Avoiding Critical Mistakes — How to Select the Right Clinical Trial Technology Partner | LSI USA '25

Jill Hadel  0:05  
All right, 

Debbie Anderson  0:06  
Afternoon, everybody, thank you for your time today. Appreciate you guys coming out to learn a little bit more about avoiding mistakes when evaluating clinical trial technology partners. Jill, you want to introduce yourselves?

Jill Hadel  0:21  
Yeah, I'm Jill Hadel. I'm a Solutions Consultant for metadata. Previous to joining, I was with kind of the manufacturer side with Boston Scientific for quite some time, so a lot of insights, both on the sponsor side, but as well as on the software side. So looking forward to the discussion today, and I'll pass it over.

Debbie Anderson  0:40  
And I'm Debbie Anderson. I am a scientist by training, but I've been in the software world for the last seven plus years. I enjoy being at Medidata, primarily because I get to use my science background, but also merge it with software to help solve problems that we're going to talk about today when it comes to running your trials and how to leverage technology. So with that, we'll get started. We're going to start off today with just some metrics, right? I think it's important to level set in terms of where medical device trials go wrong, in terms of the percentages, right? Where do they fail? So about 40% of device trials are not meeting their end points, and this is for a number of reasons, primarily for efficacy reasons, also due to statistical challenges in your design, and then also adverse events. And when you think about a step further in terms of where are there more errors or issues or failures based on certain phases, it's always that feasibility phase, right? So oftentimes the feasibility phase has issues with safety or technical challenges with the device itself. I was in the room, in case you guys weren't, about two conversations ago, there was a workshop that was talking about enrollment. Enrollment is a really painful area, right? It's really difficult to enroll. 40 I'm sorry, 80% of trials are not meeting enrollment, and that's because sites just cannot get to the enrollment targets that they have. And all of this together really just adds up to costs right time and costs. So every day that you are delayed in your trial means you are not going to market, and when you're not going to market, you're burning cash. So we're going to talk a little bit about how to help resolve some of that burn with the use of technology. So I think it's important for you all to think about clinical trial technology. I mean, what you choose as your technology to run your trials can have a profound influence on your operational as well as your growth trajectory as an organization. And I think oftentimes, I mean, there was a metric mentioned earlier, 60% of your costs are running these trials, right? So a big number to think about, and also a big number associated with the cost of changing your trial technology. So let's say you start with one partner, and then you decide this partner isn't doing all the things that we need them to do, and now we want to pivot and go to a different partner. Believe it or not, there are tremendous amount of costs associated with switching. Things that come to mind in terms of switching are, first of all, merging of data. This is huge, right? We like to call it migration in the software space. So putting data together is painful. Also thinking about validation, if your organization needs to validate technology before you start to run it. That's time and costs. And then, thirdly, people, right? You've got to train the people they were using one technology before, and now they're going to be asked to use a different technology. So you've got to incorporate, or consider the time it costs to train the people that are using the technology, whether it's the hospital site personnel, it's your employees and or even a CRO. Next.

Jill Hadel  4:05  
Great. So I'm going to dive a little bit more into what Debbie just covered a bit. So when you're looking to speak with your software partners, you want to look at data volume. And as we can see, over the years, even you know, 20 years the amount of data that we're collecting has exponentially grown. So it's not just your EDC ECRs that you're collecting on paper or in a basic EDC. Anymore, you might have additional factors that you're collecting, sensor data, images, all of that you really want to look at. Are you partnering with somebody who can help facilitate these so really grow with your company and grow with your technology. And then you also want to ask yourself, are they able to not just help us at the beginning with maybe our non complex trials, but how can they grow with us for more complexity? Again, not just bringing in data points, but how complex can you take your technology? To really move that implant or that therapy faster to a broader spectrum of patients. You want to make sure that you're working with a partner that can help accommodate this. And then, of course, you want to have this as a unified experience. So you don't want to have five different systems pulling in all of these data points that you're gathering. You want to have in one location where there's full visibility to really dive into that data. To see, do we need to change or pivot what we're investigating? Are there certain risk at sites that we may need to address earlier, instead of waiting, you know, six months down the road till we're on site, having a unified experience or unified platform will really improve the actual site level experience, but also for your internal team. And then, again, just going a little bit more into that unified platform that's again going and asking, Can we do a simplified trial? Do we just need to do a quick 510, K investigation? Do we need to actually, really dive into, you know, a bit smaller, is this vendor going to be able to help us and accommodate and really think about budgeting as well? Are we able to work together? And again, going into that real time visibility within that unified platform is very important so that you can make those timely decisions. And then, of course, you want to also make sure that the site experience is improved. So you're pulling in data points. Are we reducing the double data entry challenge that a lot of our sites don't like? Also, there's some human error. Is there a software version that can help bring that in automatically and reduce some of that burden and reduce that risk? And then, of course, you always want to look at the training option. So can we get a site started sooner? What does the training look like? Who's supporting that? Is it something that we can have stored? So maybe we use those sites a few different times without creating additional challenges. So these are all just things to look at. What you would like to discuss with your vendor or partner, but also, really, how can we improve that experience with having that unified platform? I'm going to hand it over to Debbie here, and actually, we're going to turn it over to the audience and take a quick pause to see if you have any questions. Again. If you do, please feel free to come up to the microphone if you're able to, but really want to make it interactive, so I'll go ahead and see right away if there's any questions.

Debbie Anderson  7:27  
How about a raise of hands of those of you who are either about to start a trial or are currently in a trial, and maybe you've changed the way that you've run the technology from one study to another. Yes, several people.

Jill Hadel  7:46  
That's why you do the trial.

Debbie Anderson  7:47  
Oh, I see now I'm talking about your the technology that you used on your first study or trial. Did you keep with the same vendor for your second trial? Or did you change vendors? Okay, and I'm sure that was probably not all so simple and so easy. I think it usually tends to be a little bit of a challenge for the reasons I mentioned earlier. But I think, you know, when we think about technology and being adopted for studies, not just one study, but maybe your next study, as you progress, right, it's important to think about, as Jill and I have have alluded to, what can your vendor or partner do now? Right? Maybe you're just starting off with a study and you're in a feasibility trial, but you're thinking future state, right, as you continue to progress. So as as Jill mentioned earlier, data is is coming at us from a lot of different ways. Right? Maybe you're looking at not today, but tomorrow, you're going to want to collect sensor data. So wearable data, you want to be able to monitor patients remotely. And then, if you're looking at things like, how do I help speed up the acquisition of data? So for example, can I automate the data that is in an EMR at the hospital system, and pull it into my EDC environment, right? Does your partner allow for something like that to make life easier for all of those involved in the study from a from a data perspective, and then imaging? This is another area that a lot of medical devices are looking at for endpoints, imaging is tough. These are really large files, regardless of the modality, whether it's a CT, an MRI, an echo, whatever it is if you're looking for imaging, does that does that technology provider support automation of imaging coming in from those hospital sites and doing something meaningful with it? And then real world data is another topic that is really popular right now, which we're actually going to get into here shortly. But thinking about, how can you maximize the data that's being generated during the course of the study, or even before that you want to understand more about your patients, right? What? What did they do before they started the trial? Are they behaving while they're on the trial and longer, long term after the trial is over? You can go to the next slide. Yeah. And this just really, just kind of talks a little bit about real world data. More and more regulators are asking for this. They are really excited about the opportunities for bringing this type of data in, into the clinical trial environment. We've seen probably close to about 100 references where real world data is being utilized for regulatory submission. So something for you all to think about as you're starting to think about your data strategy and your trials. Go ahead. Jill, 

Jill Hadel  10:41  
yeah. So as Debbie had mentioned, there is this capability for that long term real world data, and here with metadata, we actually have a link solution. So just think about what you can do, not just with the clinical data that you're receiving, but also it can tell a broader story from beginning to end. So pre clinical information for the patient, the patient's information during the clinical trial, and then after so how can you really optimize what you've invested in with your clinical trial, but really keep flowing through? Is there more that you want to go ahead and investigate during the trial itself, maybe it's alongside with the main study, and then, of course, long term so hopefully, you know, gone are the days of the 10 to 20 year studies that were once required, where now you can bring that therapy sooner to the market with your clinical data. But you also have long term clinical outcomes that you can consistently investigate, R and D. Can utilize this data to kind of decide which way you may pivot with your technology so you can bring it to that broader spectrum of patients. So there is options out there, and it starts at the E consent or the consent portion of the patient's journey. So you really want to look at, how can we optimize fully for the patient's long term outcome, again, kind of before, during and after. So it really does extend that opportunity that you're currently investing in. And with that, I kind of will pass it over to Debbie, but I do want to do a quick check in with the audience Any questions so far. Also, if you don't want to, you know, stand up and have an, you know, a discussion right here. We're always available to chat about some of these options. But I did just want to do a quick check in, because everybody's a little quiet if there aren't no problem. But I do want to pass it over to Debbie to kind of jump into the questions that you may ask or want to look at with any AI.

Debbie Anderson  12:41  
All right, so AI such a hot topic, right? Everybody talks about AI, you know, I think it's important to consider your long term partners, and what are they doing from an innovation standpoint, right? The term AI is being thrown around a lot, but some organizations are actually using it today as we are, and across a broad spectrum of areas. So we'll touch on just a few here we talked about earlier. You know, protocol statistical challenges being one of the reasons why trials fail. So at Medidata, we have supported or powered, I like to say, about 35,000 clinical trials. So we have a lot of data, and with that data, we are able to build and train AI to help our pay our customers. Look at, okay, what is the best way to design my trial? Because of the wealth of data that we have, and we understand whether you're a medical device client or someone else, you know, here are the best practices in terms of this is a therapy, the therapeutic area you might want to go after. This is the patient population you might want to go after, just solely based on the wealth of data that we have. Another area I talked about enrollment. Enrollment is always challenging, right? So we have built some AI to help not only with pre emptive enrollment strategies, but during the course of the trial, if you are starting to see slower and slower enrollment in real time, we can tell you, hey, you know what? We are predicting, that you are not going to meet your enrollment. We're going to pivot now. We're going to suggest you pivot now and give and we suggest you do X, right? So trying to be proactive with catching before you get to a place where you're a little late to the game. And then the other area I like to talk about is, is imaging lesion detection is what we refer to as an AI driven algorithm that is looking at CT scans. So if you take a step back and you think about if any of you are familiar with imaging, and how much it costs to pay radiologists to read your images, it's not cheap. So this is a mechanism to proactively. Look at, identify and target different lesions that are in a CT scan, and it's going to tell the user, hey, this lesion appears to be this size, etc. So another way to help automate things, go quicker, faster, cheaper, and proactively notify the user that hey, you might want to take a look at this, right? So just a couple of ways that we are using AI today, and we continue to build on on our AI strategies. So

Jill Hadel  15:30  
Great. So just a quick recap. I promise we won't continue to slide you to death. But you know, we went over kind of the most important questions, or important questions to really ask when you are looking for software for your clinical trials, and how you can mitigate some of those challenges. We also discuss some of options of really optimizing the data that you are collecting with that link capability and AI. So as we've gone through all these different kind of buckets, if you will, as to what to bring up to discuss with your software providers or partners, there's another thing to look at, and I'm sure we've all are sitting in the room. Why do we do this? You don't really have research without the patients, right? So you want to make sure that the patient experiences where it needs to be. You want to make sure that the sites have an experience that really is easy to use. So it's something that it's user centric design, if you will. So that's for your sites. If you have options for patients that you want to collect data from the comfort of their home, all of these things you want to think about. What is the experience for the site, but most importantly, what's the experience for the patient, so that you continuously improve their outcome and they have a great clinical trial experience, so maybe they want to participate in other studies down the road and or word of mouth to their friends, all of these things you really want to ask yourself, How is this driving a better experience for my patients. And then, of course, we've already spoken to enrollment. But having that accessibility, there are a lot of patients that have no idea there's a clinical trial that their physicians are working with. They don't know if they're going to be able to participate. Maybe they can't, you know, get out of bed every morning, and there's, you know, seven different visits within the first 30 days to 90 days. All of these things are what can drive kind of make or break enrollment, if you will, where a patient says, I would love to participate, but I already burden my family enough. I'm a CHF patient, and I can't get there. But now, if you are looking with your vendors or your partners, you can say, Do we have an option for patient to maybe have a hybrid approach? Sometimes they come in the office and sometimes they don't need to. We can do a telehealth visit. They can work on their iPad, if they have one, or on their laptop. You want to make sure there's accessibility for greater patient populations to really improve that enrollment. So those are all great things to think about when you are speaking with your software providers. And then, of course, going back to that integration, that unified location and one area that you and your team can go to, where it's a single source of truth for all users that have access and you want to be able to pull your data to have faster insights. So again, just kind of a recap as to what we were going through and really thinking about taking it back to the patient and to the site experience as well. And I'll pass it over to Debbie, close this up.

Debbie Anderson  18:37  
Yeah, and I think just at the end of the day, I mean, software is great, right? But without people building the software, you have nothing. So you got to think about the people behind the software, right? You know, the professional services team, as we like to call it, is meant to really help the success of the builds, right? They're meant to listen to you, understand what your goals are, make proactive recommendations based on our experience, willing to work with you on either, you know, just this one individual study, or maybe you're looking long term at kind of a number of studies, right? So how do we work with you? Program wide? Does this partner that you're evaluating have experience in medical device right? There are a lot of players out there who are really good in the pharmaceutical world, but are clueless when it comes to medical devices. And then, you know, at what level of engagement? I think the workshop just prior to ours today was talking about, how hands on do you want to be? Are you one of those sponsors who's looking to just kind of leave it to the technology provider and your CRO or do you want to roll up your sleeves and be involved on on a regular basis in terms of how the technology is going to run? What is the technology delivering? Do you want to make tweaks to the way that it was built originally? I. Um, so you know, how open is your partner going to be to listen to you right at the end of the day? This is your study. So, yeah, I think those are all things that are really important, whether you want to work on a kind of study by study basis, or you're thinking program wide, you know, this is going to be my partner for the long term, and and again, you know, it's all about building trust with the provider, making sure that you feel comfortable with the recommendations. And it's a, you know, it's like a marriage. I like to call it, right? You have just as much say as your partner. So that's really critical as well, I think. 

Jill Hadel  20:35  
Yeah, absolutely. So we have a customer testimonial video. It's just, you know, a minute or two that will go ahead and play, and then myself and Kat are one of our business development that's been wonderful. We're going to hand out something for you, so I'll turn it over to the video. 

Video Playing  20:56  
Within the Medidata team, there are people who have long, long, 10 years of experience from med device so we can speak the same language, having the kind of experience that Medidata does, and how it's not just the experience that Medidata has, it's how they use that experience and apply it they learn, they continually make things better. One of the reasons that we work with Medidata is because our customers demand it. They've worked in the system for many years, so it's important for us to ensure our customers are happy and comfortable and they have a good usability experience.  In the sites with whom we engage. Medidata, it's a very well known name. If a person sees the Medidata screen splash up on their page. They're familiar with it. They've used it. That's important to us, because there's less of a barrier to entry. It's great support. This trial would not be running if it wasn't to figure out how to do this. Medidata was instrumental in figuring out a way to meet the protocol. I love the the ability to look at some of the new products that Medidata has to assess how well are study sites doing? Encourage newer sites, maybe, or foster relationships with newer hospitals to participate in that research, we need a platform that we can use to continue to be agile. I value the partnership with Medidata in helping us see what are some extra things coming around the corner, and think how we might start to find that into our longer term roadmap. 

Debbie Anderson  22:46  
You want to tell them a little bit about what's on the card? 

Jill Hadel  22:50  
Yes, absolutely. So the card that we handed out, it's double sided. One of the sides has a checklist, just kind of the things that we went over when you are speaking to some of your software partners, that you can maybe it's just a kind of a reminder of what to ask, what to kind of keep in mind as you're having your discussions. There's also white paper available there, and you can kind of select which one if you want. Both, it's completely up to you. And then on the other side, it is our next New York, which is one of our flagship conferences. Oh, I'm sorry. I will say New York. Sorry about the wrong city. So it's in San Francisco coming next month, actually, the eighth of April. We would love to have you attend. It's a great way to kind of come in, where we are updating what metadata is doing, what's kind of the next thing that we're looking into hearing from our clients, or hopefully soon, clients that would like to ask more supportive questions. And we really are there to kind of give back to everybody who's attending. Would love to have you join. If you use that QR code, you can register. And again, if you have any questions, you can always catch us. We'll be here all week. Gina and Kat, they're they're also with our team here. We love to help in any way that we can, and we really appreciate everybody joining

Debbie Anderson  24:11  
questions. Comments open for for any comments, questions, 

Jill Hadel  24:16  
Yeah, sure, Debbie, do you want to take it? Or I'm happy to Okay, kind of. The the question and correct me, if I'm wrong, is that you wanted to kind of know the difference between clinical data and real world, and if there really is a clear definition to that, right? Is that kind of where we're at? Okay? So when you're looking at clinical data, it's part of a clinical study, right? And within your clinical study, you are collecting clinical data, which is the data regarding the patient, right? So that I can see where there'll be some questions into that, but you're collecting the clinical data to go into your clinical study, and then real world data is they're no longer participating in a clinical trial. They've completed participation, or maybe they were a lot. Follow up. We've all had that happen over time. So then the question is, what's the ongoing data? What happened to that patient if they left or after they left a study where maybe their pain score was a two out of 10 and they did great on their final visit, well, what does it look like in five to 10 years when they're not an active participant in a clinical trial, and that's where that real world data comes in, and that can be something as simple as working with datavant receiving that information from that patient. So can you imagine knowing a patient left the study a two out of 10 for their pain score, which was great. Now they're all of a sudden going to their physician more and more often they're going for this inclusion, or what was that inclusion or exclusion criteria prior for the study? Right? So now I have this information that it's 510, years down the road, and this patient is going more often to their pain provider. Maybe they're going to the pharmacy more often, and all of a sudden their oxy codon milligrams are going up the frequency of what they're actually, you know, having to take this. So let's look at this 10 years. 510 years down the road, is this patient still at a two out of 10? Is this something we want to investigate more? Or, Wow, this patient hasn't picked up any oxycodone for 1020, years, we might be onto something. Should we look into another potential marketing study? Is this an R D discussion where we want to expand and look into following up with those patients and see if they want to participate in a 510, year post clinical study? And there's a lot of ways you can go with this real world data, I find it particularly helpful, not only for the patient outcome and long term data, but also if I'm working as the sponsor or the manufacturer, if you will, where am I going to take my next project? Are we going to look to expand our label indication? What pathways can I go into based off of this ongoing real world data that initially started with a patient who participated in our one, two year study that we did, you know, 510, years ago. Where can I now turn my focus and look at what we can invest in more so if the patient's doing great, how can we kind of harness that, and how can we now go in and help more patients and really kind of take our r, d projects in in many different scopes? Does that help? Yes, absolutely. Any other questions.

Debbie Anderson  27:35  
Does this mean everybody has a good idea as to what technology, technology provider you're going to use going forward, or what questions to ask? Because there are no questions except for this gentleman here, yes. 

Audience Question  27:47  
So let's assume I'm doing your device okay. And the world population for these devices, premium, okay? And regulators in many times, bandits and also academic peers want the inclusion of the patients of PGS in Mars.

Jill Hadel  28:11  
Yeah, we definitely did this in my previous role, where we actually had patient ambassadors, so a group of patients that worked with our R and D team and said, We want it blue. We want it to the buttons to be larger. We whatever it may have been, or, you know, the surgical approach. I wish the device was a little bit more seated down. Is that something my physician can do safely just any like a patient insight board, if I will. That's very important for you as the sponsor, and you could do something very simple. You send out a questionnaire to patients at home and just say, Would you like the design to be different? Yes, no. Your team can reach out, or you can consistently have, you know, ongoing questions for them, and collect that, store it in one location. Your team can view it, and you have the automatic insight. They don't have to come into the office. They don't have to pick up the phone. It can be very simple. So as we progress, I know a lot of people don't like being on phone calls anymore. They just like to text or answer things in apps. Those are all things you definitely want to ensure that your software partner has available for you. And then at metadata, we also have something a patient insight board, that they are a group of patients who were participants in clinical trials, and they said This worked really well, or I wish they didn't do it x, y and z. And so we look at that and say, well, if they're if our patients are saying this, the patients for the sponsors are asking the same thing, why aren't we increasing our enrollment? Is this too much of a burden? What's happening? And how can we make this better? So at metadata, we do the same thing. We have patients say, What did you like, not like within your participation? And as a software company, we go ahead and we implement those changes to help our sponsors. So it's very important. And I'm glad you brought that up.

Yeah, any other questions or feedback? All right? Well, we'll give you guys a few minutes back of your precious time. I hope you all enjoy. LSI. It's a great event, so looking forward to speaking with all of you. 

Debbie Anderson  30:19  
Yeah, and if you have questions, come get us. We're around for the week. So appreciate your time. 

Jill Hadel  30:22  
Thank you. 

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