Trials with Maya Z

Maya Zlatanova, TrialHub (00:01)
Hello, everyone. This is Maya, and I'm here with a very exciting guest today with tons of experience in clinical research and precisely in startup, Angie Schwab. Angie Schwab has actually founded EZ Research Solutions, which is a very exciting company that combines startup expertise with AI.

And just before we started recording, Angie was telling me how passionate she became about startup. And I can't wait to hear more about the story. So I stopped her there and I said, let's start recording because I want to make sure that everyone can hear this amazing story. But before that, Angie, first of all, welcome. And second, can you tell us a little bit more about yourself and your background?

Angie Schwab, EZ Research Solutions (00:45)
Absolutely, Maya, thanks for having me. I'm really excited about this conversation. I love people passionate about research. I think we've got a lot of fun things to talk about today. A little bit about myself. So I grew up in Minnesota, did undergrad in Iowa in genetics, grad school in North Carolina in genetic counseling. I wanted to be a clinician. I want to see patients. I want to do research. I want to change the world, you know.

Maya Zlatanova, TrialHub (01:06)
Nice.

Angie Schwab, EZ Research Solutions (01:08)
You have these grand sparkling ideas when you're young and I love that enthusiasm. And from there, I became a clinician. was seeing patients, I was doing research on the side and just realized, wow, in order for me to have more of an impact, I need to do more research. I need to not only do my research, I need to help other people do their research. And that's when I became more like a manager and a director of a research department.

overseeing many different research studies probably helped start over 200 clinical trials in my timeline. I've been in it, dare I say, 20 years to date myself. It's been a minute. I know, I really should. But my passion's always been in the startup. think if you don't have a good foundation, that study's gonna fail.

Maya Zlatanova, TrialHub (01:40)
wow.

You should be proud of it, come on!

Angie Schwab, EZ Research Solutions (01:58)
And depending on the statistics that you look at, they say upwards of 80 % of clinical trials fail for one reason or another. It's not that they're not successful improving their outcome. It's they fail. They maybe they don't enroll enough patients. They run out of money. They run out of timeline, you know, all of these things. And I would like to help people not do that. You know, let's design intelligence studies from the ground

Maya Zlatanova, TrialHub (02:10)
Yeah.

Yeah, so tell me actually, that's very interesting. Do I understand correctly that from your perspective, these clinical trials are failing because of anything related to startup? Or actually, maybe let's go one step back. And can you tell me from your experience, obviously you've supported more than 200 clinical trials, what failed the majority of these clinical trials?

Angie Schwab, EZ Research Solutions (02:48)
think it was they weren't thought, they weren't well thought out. They didn't think about the participants. They were not realistic about their inclusion, exclusion. They were asking way too much of these participants. The participants were like, thanks, but I don't want to come sit in your office for eight hours. They're not realistic. I don't think they were realistic about the budgets. Many times you see investigators say, great, we're going to have an MRI and a CT and an echo and

like blah, blah, blah, right? Like they just stack it. They stack all of these tests and procedures in thinking, at least in the US, I can caveat this in the US, they think insurance is gonna cover it. And many times it doesn't, or they haven't thought that out. And all of a sudden you're into a trial, you're doing all these procedures, and you realize, whoa, why is the department getting these bills for this? And then the department said, I gotta bill the sponsor. And the sponsor says, we don't pay for

So then they said, well, whoa, I can't enroll in your trial because I can't have my patients paying for all of your tests. So it's really having a lot of things fall through the cracks. that's why I'm passionate about study startup. If you don't think through these things in the beginning, you are setting yourself up for failure.

Maya Zlatanova, TrialHub (04:08)
Yeah. So if I'm to summarize, if you don't understand the local standard of care, because like all these procedures being done, what's reimbursed, what's not reimbursed, it's actually key to know what you can expect the motivations of patients to join your trial, but also to have a predictability over your budget and timelines. Is that correct?

Angie Schwab, EZ Research Solutions (04:25)
us.

Absolutely. Absolutely. There are so many complicated factors that are involved in study startup and designing from the beginning. And that's why I really advocate to having all of the study team around the table from day one. Yes, the investigator has a brilliant idea, but as soon as you can get the right people around the table who have these interesting perspectives, you can build that study in a much more robust way from ground

Maya Zlatanova, TrialHub (04:32)
So, so,

Mmm.

Angie Schwab, EZ Research Solutions (04:57)
and then all of your documents trickle out of there. It's not take a document, make another document, make another document, realize you needed to change something in the first document and have this continual cycle of revisions and documents. So I was like, no, like we need to get away from that. Let's all agree at the study component level and let the documents write themselves.

Maya Zlatanova, TrialHub (05:19)
Angie, I have a question to you. You mentioned that very often these clinical trials fail because of the fundamentals. The fundamentals were not there. So when you are involved in startup, and I want to make an amendment, I've never been a part of startup, like not actively, let's say. So what's the possibility of you to impact these fundamentals?

Like how often sponsors or investigators or whoever is working on the protocol that defines that, do they give you the chance to actually think, hey, you need to go back and change that?

Angie Schwab, EZ Research Solutions (05:54)
Yeah, that's why we are starting from the very beginning, asking the sponsors, the CROs, the investigators themselves to say, bring in your people now. And the way that we do that is by creating, it's a very robust kind of a questionnaire. It's an iterative questionnaire, like design your own adventure kind of thing, right? If you want to do a drug study, I'm going to ask you all these drug questions, but then I'm going to ask you, who's paying for that drug? Okay. What are the tests involved? Who's paying for those tests?

So I think the best thing a sponsor and a CRO and an investigator wanting to launch their own research study to do is write out your summary. Decide in general, what do you want to do and then start pulling in those other resources. So from a sponsor's perspective, what I would think would be fantastic and some of them are doing it, certainly not all, but they have a theory.

and then they're going to bring in a CRO to help them execute on that. That protocol shouldn't be final at that point. It should be 90 % of the way there, but that's when you give the opportunity for the CRO to come in and say, you know, this part, we've seen this in our experience, it's probably not gonna work well. It's gonna be hard to find these patients at these locations, et cetera. And then also bring in an investigator. If you think,

Dr. Johnson in cardiology has done a similar trial. Don't be afraid to reach out. Say, we're thinking of a similar type of a trial and enrolling a similar type of participants. I would like your input. And the more we can create this cohesive collaborative environment, the better all of these trials are going to be. They're gonna be more efficient, cost efficient, time efficient, more realistic, and the participants are.

hopefully going to be much happier than they are today.

Maya Zlatanova, TrialHub (07:46)
Yeah, but Angie, you mentioned bringing in another investigator that's maybe done something similar. And I totally agree with you. Like someone going through a similar experience can tell you what are the pluses, minuses, what are the let's say challenges that you can expect, maybe even predict and prevent some of them. But what about bringing the patient in as well? Because, okay, so for out of these 200 clinical trials, how many did you

Angie Schwab, EZ Research Solutions (08:09)
I love that.

Maya Zlatanova, TrialHub (08:15)
Did you manage to bring the patients in the right time and get their thoughts as

Angie Schwab, EZ Research Solutions (08:21)
You know, for us, when I was working back in it, we did our best to get perspectives from people. Like we would ask and say, we'll have an upcoming trial about this. But it was never a roundtable with a patient there to say, this is our proposed schedule. What do you think? Does this seem reasonable? Could you come back every three weeks? You know, I love, love that idea. I think the implementation is a little bit harder.

to do, but I would love to see that happen.

Maya Zlatanova, TrialHub (08:48)
Mmm.

What makes it harder? What makes it even hard to ask an investigator because from what you said, that's not very common to bring another investigator. That's what you're advising, but from what I understand, it's not, let's say, a common practice. So what makes it hard to bring another investigator with the same experience? And then what makes it hard to bring a patient to the round table, like you mentioned?

Angie Schwab, EZ Research Solutions (09:13)
Yeah, I think you have to also be very strategic about your intellectual property. You know, we are, we're in a very high stakes environment where we're creating novel therapeutics, novel drugs. And so you have to be very confident in the people you bring into your table. You know, the CDAs, the NDAs, but usually adding them as investigators

Maya Zlatanova, TrialHub (09:18)
Mmm.

Angie Schwab, EZ Research Solutions (09:33)
If they did a similar type of research, there may be some conflicts of interest there. So it's just vetting and thinking through all of those things. But I say, absolutely, it's worth it. It's worth taking the time. And the patient side of things, I think it honestly doesn't cross our mind that much. As researchers, we're so busy. We're trying to do so many things. We're creating all the forms. We're doing all the things. We're creating all the submissions and the responses.

It's a lot of work and to be like, know, Jane is in my mind. I think Jane would be a great candidate for this. When is Jane coming to clinic next? I should sit and talk to Jane about this. Like the timing and make coordinating all of that is a heavy lift. But again, if you can do

Maya Zlatanova, TrialHub (10:19)
It's one more thing. Yeah, yeah, I understand. I truly, and I think most people are convinced of the impact, most people. But then like you said, it's one more thing on top of everything else that you need to do. And it's a lot. But I hope we find a way and scalable way to actually support investigators, sponsors, whoever basically to include the patient at the round table because

You mentioned it, like 90 % clinical trials fail. So I think we need to do something else. Yeah, well, yes. Yeah, of course, of course. Angie, I wonder from the very beginning when you started mentioning your background, you mentioned this passion to become a researcher, and then you became one. And I wonder what was the difference between what you expected to be like to be a researcher?

Angie Schwab, EZ Research Solutions (10:48)
I think the latest I saw was upwards of 80. Yeah, but for various reasons, yes.

Maya Zlatanova, TrialHub (11:12)
And what it actually was, once you are a researcher.

Angie Schwab, EZ Research Solutions (11:16)
You know, again, you have this like pie in the sky. I'll get to work on all the most amazing things and design trials and work with this doctor and that doctor, because I have a master's, I'm not a doctor. So my goal was to work with clinicians and to bring these ideas to fruition, right? Like that was my passion. And then you start getting into the bureaucracy. There's limited resources, there's limited time, there's limited access. You are...

Maya Zlatanova, TrialHub (11:36)
Mmm.

Angie Schwab, EZ Research Solutions (11:43)
I'd like in being a clinical researcher to an entrepreneur. You have so many chips stacked against you from day one. You have to literally peel away every single one to try to get at that dream trial that you have or that dream business that you have. And it's gonna take effort and it's gonna take networking and you have to find a way to be incredibly resourceful. One of the biggest issues that most investigators face is

knowing how to find funding and knowing that there are sponsors out there that may love to help you with your research study. There may be universities that would love to help you. There may be nonprofits. And if you're lucky enough to get a government grant, that would be wonderful. But going through all of those channels, it's a really heavy lift.

Maya Zlatanova, TrialHub (12:13)
Hmm, of

Interesting. And then you decided to focus on startup. So I wonder, like I said, I don't have that hands -on experience with startup, like with the stage of the clinical trial. So tell me what got you excited about startup, but also, actually, let's start with what got you excited. And then I have a follow -up question.

Angie Schwab, EZ Research Solutions (12:51)
I think it was all the challenges. For some reason, like it may not be very bright thing to do, but I love to run towards the problems, not away. And I was like, okay, like if we develop this from the ground up, it's gonna be more successful. Like I don't wanna keep seeing and putting all my life's effort into studies that continue to fail and don't have the outcomes that they want. Like I could literally consider that wasted lifetime. And if we

build it better from the beginning, then my life hopefully isn't wasted on trials that go nowhere. So that's where I became passionate. Like, let's solve some problems.

Maya Zlatanova, TrialHub (13:22)
Yeah.

I can see that you're literally going after the bureaucracy problem. Exactly the thing that you didn't like, you are actually fighting it to make it better. So other people are way more other, let's say other people that dream of becoming a researcher, they find it way more attractive. Nice. I love

Angie Schwab, EZ Research Solutions (13:42)
Yes. Yes. Yes. And I actually built that into EZ Docs as well. So we have a very easy intuitive platform for new researchers to come in and build your study. So let's not grab this template, change this info, grab that template, change that info. And you do that 30 times in all these different forms. It's, let me help you think through your study. Let's take a step back, answer the questions.

Maya Zlatanova, TrialHub (14:04)
Yeah.

Mmm.

Angie Schwab, EZ Research Solutions (14:11)
Let's think through how are you designing your study. I'm going to ask you questions you never even thought about, but it's going to prompt you and give you ideas of things you should be thinking about so that you're not one of that 80 % that fails.

Maya Zlatanova, TrialHub (14:26)
Yeah, you know, this reminds me, Angie, of one of my experiences lately, maybe last year. created, like as part of my company, we created like this gen AI solution that can empower you to ask questions proactively. And then we thought that because this saves us so much time on researching.

People will be proactively asking for things around patient feasibility. Why would patients join a trial? What would motivate them? What would be the barriers for recruitment and stuff like that. Only to find out that actually people are not necessarily, they don't necessarily know what are these questions. There's so many questions they need to ask. So like you said, even in startup, maybe sometimes you haven't even thought about these, questions that you should be asking and making sure that you are bulletproof.

Angie Schwab, EZ Research Solutions (14:52)
Yes.

Maya Zlatanova, TrialHub (15:19)
clinical trial protocol with your feasibility, execution plan, and so on and so forth. Very interesting. Angie, tell me more about the challenges that you face with startup. And my next question would be, mentioned EZ research solutions, the platform that you have. It'd be also very interesting, how many and which of these challenges you're directly addressing with your company now, and what's the role of AI?

Angie Schwab, EZ Research Solutions (15:31)
Mm -hmm.

Yes. So the challenges for me that I saw in study startup is number one, not well thought out. You're not answering all the questions you need to. You're not thinking through it. You are getting surprised more often than not and not in a good way. As you launch and you do your first patient, you realize things went sideways and now you've got to do amendments and it's just really hard.

And especially for a new investigator, it's a really, really heavy lift to get that first research study done. So how I wanted to solve that is create a platform that's collaborative, where all of the experts can come in and answer the questions with you, review it with you. You could seriously sit in a table, have an hour long session with people and say, hey guys, what do you think about this? How many participants should we do? What are our primary and secondary objectives? How are we going to manage this?

How much time will it take? You go through all of that with your team. That's where you hash everything out. You should be hashing it out before you launch and get your first patient in and see how it goes. So that's what I built into EZ Docs. And then from there, I wanted to tackle this issue of data reuse. So much manual data time. We actually worked with the university lately

looking at EZ docs. And the thing is people don't understand how much time they're spending on these documents. They're like, don't worry, I have a template. But yeah, you have a template. You're still spending 25 hours crafting that document based on your directions in your template. And that's one document. And then you go to the next document and the next document and the next document, just to create like the basic of your study design, your protocol, your consent form to get

legal onboard, your finance people, your operations team, and your investigators, you really are looking at over 250 hours. At the least, most people tell me I way underestimate that for an investigator -initiated university study. And with ours, we've been able to save almost 200 hours. Because now you're just answering the questions, the documents create themselves, you proof the documents. It's

Maya Zlatanova, TrialHub (17:39)
Hmm, okay.

wow.

Wow.

Angie Schwab, EZ Research Solutions (17:58)
Very simple, very fast. And I would love to see more people use it. Like that's where we're at right now. I want to help more researchers do more research.

Maya Zlatanova, TrialHub (18:01)
fascinating.

That actually reminds me of another question. I know that in your past, like you mentioned beforehand, that you've supported both investigator -initiated clinical trials, but also sponsor -led clinical trials. Is there a difference between the way they are doing their planning on their next clinical trial? Is it fair to say that sponsors are way more prepared? They have these, let's say, preparation with all these questions, because let's say they're doing a lot more research.

Or you've seen the very same mistakes that investigators are doing for their own clinical trials with sponsors as well.

Angie Schwab, EZ Research Solutions (18:49)
Yeah. You see the same mistakes, however, the stakes are much higher, right? If you're taking a big pharma company, they're putting many, many more research resources at this to try to prevent that, but I've absolutely seen them fail for the exact same reasons. I'll give you a specific example. It a cardiology study that I had taken part in and

Maya Zlatanova, TrialHub (18:54)
Exactly,

Angie Schwab, EZ Research Solutions (19:15)
We knew it just, didn't work well because one of the things is you had to catch them before they were cardiac patients. However, you were enrolling them in cardiac clinics or looking for the patients in cardiac clinics. That doesn't make any sense. You have to hit them in primary care, right? So, but that was the team is the cardiologists were the ones passionate about it. So they were trying to enroll from their area. So it's just thinking through the operations and the feasibility. And this was a very large.

multi -site study, actually it was an international study. And it was like, let's just think through this for a second. So the same mistakes are happening, which is sad. On the bright side though, ICH M11 guidelines for the protocol are coming out soon. they

guidance documents saying, okay, this is what I think like the final protocol suggestions are going to look like. Hopefully that's released at the end of 2024, depending on when you hear this. And at that case, we really all should be playing by the same rules. Like all of our documents should all look the same, whether you are a sponsor doing a prospective study or investigator initiated. You should be thinking through all of the same aspects because when it comes down to it, it's about patient safety. It's about doing a good trial.

about taking care of your patients and hopefully having a good outcome so that you can actually test your hypothesis.

Maya Zlatanova, TrialHub (20:43)
And I understand your focus on the documents, but then again with your example, for example, it's very interesting because I've heard these stories. I hear these stories all the time. For example, looking for a breast cancer patient before any treatment and looking for such a patient with the oncologist.

Angie Schwab, EZ Research Solutions (20:56)
Yes.

Maya Zlatanova, TrialHub (21:12)
who is actually the person that gives you the first -line treatment and not the one that diagnoses you. like in country and that varies country by country. So that happens all the time and I'm like, I understand the documents and the documentation is super important, but they're only a reflection of your initial research. And in this case, understanding the local specific patient pathway.

Angie Schwab, EZ Research Solutions (21:19)
Right.

Maya Zlatanova, TrialHub (21:38)
understanding their country -specific standard of care, access to treatment, access to procedures, and at what stage they become eligible, at what stage they may be motivated to join your clinical trial, and then getting this research, not only that, but also all the regulatory frameworks and so on and so forth, and translate that into your trial documentation. That just makes

Angie Schwab, EZ Research Solutions (21:38)
Yes.

Yes, there are so many hiccups along the pathway that people need to think through and sponsors specifically, especially if you're doing international study, the level of complexity just got ramped up, know, tenfold. And like you were saying, the care pathway is different. And I would even say international, the care pathway is different clinic to clinic in the same city. You know, how we treat our patients can be very different no matter who the

Maya Zlatanova, TrialHub (22:15)
Exactly.

Angie Schwab, EZ Research Solutions (22:31)
treating clinician is. So we have to think through who are our investigators, who are our sites. Does it actually make sense? And that's where you would want to come in and create a very good like schedule of activities and think through the site burden. So as you're going through feasibility, that's another big part of the study startup process is site feasibility. So whether you're on the receiving end or the side of trying to find your sites.

actually sit down with them and have a conversation. It's not, here's the schedule, how does it look? Here's the budget, here we go. Everybody okay, sign the document. Great, now here we go. But actually have a conversation. This is how we anticipate the study to go. This is the schedule. Does this work in your clinic? Is this when you see the patient? Is this when you do these tests? Does this make sense? Do you actually even see these patients? That should be number one.

Maya Zlatanova, TrialHub (23:21)
That's a very good question. That's a very good question. Especially when you're asking someone for their advice and feedback. Do you get to see these patients? Wow. Angie, I wanted to once again ask you about the role of AI because you always speak is about automation, reducing this manual work. And I would also add to what you're saying. I understand that you're saving

Angie Schwab, EZ Research Solutions (23:45)
Yes. Yes.

Maya Zlatanova, TrialHub (23:50)
a huge amount of hours, but I would probably, would add, here I'm assuming, but you can actually tell me if I'm wrong, I assume that you're not only saving a bunch of hours, but you're also saving a bunch of manual mistakes. Because let's face it, we are humans, and it's normal to make mistakes, especially when you work hundreds of hours on multiple documents, missing something, saying it differently, and so on and so forth. So it's not just the saving hours, it's also

Angie Schwab, EZ Research Solutions (24:05)
Absolutely.

Maya Zlatanova, TrialHub (24:19)
saving the mistakes. So what is the role of AI and where do see the future of

Angie Schwab, EZ Research Solutions (24:28)
Yeah, I would actually take those as two separate things. I'm so glad you brought that up because doing the automation really drastically reduces. So imagine you're now entering in, I have 150 patients and then you create all 30 documents that have 150 patients in 27 different spots, right? And the chance of you manually entering in accidentally 151.

Maya Zlatanova, TrialHub (24:31)
They are.

Angie Schwab, EZ Research Solutions (24:54)
in that one spot and it goes to the IRB and it gets kicked back and delaying you, it's likely this happens all the time. We are humans. So yes, I do think automation has a huge opportunity there to increase the compliance as well. You're also putting it into templates that are standardized and you're using expert crafted language. You're not trying to create all of this yourself, which is such

uphill battle for especially new investigators who don't have that done. So I lean very heavily into automation right now. And EZ Docs is predominantly automation right now. But with that caveat said, I also saw a great statistic that said AI's capabilities are doubling every six months. And so we are, we're certainly adding in AI components, which gives you suggested language.

Maya Zlatanova, TrialHub (25:33)
Mm

Angie Schwab, EZ Research Solutions (25:48)
we're not having AI write all of your documents right now, because I honestly think that's a big mistake. AI is not ready right now. AI can provide some suggestions that you would need to review, but these are highly regulated documents that need to be perfect. You should not just say, hey, write my protocol about cardiomyopathy and blah, blah, blah, write a research program and think it's going to come out looking good. It just does not.

Please, please do not make that mistake of making any regulatory documents with AI right now. That being said, this is, as we're taping it, July 2024. And as I said, AI doubles every six months. Things are going to change. But how I incorporate AI is specifically that giving suggestions, okay, how would I craft this section of a paragraph, et cetera? I think it's really helpful.

Maya Zlatanova, TrialHub (26:43)
Yeah.

Angie Schwab, EZ Research Solutions (26:43)
to give you ideas and to do an initial draft for you. Right now, it's not ready to create all the documents. But talk to me in six months, we're going to have a very different conversation.

Maya Zlatanova, TrialHub (26:50)
Hmm. Okay. I'm going to take this advice. I'm going to talk to you in six months. Just joking. Where do you see the future of startup in general? mean, AI is just an instrument. Let's not forget that. But where do you see the future of startup for clinical trials? Are you expecting, you already mentioned some regulations coming

Angie Schwab, EZ Research Solutions (26:58)
-huh.

Yes, that's right.

Maya Zlatanova, TrialHub (27:16)
So that also influences this area. But what's your overall feeling? And if not a feeling, where do you want to see StartUp going?

Angie Schwab, EZ Research Solutions (27:28)
Yeah, so not only startup, but the entire clinical trials is moving digital. And I don't think a lot of people recognize that yet, but Transcelerate, which is a very large nonprofit that helps push the entire industry forward. They have a digital protocol initiative. So they're recognizing this. Sponsors are recognizing that we need to quit.

Maya Zlatanova, TrialHub (27:33)
Mm, okay.

Angie Schwab, EZ Research Solutions (27:52)
pulling information out of documents and manually entering it into other documents. This is just, it's so outdated. It's, yeah. So I think everyone's on the same page of realizing we need a better way to do this. And the way to do that is to create these digital components. But the benefits of that are not just, yay, we write your documents, but it's also all the downstream effects.

Maya Zlatanova, TrialHub (27:58)
Yeah.

Middle age. Yeah.

Angie Schwab, EZ Research Solutions (28:20)
So let's say you create your schedule of activities, it's digital. Now it can go into your CTMS, it can go to your ETMF, it can go into everything downstream that you need to have. And you once again, don't have to retype it and reenter it into all of those systems. You know there's one source of truth at the very beginning of that trial. And if you change that source of truth, everything trickles down after that.

So I see this becoming much more integrated very, very quickly. I'm seeing sponsors decide that this manual way of doing it and paying very intelligent people many, many hours of work to draft documents is not going to continue. I see automation coming in a lot more. I see AI coming in a lot more. I also see

the entire world is coming together. So ICH, as I said before, alluded to as with their M11 protocol and creating these kind of standardized templates in a way. Now it's not, okay, there's a template for England and there's a template for France and a template for the US. It's no, we should all be talking the same language because we're all doing international trials. And we're all here for the same reason.

Maya Zlatanova, TrialHub (29:32)
Amen.

Angie Schwab, EZ Research Solutions (29:40)
So I think that is really going to catapult our industry forward. I'm a big proponent of standardization. This guy's the limit right now. I think this is really an inflection point for research. Also, as you look into biotech, I mean, the economy has been pretty rough for a lot of people. I think we can admit that the last several months in particular.

Maya Zlatanova, TrialHub (29:57)
It is.

Angie Schwab, EZ Research Solutions (30:08)
and lots of layoffs. And if I was to give any advice to people out there right now, use your network, start realizing the power of AI. Because the old way of doing things is very, quickly becoming the old way. And if you don't know how to properly harness AI and automation and do things smarter and faster and more consistently, it's going

Maya Zlatanova, TrialHub (30:19)
Yeah.

Angie Schwab, EZ Research Solutions (30:37)
to be a detriment. And that's my two cents of the day.

Maya Zlatanova, TrialHub (30:42)
Thank you for sharing this vision and it makes a lot of sense and I really hope you're right because we need this standardization like you mentioned. Whether that's feasible, it doesn't depend on technology. We all agree it's not about that. I think it's about time the industry to understand that all we need is better collaboration because at the end we don't have anything to divide.

Angie Schwab, EZ Research Solutions (31:07)
Yes!

Maya Zlatanova, TrialHub (31:11)
Yeah, maybe some like who owns the innovation, who owns the patent and so on and so forth. But at the end of the day, there is plenty of room for innovation, for new treatments, for like the market is like, come on, healthcare market is enormous. So it's really time to get together, collaborate, use what's available. Because like you said, AI is growing. It's evolving constantly, but also

Angie Schwab, EZ Research Solutions (31:23)
Yes!

Yes.

Maya Zlatanova, TrialHub (31:40)
cost of AI is decreasing constantly. So that's already scalable. That's already scalable. Let's leverage that. let's really, I like, I very much like people like you Angie who find their passion in a niche, in a place where they can, where they have the expertise and they know they can contribute. So thank you for doing that.

Angie Schwab, EZ Research Solutions (31:44)
Absolutely.

Maya Zlatanova, TrialHub (32:09)
If you can share the regulation that you mentioned that you're expecting, I will include that to the episode. I'll also include the link to EZDoc. I didn't realize that EZ comes from EZ. How cool is that? But thank you so much for sharing your thoughts with me, Angie. It was a pleasure to have

Angie Schwab, EZ Research Solutions (32:31)
It's a pleasure. Thank you, Maya. I really appreciate it. And yes, I would love to collaborate with people. This is a time for innovation and working together. Feel free to reach out to us. Our website is EZResearchSolutions .com. The platform that can help you create your documents is EZ Docs You can contact us through that form. You can book a demo on there. I would love to collaborate with businesses, universities, and sponsors. Looking forward to the future.

Maya Zlatanova, TrialHub (32:59)
Yeah, well, I love this energy, so everyone should try it out, at least me, like once.

Angie Schwab, EZ Research Solutions (33:03)
Thank you, Maya.

Maya Zlatanova, TrialHub (33:07)
Thank you, Angie.

Angie Schwab, EZ Research Solutions (33:10)
Great, have a great day.