15:46.746)

Mm-hmm.

Ram Yalamanchili (15:57.646)

because that's really important, right? But I'd to get your thoughts from a clinician perspective. how do you see that evolving in the next five, years or even two to five years?

David Chin Yee (16:05.946)

Yeah, you know, I think you hit the nail on the head. One of the bottlenecks, right, is the ability to get the study patients, you know, yes, identifying the patient's recruitment, but then processing and getting them through 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 individuals coming through,

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, know, pour data in, you get poor data and information out, which is not gonna be beneficial for the patient 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.

you want to get good quality data and information. And besides the point, remember, if you're not doing, what's the point if you're not doing high quality work, because then you put yourself at risk of getting into problems and trouble in terms of from a regulatory standpoint, right? So again, you definitely want to avoid any of those hurdles or pitfalls if possible. But as I said, I think one of the largest bottlenecks that I'm seeing, where they 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 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 is to work within that system and find out how can we become more efficient? How can we minimize that curve or that step ladder and flatten it to get us to that process a little bit faster and sooner? And thereby allowing us to one, have more patients included in studies and then also lower the barrier or entry level for me for example wanting to start a new site. Again, if...

David Chin Yee (18:28.9)

the system is in place, it's a little bit easier to streamline. I can open up other sites or even other practices can start to inherit other clinical trial sites and it'd be easier, right? So lowering that barrier or burden to enter into the system in place. And again, 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.

allowing them to be able to be as efficient or get to where we potentially are with lower entry points.

Ram Yalamanchili (19:05.954)

Yeah, and 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 say on a ratio basis, a fairly large administrative burden to productive burden. And productive is more like, you're seeing the patients, you're managing 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 fired papers. I only entered data or entered, you know, caught up on my queries. I've got a monitoring wizard coming in. I've got, you know, something else coming in.

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

or recruitment. These are all areas where you can meaningfully improve bandwidth of a clinical study, but just having these additional burden of, I'm just saying like even from where we were when we first started working together.

the same team set of team members were managing multiple studies, tens of studies, regulatory, quality, data management, finance. And it's all intertwined, right? Your finance cannot be accurate without great quality and your quality cannot be great without good workflow management, data management, regulatory. So it's very...

David Chin Yee (20:51.13)

Hmm.

Ram Yalamanchili (20:53.806)

closely intertwined and like you said, if you don't have the right people or if you had a turnover or a burnout, you sort of very quickly run into these issues where things start to unravel. And like you said, then the ultimate concern is, 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?

And one thing I've noticed, which maybe I'd love to hear your perspective is I've heard something like 95 % of the sites bill under the amount of work they've performed. know, budgets can be complicated, can have quite a bit of invoice bills, can be structured in a way where, you know, your negotiation is dependent on how you bill for it, how you bill for the work you've done. And...

Unfortunately, the systems are not mature enough today to capture this sort of financial intelligence and place it 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 you've gone through quite a bit of that experience. I'd love to hear your own story on this,

David Chin Yee (22:05.432)

Yeah, I think first off, just to kind of reinforce what you said before, 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 way.

And one of those errors, unfortunately, is this billing part. And the biggest reason for that, I think, is, well, again, the most important thing 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, that you're not making any mistakes. And 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 how do you invoice for each

study could be completely different. So it's not streamlined at all, which to me just, mean, it seems kind of ridiculous, but it is what it is. And so you know the system, you know the game that's played, and then unfortunately, you know, 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 it...

you have a staff member or someone that's focused on that. And if you're just starting up, got to be honest with you, you're not putting so much the realities you probably should because to be able to continue to grow, you need to have the income coming in because that's a major part and reason why we're doing clinical trials. Yes, it's to help the patients provide new technology and capabilities, but it also is a financial benefit from a group and a study standpoint. 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 backlog information to be able to then invoice correctly. And so 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 a 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.

David Chin Yee (24:18.576)

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 back end to try to reconcile that. So it's kind of like you need another accountant or an auditor to basically implement this system in place. And so again, all these identifying the issues, but then therefore that's why you're not getting the, yes, the budgets are large, but how much, I think you mentioned only 95 % is being invoiced. And then

Again, let's be honest, CROs, don't mind if we don't send an invoice and bill. They don't want to pay, right? So you set yourself up for an environment, right? Where you're going to 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 kinds of reconciliation to kind of say, hey, we did get reimbursed or get paid for this.

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 a priority in the first place.

Ram Yalamanchili (25:31.822)

Yeah, no, it's such an important aspect, right? just my view about this has always been, I mean, you touched on many great points. It's the idea that we have to work within the ecosystem. We have to do things where 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 or like, you know, things like this, right? Which is very typical from most technology companies. They come in, they say, here's a new software, which will basically change everything, you know, 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 from a sponsor supplied systems and things like that. Our view 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 automated away quite a few of these workflows which would otherwise be manual 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 particular workflow might be.

So whether it is data management, whether it is 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 provided.

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

Ram Yalamanchili (27:28.238)

There's a lot of things you can do from all this information from an AI team and we can say, OK, I'm just going to 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. And I think this sort of a augmentation of AI, I feel, is going to be a big part of our future. It's already here and it will accelerate, right? This is where the world is going. 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.

David Chin Yee (27:35.717)

Mm-hmm.

Ram Yalamanchili (27:57.514)

So just from an experience perspective, do you see this sort of thing accelerating? Have you seen things outside of our relationship working with Tilda, right? But any other areas where you're excited about, maybe just for the general field?

David Chin Yee (28:15.076)

Yeah, think, you know, just within the clinic, whether it be for scribing and charting for a patient 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 on documentation with a patient with say diabetic retinopathy or a patient with macular degeneration. So, you know, assisting the scribe and documentation for that encounter visit is going to be

tremendous in addition to that in terms of AI technology for imaging diagnostic evaluation. 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 these medications are doing for 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 HomoCT that uses an AI-based algorithm to kind of help us to have better monitoring and control on how well our patients are doing when 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 doctor to say, we need to come in and have treatment a little bit more frequently or sooner. So all these different tools that are coming is definitely here and super important. I think one thing that's important to note, to differentiate your system as well, it's not only an 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 think it's also important, and I found that extremely helpful, that it's not just a software system and platform, but it's a partnership with your team that also bring along experience within clinical research and also ophthalmology.

Ram Yalamanchili (30:25.964)

Yeah, absolutely. think that's really key, right? I think having a strong partnership driving value for you and your program. I mean, that's really critical and non-negotiable, really. No, this is great. I think I sort of covered most of what I wanted to cover. Abdullar, do you want to have anything else you want to talk about?

Ram Yalamanchili (31:08.003)

yeah.

Yes, yes, I think that'll be helpful. All right, so I think one, so let's talk about that question. So another question I have is, I think most like you're seeing, we're all grappling with this new reality that AI is gonna be a big part of our life. Great things are coming and they're coming on a regular basis.

How do we get started? Where do you think that starting point will be? And what are the right environment or the variables which you have to consider before saying, let's get started on this thing and really adopt it.

David Chin Yee (31:49.316)

Yeah, 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, 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 want to start exercising, right? 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 AI platforms.

and see which one may work best for you. The first step is making the action and actually reaching out and seeing what are the next steps to implement. From my experience working with you, it's quite actually easy. You kind of develop a framework. What are your needs? What parts of the system would help my department to achieve the metrics that I'm looking to achieve? So it's having a clear idea of what your goals and 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 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 going to 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. Learn, reach out, and see what would be the best system for you.

Ram Yalamanchili (33:23.298)

That's well said. I would ask you, when you said metrics or where you want to go, I know we touched upon this in various forms today, but can you maybe describe where would you like to take this program? mean, from you personally, know, I'd to hear your like, you know, what's your goal for here?

David Chin Yee (33:46.318)

Yeah, know, my aspirations, you know, I'd love to tell you, I want to 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 seeked 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 cut and edge technology and treatment modalities. I want us to again be

revealed or being considered one of the top sites 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 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 (35:01.454)

Yeah, and I think you'll get there. At the pace we're going, I think it'll be great. OK, wonderful.