Join our Chief Data & Analytics Officer Silvio Galea, along with Dr. Donna Snyder & Dr. Barbara Bierer to discuss opportunities on the ethical and regulatory challenges regarding artificial intelligence in clinical trials. The discussion is focused through the lens of the IRB review, and how a multi-stakeholder task force led by the Multi-Regional Clinical Trials (MRCT) Center of Brigham and Women’s Hospital and WCG will address the growing need for guidance in this rapidly evolving area of research.
Key Insights:
- Strategic Industry Collaboration
WCG and the MRCT Center formed a multidisciplinary task force to develop resources to address ethical and regulatory challenges during the IRB review of clinical research involving AI.
- The Expanding Role of Machine Learning
Technology is already or becoming involved at nearly every stage of clinical trial development. Software assists with drug discovery, dosing models, and participant recruitment. Investigators also utilize these digital systems for patient-reported outcomes and complex statistical analysis during Phase I or Phase II studies.
- Navigating Ethical and Regulatory Challenges
Innovation is evolving rapidly, and regulations are consistently being developed to address these technological advancements. IRBs are considering difficult questions regarding data privacy, algorithm stability, and informed consent. It’s crucial to prioritize participant safety above all other operational aspects.
Transcript
Introduction:
Welcome to WCG Talks Trials, the podcast where we dive deep into the world of clinical research, sharing the latest trends, insights and best practices from experts across the industry. In each episode of WCG Talks Trials, we’ll explore a different area of the clinical trial industry, while featuring a diverse range of clinical research and medical professionals. If you’re passionate about advancing clinical research, improving patient outcomes and driving health care forward, then WCG Talks Trials is the right podcast for you. We are so glad you could join us today.
Silvio Galea:
Hey everyone. I’m Silvio Galea, Chief Data and Analytics Officer here at WCG, and I’m thrilled to be your host for today’s episode where we’re going to discuss opportunities on the ethical and regulatory challenges regarding artificial intelligence and clinical trials. We’re going to focus this discussion through the lens of the IRB review and how a multi-stakeholder task force led by the MRCT Center and WCG will help address the growing needs for guidance in this rapidly evolving area of research. Before we dive in, let me remind you to subscribe to our podcast and follow us on your favorite listening platforms like Apple podcasts, Spotify, or others, you’ll never miss an episode of WCG Talks Trials. We’re joined today by Dr. Donna Snyder, Executive physician at WCG, and Dr. Barbara Bierer, faculty director of the MRCT Center and Professor of Medicine at Harvard Medical School. So welcome both. Thank you so much for joining us today. And before we get into the details, we’d like to ask to tell us a little bit about your background and how you got to where you are, especially and specifically in the clinical research industry. Dr Bierer could start please,
Barbara Bierer:
Sure. Thank you, wonderful to be here, and thank you for inviting me. My history is starting as a physician, a hematologist, oncologist at the Brigham and Women’s Hospital and Harvard Medical School. I’m now Professor of Medicine at Harvard Medical School, and every 10 years or so, I’ve reinvented myself. So I was a hematologist and then a stem cell transplanter, then I went to the NIH for seven years running an immunology laboratory both at Harvard and the NIH. I came back to be Senior Vice President of Research at the Brigham, where I had responsibility for basic, translational, and clinical research. I had always done clinical trials in my history, and then I had responsibility for the oversight of those trials, and in the context of that responsibility, I realized how little we knew about international clinical trials and how they’re conducted, what the ethical grounding was. And a friend of mine, a lawyer, Mark Barnes and I set up the Multi-Regional clinical trial center of Harvard, initially Harvard, now the Brigham and Women’s Hospital and Harvard, which will abbreviate MRCT center, because it’s a mouthful, which is a research and policy platform and center that looks at emerging issues and unsolved issues in multi-site, multinational clinical trials, we look at the ethics, regulatory environment and conduct of these trials, and then try through a multi stakeholder process where we get people together to address a problem, not to stop at that problem, but to then address actionable and practical solutions. And that is really why we’re excited to be collaborating with WCG on this. So we’ll talk about what this is a little bit later, but let me give the floor to Donna to introduce herself.
Donna Snyder:
Amazing. Thank you. Sure. Yeah, so I think it’s great that we’re getting together today to talk about this topic, and I’m so pleased to have Barbara as part of this call. So I’ve been interested in clinical trials I think since I was a resident, I actually wrote my first protocol and informed consent form when I was a resident, and did training in general academic pediatrics. Expected to go into academia, but then took a detour into private practice, and was in pediatric private practice for a while. I then became interested in research ethics started working for an independent IRB and in that role, really grew that interest in research ethics, serving as an IRB chair and doing a fair amount of expedited review. Because of that interest, and because of all the interactions I had with FDA protocols, I applied for a job at FDA. Ended up starting out at FDA in the Center for Drug Evaluation of research in the Division of pediatrics and maternal health. It was there as a medical reviewer and then as an acting team lead, where I learned more about how FDA applications were formulated and all of the scientific issues behind protocol development. But then, because of my experience in research ethics, I also have a master’s in bioethics, I was asked to lead the pediatric ethics program in the office of pediatric therapeutics. That office is actually in the Office of the Commissioner, and our team was responsible for handling any questions related to human subject protection across the agency. I was there for a little over a decade when I decided to leave and join WCG as its executive position. And I’m so pleased to be able to, you know, be in this role now and use some of this experience I’ve had over time to, you know, really grow the program at WCG.
Silvio Galea:
Amazing. Thank you. Dr. Snyder, given both of your background, so much, I wanted to ask whether it’s getting deep into the bioethics, or going back to my previous life in medical devices and trying to put that through the FDA of compliance process bioethics or others. But let’s focus on AI today, shall we? But before we get into it, the new collaboration between WCG and the MRCT Center. What does it mean? What is it what can we expect to see? What’s What’s the collaboration all about? What are the results coming out of collaboration? All right, so given both of your backgrounds, it’s going to be really hard to not ask about topics from your past that are of particular interest, whether it’s stem cells or bioethics research. But you know, Donna, Barbara, given your extensive careers in the industry, have you worked together in the past?
Donna Syder:
Yes, so I met Barbara when I worked at FDA because of our mutual interest in research ethics, and FDA was involved in a number of projects with the MRCT Center. Most specifically, I worked with Barbara on a project called advancing international pediatric clinical research, and that was a large program which created a fair amount of tools that can be used in the area of pediatric research ethics. And the MRCT also developed a five part webinar series on the topic, and I sat on the working group that helped develop those while I was at FDA, I was also part of the international team. I oversaw the international program within the Office of Pediatric Therapeutics, in addition to my work, running the ethics team so that this particular collaboration was particularly consistent with what we were doing within the Office of Pediatric Therapeutics. But in addition to that, I’ve talked to Barbara on a number of occasions. We’ve met at conferences, and I find her to be a wealth of knowledge on most topics related to Human Subjects Protection and anything in clinical research. So again, as I’ve already said, I’m really excited about this opportunity to partner with MRCT and Barbara on this new collaboration.
Barbara Bierer:
Well, let me just annotate that a tiny bit, which is that I remember the first time I heard about Donna at the FDA. Now you have to understand that all of us in the academic world are sort of both terrified and thrilled when we interact with the FDA. And when I first met her, I was in awe of the sort of range of responsibilities that Donna had on behalf of essentially, all pediatrics, all children, and the medicines that they receive and are allowed to receive in this country. And this country sets the stage for many ways the world. And frankly, I was terrified of Donna until I met her at at a meeting, and the two of us sat down and realized huh, or at least I realized huh, she’s just a person and a wealth of knowledge about this and cares deeply about pediatrics and making sure that the medicines that we provide children are safe and effective, and that that’s the mission going forward. And she always had a true north, and I respected it, so I was delighted when we were able to do this collaboration together.
Silvio Galea:
Sounds great. So about this collaboration between WCG and the MRCT Center? What? What does the collaboration mean? What is it all about? What’s the North Star? What can we expect to see? What are the results?
Barbara Bierer:
Yeah, so let me give you my perspective initially. So whenever the role and function of an IRB is participant protections, making sure that the risk benefit of any protocol that involves human beings considers the ethics, the risks, the benefits of that research, make sure it’s scientifically sound and that the results will be applicable and informative. Whenever we see a new therapy approach technology come forward, we really have to figure out how to apply the principles of bioethics to that technology, and that’s been true for AI. One of the things I’ll say about it is that as soon as you figure out how to approach something in AI, AI has already moved on. So we need to think about not how to restrict the, you know, use and possible real advantage of AI enabled technologies for human health, but rather how to make sure that that’s done appropriately, because it will be done. And what we’re setting out to do is getting a set of experts from all domains, IRBs, academia, technology folks, patient advocates, regulators, people that have been thinking about this in a way that makes sense, but is permissive of AI research under the right conditions, and to really think through, how is this research different than other research we’re comfortable with, just because the technology is different. So we’re doing that first by pulling together this multi stakeholder work group, and then thinking about the principles that we want to apply. We can get to that a little later, and then discussing a number of different cases that have come before, IRBs in the past and thinking about how should an IRB really address those issues comprehensively, thoughtfully and in a way that applies those principles for the protection of human participants, and that’s really the goal of this, to create tools that IRBs can use, which will reflect then to the investigator community and what they need, information they need to provide to the IRB in order to do the review comprehensively, and that person who writes the protocol, or the company that submits the protocol, should be providing information that equips the IRB to do their job. And then the IRB should be doing a job, you know, that is thoughtful and and applying those principles to the case before it so that’s really what this is about. Donna, do you want to add anything?
Donna Snyder:
Sure? I was just going to say. So, you know, these tools will be created by our work with the MRCT Center, being made widely available. So they’re not necessarily for one specific group use. They’ll be housed on the MRCT website, but WCG will be involved in disseminating, promoting the tools for use. And I will say that the reason that we went to MRCT with this question is because we were starting to grapple with some of these issues with IRB review, and we realized that we really needed to think about this, and, you know, more focused way so that we could be providing the best reviews for our protocols as possible under the WCG umbrella, but at the same time, also wanted to contribute to general good across all of clinical research in terms of, you know, we know everybody else is grappling with these issues too, and see if we could come up with some specific and general guidelines that we all could follow so we can be consistent.
Barbara Bierer:
And let me just let me just add. You know, I really appreciated WCG bringing this to us to coordinate the work group, but it is not a product of WCG and the MRCT Center. It is a product of 20 people, 25 people, representing all sorts of different stakeholders and with all sorts of different expertise coming together to put their best thinking forward. So while we’re here talking about it, it reflects the work of all.
Silvio Galea:
So if I put myself back into a prior life where I was working at a AI enabled medical device company, how would I be able to use what this collaboration is providing? What are the things that will be tangible for me to apply in preparation for the protocol, for the trial or to process health certification and testing?
Donna Snyder:
So I can just say, and I think right now, we’re working on these tools. We’re trying to decide what we do need to move forward. So the working group is in the process now of looking at the landscape and coming up with some questions and some deliverables that will come out of the working group, and hopefully we’ll have the answer to that question sometime in the next few months.
Barbara Bierer:
And our hope is that we’d be providing you with a view or lens as to how the IRB is thinking about this, so that you can do the work to bring forward the information that makes us feel one that you know you’re what you’re doing, and are thinking about the experiment on humans appropriately and with the guardrails in place to make it safe for them and transparent, and all the rest of the pieces that go into any protocol that we do.
Silvio Galea:
Yeah, there’s just such a deep thirst for information, especially in the smaller start-up community, and the medical devices are in the AI space, as AI becomes complementary to devices out there, or AI as a medical device, or software as a medical device, there’s just a vibrant community out there of discussions, of information sharing, and I do believe that the outcomes of this collaboration will be highly beneficial to that smaller and larger industry as a whole.
Barbara Bierer:
The other group is the hospitals and health systems themselves are applying AI tools and developing AI tools for management of it their patient population, and have not traditionally thought about some of those as research protocols when they’re really to improve either operations or the care of their patients. So also important for us to be thinking about that
Silvio Galea:
We’re probably starting to see this already, right? And how are you seeing AI making its way into clinical trials and mission protocols. How is it represented in the protocols?
Donna Snyder:
Go ahead and start with this. So I think AI is involved in all areas of protocol development, even before you get to the point where you have a written protocol. AI may have been involved in the development of that drug product, or that device studied in that protocol. So AI is being used in the area of drug discovery to find candidates where a product might be more likely to you know, and things might be more likely to respond to a product. AI can be used to search through nonclinical information to see whether or not, again, the product might be beneficial. AI can be used to establish dosing, to know what dose to start out with, and this is particularly important in pediatric trials, because you’re going to start with a lower dose often, or a different dose in kids than you would in adults. So you can model those doses and determine where you started the protocol. Then when you have the protocol written, AI can be used for recruitment. So rather than an investigator needing to go through all of their medical records and look for patients who might meet the eligibility criteria, an AI algorithm can comb those records and find those individuals much more quickly. Of course, the human will likely need to reach out to them, to find them and talk to them about the study. AI can be used to enrich the population that may be enrolled in a trial. So if you’re looking for a patient population that might have a specific biomarker or specific genetic trait, then those patients or those participants may be more likely to respond to the drug or to the product, and so therefore, if you can find those individuals, you may be able to facilitate drug development, conduct a smaller trial and move things forward more quickly. Then when we get to the protocol stage, you know, there are tools within protocols that are being used now that that may utilize, AI. Think, smartwatch or app for your phone where you have a patient reported outcome that’s loaded into a phone, and the individual receives a reminder that they need to complete it, rather than needing to go into a center to do those types of assessments. And then there’s even talk, although I don’t know if this is being used widely yet, about having bots that remind participants to take their medication or talk to them about how to care for their disease. Now, the flip side of this is for people who are technologically adverse, they may feel that it’s a little bit uncomfortable to have to use those tools. So there may be some participants who are turned off by those types of tools. But I think as we’re becoming more comfortable with these types of things in our daily life, it’s more likely that those are going to facilitate research. And then when you get down to the protocol itself, what’s being studied. You know, Silvio, you’ve already talked about software as a medical device. AI has been used as in software for many years now. That’s probably where AI was most first seen in terms of research and clinical trials, but now we’re seeing protocols coming in that are specifically looking at AI algorithms to determine whether or not the algorithm might be superior, say, for example, to a human conducting some sort of assessment. So for example, the AI may read an x ray and give an assessment in terms of whether or not that individual has that particular condition. Right now, those protocols are in a state where they’re being verified. So the AI may look at the x ray, but oftentimes there’s a human who is also assessing that X ray or that scan, or whatever it happens to be, to see whether or not if there’s agreement there. So those are all the areas right now, actually, there’s one other statistical analysis of protocols. So if you have disparate data sets from particular sites, say, for example, first events, those can be pulled together by AI, would take a statistician many more hours to do it than AI can do it, if you have an algorithm that can do that. So these are just some things to think about. It’s obviously not all inclusive. And I know Sylvio, you have some interest in this area, so I don’t know if you have anything to add about some type of monitoring that might be done in trial.
Silvio Galea:
Yeah. Indeed, I think that the smart devices making their way into just the day to day consumer space, being verified and then being used for data collection or supplemental reminders, as you noted before. Dr. Snyder, whether it’s notification or reminder to help with adherence continuous collection and processing of data, right? Allows us to potentially identify outliers, triggering alerts for safety, a lot of opportunities, but that comes with a drawback. It’s another technology we’re introducing, right? We all know in the clinical trial space, we’re just drowning in the amount of tools, integration, data, vendors, and now we’re throwing another one that’s like shooting data out in real time. So it’s just going to be another technology to integrate. And then, from the patient perspective, is that a burden, right? Is it another device that they have to add to, you know, the 15 things they plug in at night, whether it’s like their phone or their headphones or whatever else. Now we have this other thing that has to be taken care of and cared for, and it might not be at the same level of usability or modernity as a consumer device is. So it’s a bit of a double-edged sword, so to say. And I think we just need to be a little strategic with the deployment and use to make sure that it’s set up for overall patient and researcher for success, and not just something that we throw out there because it’s cool.
Barbara Bierer:
So let me bring this back to the project that we’re doing this, because we’ve covered a lot of ground here. So one thing I’ll say is, you know, the IRBs really don’t get involved in preclinical data, sort of, how is the product identified? Are there areas of molecule that would be more predictive of being immunogenic or something? None of that comes to the IRB. And similarly, there are many things that happen, which also don’t come to an IRB, if there’s de identified or anonymized data that’s being analyzed, we don’t know about that as an IRB, we only know if it’s identifiable or involves a human being, and that’s a pretty restricted set of questions, you know, so we can talk about that a little bit, but one of the things that I’m sensitive to is that I do think IRB should be thinking about is this question of participant burden and the complexity. Can we use their own smartphone rather than introducing yet another device? And if you do decide to do that because it’s easier for people, is the data going to be the same if you’re collecting it from one device versus a different kind of device. Can a participant turn off those reminders, and is that going to affect the data? How much choice can we give people? And then there’s all sorts of other questions that I think IRB should be thinking about, like if we use AI to scan the medical records to find people that would be eligible for the trial. Couple of things to think about there, one now you’re going to go cold call a patient in a hospital system to say, Would you like to be in a trial, and they’ll be like, how did you know that I that I’ve got this disease, you know? So what’s our public responsibility to be telling the public that we can do this? You can, you may be hearing from us in the future. Or can they opt out of that, and if they are able to opt out of that, is that going to change the representation in the clinical trial? Is there bias in terms of the selection of participants? These kinds of things are exactly, in my opinion, what the IRB should be worrying about, because those are going to impact the public, you know, acceptability, but also the perception of research and the research community, and we want to align the public with what we’re doing. So it’s, it’s really to improve public health. So you know, lots to talk about there.
Silvio Galea:
There’s certainly a big opportunity for raising awareness and allowing individuals to opt in, right? I think that there’s so much opportunity there, both from the researcher as well as the public side, to make this, you know, a collaboration for the greater good. It just doesn’t feel like there’s, there’s a single entry point, but all those things we could probably touch on in a dedicated topic, going back to something you mentioned before, in terms of,
Barbara Bierer:
Let me just let me just say I think we should, because, you know, if you, if you say, you can opt in, which I think is a thoughtful approach, you have to make sure that the people who do opt in represent the general public and have the diverse representation that you’re going to then apply your product or your tool to after it’s approved, because if it’s not reflective of the general population, you may, you may both develop the AI algorithm and test it on a select population that it and it may work differently in other populations. So those are the kinds of intersection of ethics, science, application, generalizability that I think is challenging.
Silvio Galea:
Yeah, it certainly is something that we in the AI community focus on in terms of making sure that we keep an eye out for bias. We’ve seen examples in the media on some of these algorithms being biased, but from an IRB perspective, what are some of the AI principles we need to be aware of in the context of consent, privacy, by the transparency, protecting participants from harm. We have this new toolkit now, and we need to make sure we put it in through the lens of safety, which is key function of the IRB. What do we need to be aware of?
Barbara Bierer:
Let me start a little bit, because I’ve already been starting down this path. So I think, so, I think we really need to engage the public in this general area, because most people don’t really understand how their data is used. And every time they go to, you know, search something on Google, that data is captured in an identifiable way that they Google Analytics is doing work that doesn’t come to the IRB, because they’re, you know. So we’ve got to make sure that people are what we’ll call data literate. Then you get to the point where I think, as in health and public health, we should be transparent with what we’re doing, not that everything needs permission, and we should be sure that people understand how data is used, particularly general data, you know, billions of data points are necessary. You’re not going to get billions of consent, but when it touches the patient, then or the participant, then, I think we need to be careful about what we’re asking and how clear we are, and make sure that we do tell participants about how AI is, has enabled the trial, or is the sort of focus of the scientific question if you’re developing an algorithm to predict cancer, that person should know that you’re doing that, because if you predict cancer and you find it, you want to know whether they want to know about it, whether they want to know what that prediction has given them, and do they have a right to it? Well, you know, that’s a different conversation entirely, because the algorithm is not yet approved. It’s not just tested the efficacious, safe. So will you tell the participant what you might have found and worry them or not worry them? You know, those are the kinds of questions that are so complicated. So I think we need to be particularly careful about how we treat the data and make sure that when we collect it, transfer it, store it and use it. It’s confidential and patient privacy is protected. One of the problems with having people answer questions on their own smartphone is that that data will become stored and potentially accessible through other means, and doesn’t have the guardrails in place that we would like to see and what you answer in a clinical trial protocol about your emotional self or medical state or whatever is completely different than what you might otherwise put in a smartphone for public dissemination. So we do need to protect participants from harm and where AI tools are themselves not fixed, but learning in the context of the protocol, we have to make sure that we know when that algorithm changes in a way that might impact patient safety. So lots of pieces where, I think going forward, we’re going to need some better IT, understanding and sophistication on the IRB. It’s not just about ethics, it’s about understanding the technologies themselves. So those are the kinds of things we’re thinking about, hugely complex, but very, very relevant.
Silvio Galea:
Are there any initiatives being put forth to provide oversight of AI development and implementation in the research space? I mean, I think a lot of us take it for granted the price movement in the industry. We know what’s ethnically right, what we could do, what we shouldn’t do, etc. But those who are new to the industry may, you know, inadvertently slip. So how are we helping with protecting and securing that information.
Donna Snyder:
So I’ll start with this one so and as Barbara was talking, I was thinking about the regulations that we have in place right now and how we define minimal risk. And you know, some of the youth protocols that are coming through might be considered to be minimal risk and even eligible for waivers of informed consent. But because of this future use of information that can arise out of some of these protocols, and because the fact that there could say, for example, like we talked about the cancer example, you know that individuals could be identified at risk for certain diseases. You know it may not be appropriate in those cases to issue, say, a waiver of informed consent. And so there are different considerations there. The issue that we have right now is, as you know, AI is moving rapidly ahead, and it’s really hard to keep pace with that. So There currently are no regulations that direct IRBs or researchers, you know, to consider how to use, you know, AI might, how AI might be incorporated into research. I mean, there are larger initiatives, you know, we know about the executive order that the President has issued in October of 2023, and the European Union has an AI act that was agreed to in parliament in 2023 and these will create broader government regulations for AI development, but really don’t address the research issues. So I think that that’s something we need to focus on, and that’s one of the reasons for creating this working group, and working with MRCT center, is to come up with some guidelines that may help with some of these issues that we’re grappling with as the rest of the industry, government, etc, “catches up” with creating some guidelines that will really be helpful in this area, FDA has issued position papers on the use of AI and focus elements and for devices. FDA has a number of draft guidances out there use of software as a medical device, and working in collaboration with the International Medical Device regulators forum, or IMDRF, to develop guidelines in AI and machine learning, but all these are in the process now of being developed, and you know, there really isn’t anything out there right now. So, you know, I think the onus is on us to think about this and to really try to come up with some tools that might be helpful for IRB.
Barbara Bierer:
And I agree completely. But let me back up to Silvio’s question. You know, you’re you’re sensitive to these issues as they arise? Having been in the field a long time, I’m not sure that everybody is. You know, a lot of data scientists that I interact with in bioinformaticians, think they’re, you know, of data impersonal as a date, you know, massive data collections and sort of how to use it, but at the end of every data point that we’re talking about is a person. And I think that in addition to all of the things that Donna mentioned that we should be thinking about how to, you know, sensitize the data scientists to think about these issues, regardless of whether they come forward to the IRB, We have to do a much better job not of educating because it’s not a one way trip, it’s a bilateral learning environment where we think about that interaction in a dynamic and forward looking way. I don’t know whether one can build the safety controls into this technology themselves. But there’s always an underbelly to these technologies, and we have to make sure that people are thinking about use and abuse, intended use and non intended use, thinking about the that the fact that this data represents our population and people and and that’s never going to come before an IRB that we see only the tip of the iceberg. We’re going to start with trying to develop these principles for that tip of the iceberg. But in general, we have a greater responsibility.
Silivo Galea:
Indeed, we’re going to be hearing a lot more about responsible AI in the coming orders and years where the many corporate groups are having very deep discussions right now about responsible AI within their own corporations. We need to also put those guidelines out for those who are researching on behalf of individuals. You know, AI, as you mentioned before, is moving faster than then. I think we have time to, you know, I don’t want to say regulate, but, you know, in some ways, we don’t want to restrict progress.
Barbara Bierer:
That’s exactly right.
Silivo Galea:
Other side, we have to be responsible with how it’s used and what it’s creating, and how those outcomes are going to be interpreted by an individual. So I think that we’re going to close off on a great, I think, question here, which, you know, we’ll look forward to the MRCT center and WCG to put together some of these guiding principles for those of us in the technology field to ensure we go forward in a safe and effective way. Before we close any closing commentary. Dr. Bierer, Dr. Snyder,
Barbara Bierer:
No, I’m, I’m really thankful that you, you know, are hosting this podcast. I think it’s the beginning of a much longer conversation, and happy to be part of it. And thank you.
Silivo Galea:
Thank you.
Donna Snyder:
And I was also going to say that I just want us to remember that it’s not just WCG and MRCT Center. It also is a number of other great minds getting together to talk about these issues. So I’m looking forward to seeing what comes out of this project and collaboration, but I think it’s going to be great. Thank you
Silvio Galea:
So thank you so much Dr. Donna Snyder and Dr. Barbara Brierer for joining us today on this episode of WCG Talks Trials. Thanks to our listeners for tuning in. And if you have any questions or would like more information about this or other topics, visit WCGClinical.com, engage with us on LinkedIn, or other channels, and we really hope that you found this episode insightful, and look forward to having you join us for future episodes of WCG Talks Trials. Bye for now.
