Data Beyond Trials Unlocking Real-World Evidence for Regulatory Success

Hello! Good morning. Good afternoon. Welcome, everyone to medtech leading voice. And yoner Institute. Presenting today's webinar on real world data with Dr. Johannes Goldman, and he is manager of clinical affairs at yoner Institute in Germany. thank you for joining us. We were talking before the call, and he shared some fun facts which I might share with you. He has 2 little kids, and he also has a Youtube channel not related to his job. I'm going to drop that into the into the chat function. Any of you want to follow him on Youtube, not talking about clinical affairs? Then please, please do so.

Dr. Goldman, welcome, and I'm going to turn it over to you. Oh, wait before I do that. I have a number of housekeeping announcements that I totally forgot, because I got too excited about what we were talking about. The housekeeping announcements which I will put into the chat are number one. This webinar will be recorded, and the webinar will be made available tomorrow at the same time. To all of you who have registered along with a link to his slides. The slides are downloadable, but you have to hover over the little down arrow in the left hand side. Linkedin does not make it easy to download slides, so that said, next, use the Q. And a function for questions. Use the chat function for messages. Feel free to message me throughout the

thing and through the throughout the webinar. and to ask questions using the Q&A function which we'll try to get to all the questions, but last time we had so many questions that we couldn't get to all of them, we'll try to follow up with you individually, if your question is not answered. Next, if you would like certificate of attendance for the program. please put your name and email address in the chat. So you don't need to write anything else, just, you know, if you have your full name, as you'd like it to appear on the thing, it takes 2 or 3 days for us to make these. This has to be done manually. So please be patient.

Lastly, I'm going to put a number of other links, including a link to this fantastic, new, free version of regulatory Pms radar post-market surveillance radar from yoner Institute which allows you to search several databases for free. This is a free, free version of the product. They also have paid versions. I'm going to put that in there. I encourage you to take advantage of this permanently free offer. This is not a free trial. This is a free version of the product. It's amazing. So with that in mind, I think those are all my spammy announcements, oh, and part 3 of this Furna regulation market access in the EU with Dr. Bettina Martin on April second. At the same time as this webinar, there'll be links to all of this. So please

do your thing. Sign up. Participate in the poll, which is going to take place after his presentation before the Q. And A. And the survey after the call. That's it.

So thank you very much for the introduction and also for the small commercial for my Youtube channel. I was just laughing after you do it. So thank you very much. So 1st of all, I'm gonna share my screen that you can see the presentation so everybody can see it. So also welcome from my side. If you haven't done it already, arm yourself with some coffee or biscuits. So the next 40 min I guess we will talk about the topic of real world evidence. In general. This is the second part, as already mentioned by Sean for this Webinar series to Master EU regulatory framework. I thank you for your taking the time and joining this webinar. The topic will be data beyond trial. So unlocking real world evidence for regulatory success.

As mentioned. My name is Dr. Jans Goldman. I'm a clinical expert at the Owner Institute for 3 and a half years, so I've been most of the time doing clinical strategies and clinical evaluations. But I'm also an expert for clinical investigation and case number planning. So if you have additional questions after this, seminar don't hesitate to forward them to me. I also was a study coordinator for 6 years, so I've been working on clinical trials also, for on the pharmaceutical field and the medical device field. So I know the pain from a manufacturer perspective to get a research product finished up from the documentation to the technical documentation you need for the Ce marked registration.

So to get it going, I just wanted to add my personal email address, if beyond this, webinar, you have any questions to forward. Please don't hesitate to contact me, or if you want to talk to a different expert in our Institute, you can choose the Clinical Affairs Department address which is set below it, and if you have general questions concerning your technical documentation, you can use our homepage. Address the info at Yona Institute. So, and then you will be forwarded to the expert which you were asking for in the field there, where you have the question. So today we're going to cover 4 different topics. The 1st topic will be, what is the concept of real world evidence? What are the sources and what you can do about it. Then we will go into the regulatory framework. What is the current situation for real world evidence? What might be limitations, future outlooks on the development stage.

Then we will go into clinical evidence generation. Some strategies concerning your Pmcf. Or which is not so in common in silico trials. So simulation studies which you also can use for getting clinical evidence, and in the end I will give you some hints concerning how you can adapt certain strategies for implementing your medical product on the EU market. So let's get started right in the 1st chapter, what is real world evidence? So real world evidence are data related to patient health status or the delivery of health care which, routinely collected from a rarity of sources other than traditional clinical trials. And there are a bunch of sources. I will show you the slide now, so don't take in. There's really a variety of sources, and we will go briefly through them one by one.

I think the most useful source are electronical and mathematical records, because, there you can list. In the clinics. There are demographics that they list. You have access to lab test results. The 2 diagnoses. There may be pictures for your histology, for ideology, or the the whole family history of the patient is on full display, so you can use it for your medical device to get some background information. Other source would be primary data collections like observational studies. So you watch directly into the routine business of the healthcare unit. If it's clinics, if it's different physician types, you can use this data as well.

Also patient and disease registries are useful. I strongly recommend the site from the National Institute of Health, which has a list of different registry types depending on the disease you're working with. If you want to have access to that, it's free. So it's just visit the homepage at that point. and other possibilities are public health surveys, patient surveys, provider surveys from healthcare. They have a huge impact. You can do pragmatic trials which are clinical trials that focus on the correlation between treatment and outcome in the real world health system. You can use social media like patient communities. X Facebook. What you prefer, also medicinal procs. If you get data out of that, you can use them for real world evidence.

The most developing field are patient, generated health data. That's our data that are gathered by mobile health fitness trackers or wearable devices, everything that is considered measuring activity or body function that you can use as real world evidence as well. Then there are also hybrid data which, from observational studies and insurance data which you can combine with literature or molecular profiling, you can relate to environmental factors. Climate is a factor that you can be involved. Pollution is a factor, lifestyle factors, and in the end also administratively claims records or medical records.

As you can see, a bunch of different sources available. But the general message always is that real world evidence gives you evidence regarding the usage of your product and also the potential benefits and the risks. And this is derived from the analysis of this kind data. So now you have all the sources where you can take out real world evidence. What are the strategic approaches that you can use one. So 1st of all, I think 3 points are very important. You have to choose the right source. What I mean is, 1st of all, the institution you want to obtain this data from. You don't have to know if you need contract to get access to raw data?

Who is checking the quality at the data side? Who performs the statistical analysis? What are the qualifications of the staff that is in the center are patient data involved is data, privacy or security, maybe an issue. These are all aspects you have to think prior before really getting to the source of the real world evidence. Secondly, the timeline you want to achieve this kind of data, you have to consider, because, on the one hand, you can get huge amount of data like from fitness trackers in a very short amount of time. Or if you plan on Pmcf. Surveys or other surveys, you might have to calculate 2 or 3 months in getting this results. So you really have to have a timeline when you want to have this kind of data.

And the most I think impactful point is the costs, of course. So what is your budget for this kind of real world evidence? Do you have enough resources in your company, that, and and enough stuff to prepare, and good good analysis, good preparation of the needed protocols for this thing, and do you get feedback from that? So these are the 3 main points, and the reason why I present it, because it's completely different to the ones you've receiving. If you plan a traditional clinical trial for those of you who have been working in the field with classical clinical trials, know that if you have a clinical trial in several countries with several centers involved, it's a very cost.

a very expensive, and also time consuming strategy to deal with sometimes. If if you have good personnel, you can have it underneath 1 million. But normally you calculate one to 2 million of dollars of cost, and 1, 2 to 3 years of time. Concerning the risk of your medical device, you can also perform other approaches which might be a bit faster and not so expensive. If you use registry studies or surveys that might fulfill already the evidence level that you need for your medical device, you can also do it in a much faster way. So the general goal is to have a long-term strategy which refines high data, high quality data with a fraction of the cost.

To sum up some of the benefits you might have using real world evidence, the FDA makes a small list. So the understanding of the device function in the real world is one of the benefits you see, and the impact on risks on the benefit that the medical device is delivering. You also have the possibility in the real world evidence setting that you get additional data which you don't get in these artificial conditions, like the classical clinical trial setting. You also have the possibility to increase your network in contacting new partners in contacting new centers and patients and increase your net network for coming, for post-market surveillance. You can reduce the time and the cost

to answer important questions concerning your medical device and also set up for future device modification and new technology developments. Also, you can be better aligned in evidence generation with innovation cycles. Now, you know the benefits of real world evidence. So let's look at the the things this real world evidence can be used for typical uses of real world evidence are gathering data for marketing claims, additional claims where you need specific types. Sometimes, when you have approval studies, you cannot fill all marketing claims with clinical data. So you aim for additional data to set up the claims or alter your indication, or even

alter your intended use. Another approach would be, if you have high risk products, or if you have products like permanent implants who have a long shelf life in the patient themselves, and that you can do post-approval monitoring because you have to ensure that even after 3 or 5 or 10 years. The device is still functioning the way you intended it to function. then the classical approach of device traceability from the post market surveillance side. So you're collecting complaints from the market customer feedback, but also the sales numbers. The sales number are also especially important, considering the state of the art, it gives you insight. If the

product is still the gold standard of the market, if it's increasing, decreasing, you can correct to, you can react to competitors. And this gives you more insight of what is happening in the market, and how future developments might be. The 4th thing where it's typical use for the real world evidence is in lower risk devices. So devices with not a direct clinical benefit, something like a mouse, Bartula, a blood glucose meter, a patient position device where you don't have to have clinical benefits as in the direct form. And in this time a real world evidence might be enough.

together with non-clinical data and post-market labor to have insufficient data for this device. I wanted to share you also some more rare abilities to address real world evidence. So reward address also can be used for orphan devices or humanitarian use. What does that mean? Often devices are normally used for rare diseases. So in in FDA the definition is that there are no more than 8,000 patients per year, or cases per year. Through this through this disease. So it's very difficult to get enough patients for a traditional clinical trial. So you have to use real world evidence to support some of the claims, some of the parameters that you have to define for your medical device.

Also, if you have vulnerable groups like pediatrics or pregnant people, it's sometimes unethical to perform a classical clinical trial concerning the risk that they have been taking for this kind of patients. So you have to use real world data to ensure that your product is still safe and functions the way you plan it to work. Of course you can also use it for future generations. Another aspect which I had discussed yesterday with another customer is to use real world evidence as a control arm for your clinical trial. So if you have enough data for your state of the art, and you have enough real world data. You can also decrease the cost of your initial classical trial if you set up certain parameters that already

have been published for state of the art and the literature. So you can use that as a control arm and don't have to set up a 2 armed study for that. It's a really good way of reducing your costs, and also the time this study will need. Then also you can set up more predictable clinical evidence requirements based on the available knowledge and also understand the influence of human factors of usability. Sometimes, if a human is involved, it doesn't work the way as it planned. Or you have a software where you have learning curves, even when you have physicians who are dealing with certain pictures, and they know, after the 3rd or 4th time, what the what the results may look like. You have to adapt this in your risk management file, and also into your

technical documentation. And also you can track device interactions. It's not always gold. What shines. I don't know if it's the right wording in Germany. There's, there's, there's a sentence concerning this. There's also a lot of hurdles and limitations to this kind of data, because you have to know real world evidence. Data are always observational, so they won't be taken under control settings. And so you might get access to poor data or their unstructured data, or some of the values might be wrong. So the general quality of these kind of data are sometimes questionable. Also, there's no standardization for this kind of data might be timeless also, the robustness is sometimes questionable.

The methodology is often linked also to different biases. the methodology itself is not so well understood by the people, and you also have limited capacity to really review this kind of data concerning on which source you use for real world evidence to collect it in general at the moment. The situation is also so that the trust to this kind of data is relatively low, and for the strategy, and also depending on how good of a transparency you have for the original raw data. Also the stakeholder themselves sometimes don't trust what these real world evidence might show in general, and that's what the ending message of the 1st chapter would be is that there is a lack of harmonization, as you will see, there were not. There are not a lot of guidance documents concerning this kind of topics. So there is still an ongoing process on how to handle this situation.

So that was the 1st 1st chapter. So let's go briefly to the second one. It's a bit shorter, I I promise so go to the regulatory framework. I wanted to show you this timeline for a real world evidence for the activities and the guidelines from the Emf that was shared 2023, because it should show you 2 things. One thing is the the the 1st guideline was published in 2017. So it's not long ago that these guidelines are available, and, as you can see from the regions, they're just beginning to plan certain guidelines or participate in the legislatory framework that is involved in this regulation. So

dealing with real world evidence, you are really in a development field. And you have to look from area to area, what are specific conditions. So let's look through some of the areas. Korea is one of the areas where real world evidence was increasing for regulatory decision making the Ministry of Food and drug safety, set out a guidance document in 2020 which they regulate approval studies focusing on data, quality and reliability and also appropriate methodologies for generating real world evidence. and they use it for a post-market surveillance and for rare diseases. The same approach was done by the pharmaceutical and medical device agency of Japan.

Japan was one of the pioneers concerning real world Evidence generation. They set up their guidance document in 2018, also focusing on post-market studies and device reexaminations, and they use it for safety assessments, long-term efficiency studies and rare diseases. The tga, the 3rd party good agency in Australia. slowly adapting evidence to clinical to real world evidence. Unfortunately, they don't have published a own guideline for Australia, but the internalization is that the Australian try to to be in the same standard as the FDA and the Europe is setting up

in 2,023. There was a launch concerning global standardization of real world evidence, but the outcomes of this initiative is still to come. The global leader in real world evidence and the regulation on it is Us. And the FDA. They released a framework of real world evidence in 2018, followed by a detailed guidance document on the use of real world evidence to support regulatory decisions, including device approvals and post-market requirements. And these documents got updated in 2021 which they issued a guidance document concerning real world evidence, real world data and real world evidence.

focusing on data, quality study, design, and also the use of real whatevers in regulatory submission. They have round about 14 pages concerning real world evidence, and also in the annex scenes. There are checklists and guidances, and also examples on successfully submitted real world evidence. So if if you plan to do it. I would strongly advise you to look this kind of guidance up in Europe. It's a bit different. Europe. The Mdr. Doesn't really hasn't written anything concerning real world evidence as a whole. In 2,020 the medical device coordination group with some guidelines with to legacy and

Pmcf templates, added some some sentences to real how to handle with real world evidence. But Europe is still in the phase where it's uncertain how they should implement real world evidence in the general regulatory pathway. They also joined, like Australia, this global approach of getting real world evidence to the persons, to the people. the last one in China, the National Medicinal Product Agency. They started their regulation in 2,019 and released a guidance document, also focusing on post-market and surveillance studies and rare diseases, and also submitted some pilot regions where they plan to do submission processes with real world evidence. So that's the regulatory basement out of that.

So we have the second part over. Let's go to the clinical Evidence generation Strategy and Pmcf. And in silico trials. So if you perform clinical generation strategies. I think the 4 there are 4 key questions that you have to answer. 1st of all, you have to ensure that you have the right quality of the data concerning the risk analysis of your medical device. If you have a low risk device, real world evidence might be sufficient to get enough data. If you have high risks there, you won't be able to evade any kind of classical clinical trial. The second thing you have to look at is the statistical methodology methodology around it. Consider enough patients involved for your studies. Also consider that there might be dropout rates from 10 to 20%. If you plan on studies that take longer than 1, 2, 3 years. You have to calculate this for every year.

Also, that's the 3rd point. You have to communicate transparently to authorities and notified bodies to ensure that you don't have any form of cherry picking. This is also for your state of the art. You have to present all data involved in the study, and not only the good ones that you want to choose for your medical device, and in the end. The last point, I think it's clear. If you write your study protocol or study design, you should design it as that somebody else who reads your protocol is able to replicate your data. That should be fine. So in general, if you have classical approaches and classical clinical trials, and you go to Europe. The Mdr. Have a lot of articles involved. It's in Chapter 6, from 62 to 82, and also in annex scene 15. There there are the general requirements, requirements for implementation.

how the authorization procedure works with the authorities, what you should do when you have a significant change, what are the fees that you have to pay what you should do if Regulence reporting is required. Ethical principles, and also your obligation as a sponsor as well as regulations for Pmcf studies and other clinical trials. This is for the European level. but you also have to consider on where you're plan to do the study in which country that also national laws apply. I showed you here 3 laws involved for Germany, Austria, and Switzerland, so that national laws supplement that the already in place laws from the Mdr. Concerning additional information for the sponsor, how the insurance for the patients are handled.

what are the consents that you have to fill out for the patient. What are the requirements for the principal investigators when you're allowed to start the clinical trial and the procedure with the Ethics Committee? So that's the background for a classical clinical trial. If you have a classical clinical trial, it's conformative. So the goal of these kind of trials is always to show for your medical device that it functions the way you intended to, that it is safe, and that it has a benefit for the health candidate, and this are done on this classical trials, which we already showed there. Higher costs, longer durations, very few data. But on a control setting.

In contrast to this are Pmcf. Studies. Pmcf. Studies are not. If they, if your mark have to start it that way. If you have medical device, which is on the market which you have your Ce. Marked instructive, and you want to plan a study within the intended use of this market. You can do Pmcf. Studies. The Mdr. Would not apply in this kind of condition, but the national laws would apply for clinical investigations. The design would always be observational. So you would watch what is happening in the routine, so you won't have any treatment, groups or person on that. But you would have larger numbers of patients and a shorter amount of study time. So maybe I give you 2 examples out of this. You can use like clinical, observational studies, where where you just

focus on the routine business and see how your medical device is normally used in in the field, or you make register studies on a retrospective way where you can go through different registers. Look up the data and invent your study protocol to that in general Pms and Pmcf. So post-market surveillance and post-mium market clinical follow-up are settled in the India from Article 83 to 87 in general, you have to say Pms is more of a reactive part of it. If there's feedback coming back from the market. If you have any maintaining stuff, repell reports coming back, it's kind of the way you're reacting to it.

And Pmcf. And Pmcf. Activities are more focused on proactively gathering data to ensure the benefit of your device and also to decrease residual risk that you might have concerning on which type of product you have. And also. yeah, mainly mainly the risk function on that one. There's a lot of stuff. So you have a lot of guidance documents which help you to get a good feeling for that. I strongly advise you to read the Med. F. 2 12.3 in revision. 2. This gives you outlines when the Pmcf. Study is mandatory for you to do also in the Mdr. The annex in 14 and Part B. You have the reference for Pmcf. And also 2 guidance documents for the Pmcf plan and Pmcf. Report from the Mdc.

Group from 2027 and 2028. And also you can use the international standard from the Imdif, for in general explanation of Pmcf. Studies. So let's ask, when is the Pem Pmcf. Study mandatory. the Medef lists 7 cases. So if your Ce marked is based on equivalence, you are mandatory to a Pmcf. Study afterwards, if the product is market. If you have a novel technology, and the state of the art is not clear, you are found to do Pmcf studies. If you do significant changes to your product also have to do Pmcf. Studies.

If the long-term safety and unperformance are unknown, or if you have a high risk, population like in implants with or with active devices, non-active implants. You have to perform Pmcf studies. If there's maybe a risk identified from your Pmcf, so you get customer feedbacks that some risks are met. Then you have to do Pmcf. Study to ensure that the risk is not a trend and also to assess performance and our safety and the device for more representative populations. Or if you have any clinical event occurring, then you can have to. Then you also have to do a Pmcf study. Now you would ask yourself, okay, that's that's the the topics where I have to do pieces. Are there topics where I don't have to do. Pmcf. Study. Yes, as well.

So if you have a device which is well established and the history of safe and effective use, you don't have to. You can exclude Pmcf activities. If the pre-market clinical evaluation provides you sufficient data for evidence of safety and performance. You also won't have to do a Pmcf. Study, or if there's no new risks or uncertainties identified during your post-market surveillance, then you also don't have to do clinical trial. So what is important following proper pre-market clinical evaluation. The decision to conduct Pmcf study must be based on the indefication of possible residual risk or unclarities on long-term clinical performance that may impact the benefit risk ratio.

Why is this important? Why do I present it? Because real world evidence and Pmcf. Are kind of combined because both of them have the same goal in the Pmcf. Your objective is to proactively collect evaluate clinical data from the use in or on humans. You also want to have to confirm your clinical safety and performance of the medical birth throughout the expected lifetime. You have to ensure that there's a continued acceptability of your identified risk. You have to detect emerging risks on the basis of factual evidence and also important detect off-label use or misuse of your medical device

that is, concerning Pmcf studies. Now we come to the topic of in silico trials. So that's an upcoming topic from simulation studies for clinical trials. So there there are no patients involved. It's just completes simulation. So you can use this kind of setting for risk management tools for prediction models to get cost, efficient designs approaches. or you can also calculate the success probability of the classical trial, or you can totally simulate a full clinical trial depending on the medical device model. Set up your study protocol, make those adaptations, or calculate the dropout rate.

So how does it work? How does it function in general? You have a baseline model for your patient where your indication and disease is centered. Then you take up the clinical data you already have include this in a cohort and generate ritual cohort of patients. You can do it in several ways. You can have cohorts where every patient is different. Concerning the parameters that you want to prove, or you can make synthetic patients who give you a certain group of people with certain abilities which are tested in in a simulation model. And then you add your device model, you add a model for your clinicians that are involved. You add a model from other systems or your outcome model, and add some emulators to calculate, and then you have your study protocol. In the end you have a result that you might use for your clinical application.

There are some examples where this have worked out really good. So if you look at published data, there are around about 14 studies. I found where it has been successful. The main similarity is that they are always based on a really good physics model. So if the natural laws and the physics are understand, and then you can have a good simulation model, and can use these kind of data to simulate a data for your application. What is the regulatory of this in silico trials. In America there have been draft for the guidance and assessment of this kind of data. So they were taking the 1st step, but also the FDA. Published success stories and opportunities. That's a good thing to read these reports showcase 14 success stories concerning research questions that have been with have been

addressed with silico trials and also regulatory decision making in Europe. It's a bit different. There was a position paper in 2,022 towards regulatory pathways of in silico trials. But in general, it's still an ongoing process of how to implement this kind of studies in a regulatory pathway. But I guess in the next 2 to 5 years I think there will be more useful cases. So let's come to the let's last chapter. I know the time is already running. I'm trying to be fast that you can still ask some questions. 1st of all, what is important? Be sure that you're really dealing with a medical device. If we talk to our customers, there are a lot of regulations in Europe, and it might be that it's that the Mdr. Is not fitting for you. If you are unsure. If that's the case, contact us get in contact with one of our experts and discuss what is the situation for your product.

The second thing I want to mention also the conformity assessment procedure is a different one in Europe than you have it in the, in in us. In Europe. The manufacturer can choose a notified body which they can apply their technical documentation to, and the technical documentation then gets reviewed in a notified assessment report. And if this is positive and you received all the data for your technical documentation, you're allowed to put the medical device on the market, and then the notified body you have chosen as a manufacturer is responsible for auditing and for surveillance activities concerning your product.

So that is different to the Us. Side what we see on a daily basis. As a consulting, you have a huge amount of different notified bodies, a huge amount of national, competent authorities. There's over hundreds of guidance documents which give you all hints on how to behave in addition to the Ndr. So we know that this field is very complex, and that there are some areas which which are difficult to explain. But what we get is that even the notified bodies are learning at the moment the manufacturers are learning, and the political and public pressure is increasing because medical device are missing on the market.

So to really get what you should do in the beginning. First, st if you have a clinical evaluation. search your literature, define your parameters, define your acceptance. Criteria. If you have equivalent products, involve them in this literature search, gather your preclinical data. If you have to do admission studies, do them after the initial cleaning and evaluation you have to update them. And this is the process where you enter real world evidence in your process with Pmcf Pmcf studies and also real world data, because the final goal that you have is to ensure that the device fulfills your intended use.

that your device has absence of harm, and that there's a positive impact on the market. So. And that's the last slide. I know it's really written in small language, so I will read it out. What what needs to be improved? 1st of all question must reflect the real world as clinical settings in which the device will be used. defined clinical parameters, and should be primary interested. Not so many secondary endpoints in in your study, your primary endpoints are important for device requirements. Significant user training include questions that address learning curves and an impact on medical device performance.

Consider unique aspects of innovation techniques such as software as a medical device, such as Kai in data collection and analysis methods develop better strategies for addressing potential biases. And then data addition analysis, especially if you have observational studies. establish clear documentation and evaluation protocols early in the development process, align internal stakeholders on product versions, key performance indicators and research strategies. and in the end ensure that your studies include diverse population and robust statistical methods, focus on patient-centered outcomes and clinical usability and qualify your study centers on their performance publicity rate and their equipment.

And with this I want to enter. Thank you for your intention. And I'm hopefully thinking that we still have time for questions. Thank you very much.

Hello! So I am going to run the poll question now. Sorry polls and quizzes and launch. This will help us understand the audience better. And what your what you're interested in. So please take a moment to look at that. In the meantime. I'm going to. Bring up some of the poll questions.

So the 1st question here I'm not sure I get the difference between real world evidence, post-market, clinical follow-up studies and clinical investigations which ones are mandatory for Psur performance.

The Ps. You are I think psi, normally are from to a higher risk. Class medical devices, real world evidence can be you. So there's no definitive answer that you can say it's it's black or white. So you have to include certain sources for your real world evidence. You. You plan this as a manufacturer in your Pms plan. So if if if you want to include that into your market overwatch, then is a fine approach. You have to ensure as a manufacturer that you get feedback from the market. That is the important thing that you have to consider here.

And if you do it on real world data, if you do it on Pmcf data. That depends on the situation and also what the risk class of your medical device is

Wonderful. The next question that I have is, How do in silico trials account for heterogeneity in patient baseline, eg. Comorbidities, etc. Shit

it's a really difficult thing. So these in silico trials are relatively complex to model. So that's why I was telling in the beginning that the physics or the physic principles that normally used for successful in silico trials are relatively clear. If you have a situation where you have post-mortgage things which are hard to generate or simulate. I wouldn't advise you to take in silico trial. I would use a classical trial to get these answers

Interesting. So we have another question here. Where can I find registries, particularly for a specific field. for example, type of surgeries, medical field software type of Ivd orphan devices. Rare diseases. Is there a master list one can search within, and the ones I found were limited access. That is, you have to have. You need to be a surgeon or in a clinic with a contact to contact

Data so totally right, the access is a bit limited. But if you write as a manufacturer your clinical evaluation, you, as a requirement for the author of the clinical evaluation. You have to have a clinician in your team, so he might have access to these kind of lists. I would go through the National Institute of Health, which I mentioned in the presentation. They have a huge list. Of these devices. if you are on the manufacturing side. You might also consider paying for this kind of access because they're giving you a huge amount of data input concerning your device. Also, if you have several devices on the same indication. It might be useful, but it's a business decision that you have to make in a specific case.

I also understand that with rare diseases the patient groups are the best source

Yeah, it is. It's it's really hard to get. Sometimes you have rich histories, but the but the distribution of the patient is is also very rare. So it's hard to gather this kind of information. And also, if if it's really a rare disease, it's hard to get like 100 patients which are having the same situation. So in this kind of things, you really have to to get the device market on a special condition for often devices. There's also a different guideline that you have to follow up. And then you have to look at the specific situation, the specific disease, and what what are the the benefits for the patients, and what are the risks for the patient? And then you take out data from post-market surveillance

to really get that

On the point of real world evidence as a control arm for a clinical trial. Could you please elaborate on how this could be set up

So normally you take when you do your state of the art, you consider the literature of the last 5 to 10 years. Something like that depends on if you do the initial clinical evaluation, or if you do, or if the product is already in the market and you're in the update circle. And then you take out the evidence that you have concerning certain groups. Maybe you have publications who set up the gold standard or show you clinical data of routine measurements something like that, or you get in contact with certain study centers which can give you the routine data which you can use as a comparison. Of course, these kind of comparisons are not

as good as showing a real control group, because the control group might be on a different setting. What is important that you really show, and your study protocol, what the general condition is, and what might be the alterations from the original trial and your control arm. So it's a bit tricky to formulate. But in general, if you have Ethics Committee in place, the the possibility to decrease the the risk of for patient group is well seen. So general these kind of studies are possible, but they are from lower evidence. This question may be too hard to answer. But I'm going to ask it, anyhow. How could we get access to electronic medical health record as a manufacturer?

So I think you have to get in contact with. I don't know if it depends on the country you're in and what the the registration for for your data safety are. But I would I would get in contact with insurance companies, and right, if if they have service that are official, that you might have access to. that might be an option. Sometimes it's difficult to get this this kind of gift. If you don't have the contacts and the network to the clinics itself. So my advice would be, if you have. If if you have, if you plan to go to Europe, try to set up a network with different clinics that you can have discussions with the physicians in place to give you access and to share with your data concerning the routine aspects

Very nice. We are. Have about 7 min left. I want to go ahead and share the survey results share results of the poll question. There's also going to be a survey at the end of no one filled out the okay. Something went wrong with the poll.

Okay.

So

Have to guess. I never came up. I did not work. Okay.

I don't know what happened. I apologize

Maybe we can

7,

Maybe we can try again

Yeah, no, it says it's ended. And so it it was. It was an error. Please complete the survey. The survey is now even more important. And let's go back to the questions because there are a lot of them, and I don't want to waste any more time on this

Thank you for your feedback from the chat. Yep.

Let's see. The poll only lasted for 3 seconds. We didn't get a chance to read the questions. Wow! That was probably my clumsy fingers. I apologize for that. so this question is great presentation. I would ask, what are the differences between adoptives, registries, and normal registries? Not sure. I know

I don't know what you mean with with adaptees, so I'm

Yeah.

Kind of have to look it up to be honest. for this kind of questions. If I would, I would take it with me and give you a written answer to that, because I would have to guess a bit right now. So I think the best solution would be. I will take it, and I will write you back. For solid answer

Hmm. okay, and then the last question is, why the real? Why, the real world evidence is specifically important in case of orphan devices as compared to other medical devices.

So for often devices. Sometimes the patients are globally distributed, depending on the the rare disease you have, and to get a clinical trial rolling where you have the costs of getting this patient to one place, to one study center or qualify different study centers on the different land that you get enough people to have a statistical, relevant number of patients that would be one of very costly things, and also sometimes a bit unethical to do so. You would have to rely on data coming from

from the usage of the product itself. So you can estimate risk function for these devices. in the beginning. So you don't have so many people the way you can test it out. And for this it's kind of an an nearing approach to get at least the risks are out of the way for this kind of patient

And the last question is retrospective. Clinical chart review, Pmcf. That retrieves limited patient identity, relevant data, eg. Age, sex diagnostics, categories will be exempt from ethical approval in the EU question mark and the Uk question mark, so will retrospective clinical chart review be exempt in the EU and the UK.

For Uk. I cannot say it for EU it is So you have to show the study protocol on how you did the rest retribusal the retrospective analysis on that. And then it depends because, what you have to understand notified bodies and the auditors are very subjective. Some auditors are fine with these kind of data. Some are not what I would advise you as a manufacturer if you choose one of the notified bodies that you're using a structured dialogue. Go in with your plan. And what kind of data you want to achieve and what your plan is on fulfilling the parameters on the clinical data side, and then you can feed back.

If this is a doable way or not. What these notified bodies can do is consult, but they can give you an an idea if the plan you are doing is is working or not

Fantastic. Well, thank you so much, Dr. Goldman, and thank you to everyone who participated. I apologize for the problem with the poll today. I don't know exactly what happened. Please complete the survey. At the end. We look forward to your feedback, and we'll follow up with you on any questions that remained unanswered. Shortly. Look forward

Where Matt.

Chart. Part 3. Thank you again, and on April second please be sure to register to hear Dr. Bettina Martin. Do you want to say goodbye. Goodbye bye to everyone, and don't forget to follow him on Youtube. Thanks

At least one subscriber would be nice

Okay.

Okay. Thank you very much.

Have a great evening bye.