ScientificForum2026 Technical Session 4 Scientific and technical innovation through research and

All right, good morning everybody. It's a pleasant day in Vienna. For those of you who are joining online, we have a lot of sunshine in Vienna today. So, it made getting up and making our way to the scientific forum all the more special. It's great to see all the people in the room today and also a special welcome to those of you who are joining um online. Welcome back to the second day of the scientific forum. Uh yesterday we looked at the role of medical uses in uh of radiation in cancer care. Uh we talked about how access can be strengthened. Um and we talked about how sustainable capacity and the key word there is sustainable uh capacity could be built through the raise of hope anchor centers. And that was really uh we heard a lot about that in the last session yesterday. This morning we want to sort of look to the future and to the role of scientific and technical innovation through research and development. Now research is continuously opening new possibilities for cancer care from artificial intelligence, AI, advanced radiotherapy uh to nuclear techniques in nutrition, radioarmaceuticals as well uh virtual reality uh and new approaches to education and training. Now, in this session, we're going to be hearing about how some of these innovations are already being developed and applied and what they could mean for patients and the cancer care systems, our cancer care systems in the future. So, how it'll work is each one of our our speakers today will give a short very brief 5-minute presentation. Um, and once we've heard from all of them, we'll do some Q&A. So, if you have some questions, note them down. note the speaker that you would like to address. Um, and we're going to make sure that we've got time uh to take your questions. So, please keep those ready. And let's get into it. Now, we're going to begin with our first uh presentation. It's going to be delivered by Miss Amina Kishot. Um, it's about artificial intelligence and its potential to support greater precision in radiation oncology. She is from the uh Pier and Marie Curry Center in uh Algeria and her presentation specifically is titled prostate cancer contouring guided by AI. This is an IAEA coordinated research presentation uh or research um project. Over to you Miss Kishot. >> Good morning. It's a privilege to be here with you today and thank you for having me. Uh my presentation is about citybased posted concert contouring guided by AI verification the first anker center collaborative research project let's start with why posted concert is a growing challenge around 1.55 million new cases and 420,000 deaths were recorded worldwide in 2024 in Algeria there were 3,000 and 615 new cases, 1,373 deaths. This burden is expected to increase with population aging. Radiotherapy is a cornerstone of curative treatment for localized prostate cancer. In short, prostate cancer is growing and is the need for timely diagnosis and access to high quality radiotherapy. Turning now to why it is hard to contour the prostate on city alone. First part of tissue contrast pro boundaries are difficult to distinguish on city. Second inter observer variability different clinician may contour prostate differently and this has a real clinical impact. Why is MRI is better? MRI it offers superior anatomical definition, more accurate and consistent contouring. So MRI improves contour accuracy but city remains the primary planning modality in many centers and this is exactly while highlights the need for AI assisted contour verification among challenging in resource concerned settings many radiotherapy centers rely exclusively on citybased treatment planning due to limited access to MRI. In Algeria, access to MRI simulation remains limited with only two MRI simulation currently available. Against this backdrop, this project aims to improve contouring accuracy and consistency through AI gaded contour verification and collaborative expertise. In this sense, AI assisted contour verification can help bridge the gap between city only planning and MRI informant contouring in resource constraint settings. What does this mean in practice? City has limited soft tissue contrast which makes prostant contouring challenging. MRI gives better anatomical detail but it's not always available. So our projects looks at whether AI informed by MRI can help verify CT best contours and uh more consistency especially where access MRI is limited. In this sense, clinical needs standard design best contouring support by AI verification. This project begin with consultancy meeting in Vienna in 2025 to develop CD based contouring guidelines for prostate cancer radiotherapy in low and middle inome countries. It brought together radiation oncologist and medical physicists from ankor centers worldwide including Algeria and defined the consensus contouring guidelines and shaped the design of the AI contouring tool at the core of the C therapy. This workflow follows collaborative and stepways approach. First anchor centers receive consensus guidelines and training. Next they upload the city data set for initial AI contouring. Then experts review and refine the contours which are used to train and validate the model. The future files will expand the approach to AI assisted training planning. In conclusion, the expected benefits are standardization of prostate contouring which leads to improved clinical outcomes with better tumor control, reduce toxicity and recurrence through s oran atrix sparring and enhanced care, consistent quality of care in uh middle and low and middle inome countries. This project more than an EI tool is the first center research work together on a shared challenge. It means strengthening collaboration research and developing research skills that enor centers can act as regional multipliers for research quality innovation and quality radiotherapy development. and thank you for your attention. >> Thank you, Miss Kashoot. Um, now let's look at how research and innovation can build uh not only national capacity uh but also expertise that can serve a wider region. And I'm now pleased to invite Miss Indira Teleovva uh to the podium. She's head of the center of radiation technologies at the national research oncology center in Kazakhstan. Uh she's going to be presenting from national capacity to regional resource advancing radiation oncology and nuclear medicine in Kazakhstan for Central Asia. >> Thank you very much. Um dear excellences and dear colleagues, thank you so much for having me here. I would like to represent the national research oncologist center with the presentation from national capacity to regional resources advancing radiation ancology and nuclear medicine in Kazakhstan for central Asia. Um firstly I would like to tell about our hospital how it was built and was integrated. Uh firstly the nuclear medicine and radiotherapy in Kazakhstan it was uh it started to grow very fast for the last 15 years. If you compare it like in 2010 we have only one uh nuclear medicine center uh which consists of one PET scanner, one spec scanner and one production site only one cyclron and at that moment we had only two Linux then like in 10 years in in 2020 we already had three center for nuclear medicine uh which consist of four scan op scanners two production sites and at that moment we already had uh 12 Linux uh had been uh installed and added uh today in 2026 we we already have 10 nuclear medicine centers which consists of 17 PET scanners, five production sites and uh 29 uh Linux already. So you can see the very rapid growth of this radiation medicine field in Kazakhstan. Uh because of that u the main uh the main point of ministry of health was to to uh to have uh to have a very good nice center which consists of all these uh different technologies and can u put the capacity the the quality and the uh on the needed level that's why uh our center that's how our center began to work so at the moment and rock is a national platform for full cycle radiation therapy Uh it consists of we have very big center of radiation technologies and it consists of cyclone production complex itself and then we have the terronostic department, radiation oncology department, proton therapy department, then medical physics and radiation safety and engineering department as well. Uh if it comes to the main strength of our center is the integration because uh at the moment we have more than 200 uh specialists working over there and we in in the last six years we made a big I mean a lot of work and we were able to launch all this uh department uh at that time. So uh if it comes to production at the moment we do produce the FGG and we have uh our own R&D lab and and are planning to produce uh 10 more radio pharmaceuticals in the last in next five years. Uh then we have PET CT and first PETMR in Kazakhstan uh and of course CT because we have the terostic department and we do the iodine treatment at the moment. uh in central Asia proton therapy was the first one we launched it last year in 2025 and already have more than over 150 patient had been treated during this time uh in for radiation therapy department we have four linear accelerators and one uh highdose bracket therapy uh equipment as well and of course uh we because we have the iodin we have uh uh impatient rooms so it's like eight impatient rooms uh with uh which uh which has the capacity of more than 300 patient per year. Uh what we did uh during these six years firstly it was uh the construction itself the commissioning the equipment preparation then uh we were preparing our our hospital for the uh all the regulatory readiness all the licenses and uh and everything were were obtained. Then uh specifically for radio pharmacy we prepared our pharmaceutical quality system under GMP and ISO rules. And then of course more than 600 SOPs were uh were developed during this time to be able to run all this I mean all this process together. Uh the main point of course it's not just equipment is our staff. So our team was behind all these um big technologies. uh if you compare it for the last like two years in 2024 we had only 60 employees now it's more over than 200 uh employees so it's like 30 doctors 20 production specialists 15 medical physicists uh 10 radiation uh safety specialists 25 technologists and RTS and more than 30 nurses so it's a very big team uh also uh empowering our specialists uh we we did um We did we helped them to learn in different in different countries such as US IAEA uh supported learning then uh South Korea and so on. So we uh our colleagues from those countries helped us to uh to to bring our center today. Then of course coming to research uh capacity as well at the moment we have two PhDs and over 30 master uh uh science and then we have the students who are undergoing the studies. So we are hoping that in the next couple of years we will expand our research capacity after having all this equipment together and of course the next step uh is already underway. What we need to do because Enro is the biggest uh cancer uh hospital in Kazakhstan uh our main role is a coordination of cancer care in in our country. So it means we're planning to become the reference on center in Kazakhstan both in nuclear medicine and in radiation oncology as well. So it's like uh firstly we need to um to work on uh development for the regions coordination of cancer care quality assurance and standardization of all the processes that we have clinical research innovation and development and of course it's expert expert and regional support in for our Kazakhstanian regions. um the step forward what we're planning to do uh in the next like five five years is like to in strengthening radiation medicine not only in uh Kazakhstan but as well as in central Asia with the help of IAEA uh like this year in May 2026 uh director general of IAEA Mr. GCI uh signed the practical uh arrangement with our center uh for the next three years uh because we really want to be to become a very nice IAEA uh based anchor center for central Asia to uh to bring together all the specialists uh in radiation medicine. So of course our main cooperation priority is quality management education and training uh expertise and research and innovation. So uh from national capacity to regional impact uh what we do we do we do stand we started already the work for standardization of all the processes that we have in radiation medicine in Kazakhstan. Uh then we are planning we already started the programs for regional training. Uh it means not only for Kazakhstan specialists but also for the specialists uh who uh who uh work in our in central Asian countries. Then of course it's expert support. Uh we of course because uh because nuclear medicine and radiation ancology is very fast growing uh discipline in Kazakhstan that's why we have a lot of centers that been opening. So we are trying to help them to give them the expertise so they will have any mistakes uh during the launching the their equipment. uh and of course technology transfer because we do a lot of things in our center and we want um other hospitals to have the same level to the same quality of the uh of the treatment. That's why we're trying to to help with technology transfer as well and research and collaboration. This is in our plans but we hope we will be able to do it in the coming years uh on the on the needed level not only in Kazakhstan but also in Central Asia. Thank you so much. Thank you. >> Thank you Miss Tle Lova. Now our next presentation um is going to be focusing on a different area of research. This is the use of nuclear techniques and to better understand nutrition so that we can improve the outcomes uh of cancer care for children. And I'm pleased to invite Miss Po Bun. Uh she's a nutritionist at University Kbang Sunan in Malaysia. She's presenting applying nuclear nutrition techniques to improve outcomes for children with cancer. This is insights from a multi- country coordinated research project. Thank you Christine. Um yes the slides please. So the topic of my presentation today is applying nutri nuclear nutrition techniques to improve outcomes for children with cancer. And this is a multi-country coordinated research project. Um yeah so yesterday we heard about the nutrition about the challenges for cancer in adults but in children we have more than 400,000 children and adolescents aged between 10 to 19 years who are diagnosed with cancer every year. And of this those who live in high inome countries 80% of these children can survive for at least five years or more. However in LMIC's unfortunately the survival rate is 30% or even less. Now why is that so? So this could be partly due to malnutrition. So malnutrition has impact on outcomes. For example, if they are undergoing chemotherapy, they have less tolerance for it. They are at higher risk of infections which then lead to treatment delays or interruptions and that leads on to lower survival rates. Yesterday we had profess professor Alan Keman who told us about nutrition and body composition and she says that just knowing the BMI alone is not enough. The same is true for children. So if you look at these two pictures um of the boy, the thinner one and the fatter ones, they both might have the same BMI. However, one has way more fat and way less muscles. And chemotherapy can actually lead to muscle loss and fat gain as well. So how do we do this? Beyond BMI, we need to be able to measure what is inside their body. And the CRP project that we are involved in applied dutarium dilution technique or which is one of the nuclear techniques. um where the children just drink some dutyium water and then we just collect their saliva and urine or urine and with this we test to see how much body fat they have and how much muscles or lean body mass that they have apart from d uh dutaterium dilution technique. We also have doubly labeled water technique and this one measures how much energy they actually use when when they are sick or you can use it for healthy people as well. Now um some of the centers that are involved in our CRP also have the capacity to do whole body potassium counting and this can tells us about the body cells inside as well as dexa and dexa can tell us also about how much fat or muscle mass that they have. So we had nine countries across the world and in all these countries we try to use standardized protocols except for certain countries where they have more uh sophisticated equipments and others that don't then um we might skip certain measurements. So basically we measured body composition. We looked at their nutritional status using anthropometry. We checked their dietary intake. We looked at clinical outcomes and we also looked at the quality of life of the children as well as the symptoms that they that they go through during treatment. So I'm going to share just two slides with the key insights from our CRP. The results is not just from Malaysia, it's from around the nine countries that I shared with you just now. And the first key insight tells us that although children with cancer could have recovered from their treatment clinically but their nutritional recovery does not always follow. So about 10 to 20 um these children actually have higher energy requirements meaning they need to eat more uh at about 10 to 20% more than the recommendations but they are actually eating less at about 60% of energy requirements only and in some children even worse they are they are um have a shortfall of 55% or more meaning they only eat about 40% of the energy that they require and this situation can last for up to 12 months or more after treatment has completed. So because of this we know that due to inadequate intake and the need for a high energy they could be losing body mass and what we are concerned is is particularly lean muscle mass. Now from the CRP also key insight number two is that weight alone can miss important changes. So what we usually check when children come um for treatment we might look at their weight, their height or their MUAC easily measured at the midupper arm um and also some lab tests. So this can tell us maybe if they have loss of muscle mass or changes in changes in body fat not possible changes in cells and so on. and they also have lower strength due to uh loss of muscles. But what we can do is we can add other measurements like dly labelled water or dutyium dilution. But maybe these two are very expensive methods. So the easier ones could be including a bioelect electrical impedance analysis. um it can be quite cheap or slightly more expensive depending on the equipment that you buy to look at the body composition changes or we can easily do a hand grip strength to look at their muscle strength. Now part of this CIV in Malaysia, we actually did a survivor study as well where children who have survived for about 10 years or more from their childhood cancer um what we found is that in the long term even 10 years after they have survived their childhood cancer their the body composition changes remain. Though many of them have excess edyposity, they still don't eat well enough and they have altered body composition. So in fact what we found was that some of them actually have up to 46.8% of body fat mass. Now for a normal person like you and I our for females body composition that's normal is 20 to 30% and for men is 10 to 20%. Now these children who have grown up to be teenagers or young adults their body fat could be up to nearly 50%. Which is um not good for their health. All right. So this is my last slide. Um so what can we do with nuclear assessments in terms of nutrition? So these are the methods that I talked about just now. So if we measure them, it can tell us whether the child has muscle loss or limb tissue loss. It can tell us maybe nutrition inadequacies and what are the energy gaps. And with that information, we hope that we can turn it into insights where we can do targeted nutrition therapy, rehabilitation and ongoing moni monitoring. Um, and ultimately what we want is for the children who are growing up to have a good quality of life and good health in the future. With that, I thank you. Thank you, Miss Poe. So, we're now going to move to innovation in radiation oncology. um how and the technologies that continue to reshape uh how we deliver um radiotherapy. I have the pleasure of inviting Mr. Roberto Orea. He is the scientific director of the European Institute of Oncology in Italy. He's presenting innovations in cancer treatment, the evolving landscape of radiation oncology. Good morning and thank you so much to Aya for your kind invitation here. Uh many think has been already discussed today on radiation but we try to have just a summary and uh radiation is uh is characterized by really more than one century of research and development with fundamental uh steps. The first uh was auto voltage and super voltage to mega voltage electrons charged particles. The second one from uh no any type of uh image guidance to for internal anatomy to sub millimeter accuracy and target localization. The third is from fostatic open radiation beams to complex arc therapy with beam aperture modulation. all the progresses allow to apply along this period new uh schedules of fractionation. Uh this is just a list of the innovation that today we can use in clinics uh for uh applying radiation therapy. uh some technological innovation like for example EGRT image guidance treatment with the use of 3D or 4D organ motion control uh CT MRI Linux system means uh hbrid machine. The next will be probably the PET Linux. uh they use the possibility to use the true adaptive radiation therapy, the art that means daily scans, adjustment of the plan online versus offline. The increasing uh uh use of artificial intelligence in the process of radiation therapy for not only for auto segmentation those distribution uh prediction dosomic for example but also for modeling outcome and toxicity. This is proper selection of patient. We have also the implementation of many biological and targeted strategies. One of the most growing in interest is the use of terronostic that means diagnostic phase imaging verification and target therapy that can be also combined with external beam radiation. And the second topic of really biological interest is the effect of radiation therapy on the immuno immuno system. Traditionally depressive but now may be synergistic and the association of radiation therapy with uh different drugs monoconal antibbody target inhibitors can allow to improve a lot of type of cancer. Finally treatment delivery optimization particle therapy again of growing interest proton EV ion boron neutron captor and uh the the next step will be the flesh therapy and the special fractionation so means ultra high dose rate and mini beams um as we mentioned it hypofractionation because hypopractionation is really important is really important for the optimization of the treatment the personal ization of the treatment and also is able to facilitate the access more access to radiation therapy. We have in history first generation uh five to seven weeks of treatment second generation of fractionation moderate hypofractionation. This means on average three weeks of treatment. Ultra hypofractionation that means one week of treatment. But now we are moving to single dose. Single dose is the application of the concept of ablative radiation. Uh surgeon operates once and radiation therapy have to treat the patient once. is is is equal because today due to the technology we are able to give up to a single shot of dose up to 40 gray that is absolutely uh very uh as I said ablative dose. Some advantages of hypofractionation. Of course, reduce the overall t time of the treatment. Improve the patient quality of life. Avoid traveling for example or reduce traveling. Increase system capacity. Again, important point. And reduce direct and in direct uh cost. And so is is moving. We have to move to green. and and this may be help in this. Another point is that especially in western country there is a problem that uh is is on about 20% of the people that experiment financial toxicity. So that means the cost that the patient have to pay in addition to the to the cure for other other issue. uh some example because the time is really short. Sterotactic radio surgery is the typical example of ablative radiation therapy started a lot of years ago by Lexel neurosurgeon but now it can be applied in any uh type of extranial tumor including a moving target with dedicated machine maybe gamma knife maybe cyber knife but can be also applied with the use of volutric arc with a common Linux accelerator. Uh the concept of adaptive is is really important because the combination of high quality imaging with artificial intelligent driven planning and automation and art allow clinician to adjust the treatment plan in a near real time. uh instead of static plan you can reflect and to treat the patient during the same session according some difference in movement or difference in anatomy at the same time of the treatment and this is another way to increase the number of patient that can be treated with one or very few session of treatment due to the high precision of uh of uh the treatment charged particle therapy is is an issue. Uh the main issue is the high cost of this implant. But anyway uh there is an increasing interest increasing development mainly in United States and in Europe in east of Asia but center are opening now also in other part of of the world. uh charged particle has a unique characteristic that is a black peak and the capability to to deposit the energy in a specific depth uh beyond uh which there is a minimal radiation. This allow uh to uh spur normal tissue and to uh hit uh the the target that is the tumor. So we have three main effect especially with the active scanning that allow true dose painting of the dose. So organ at risk sparing low integral dose. This is really important for for example for pediatric patient because reduce the the the risk of secondary cancer induced by by radiation and charger particle also are able to to to break the double chain of of the DNA more with respect to X-ray because they have a mass and this allow to overcome come or to minimize the effect of so named radioistant tumor. Yeah, I finish flash is a is a is a unique fantastic future I believe and because the use of ultra high do those rate that means that is with flash is possible to give 40 gray single shot in one second uh instead of several several mill minutes and uh it's possible to integrate flash both in lina or in charged particle and this probably will be a major rate a lot the possibility of uh safe do escalation and tissue sparring. Just to close uh this list of uh key technological advances that we can use as I already mentioned just to give a summary. Adaptive radiation therapy tailored treatment to daily anatomical change. Image guidance enhance target precision and minimize damage. Artificial intelligence supported automation and prediction. Convergence of molecular target and radiation, charged particle therapy for high precision, very high precision radiation therapy and hypractionation, ultra high dose rate and improved efficacy in reduced time. At the end, the message that radiation oncologists uh have to be able to use radiation exactly like a drug in order to personalize the treatment at lower cost with respect to many many uh drugs that are currently use it because the impact the economical impact of radiation therapy in total is only 5% of the total cost of cancer care is a high high efficacy and uh and I believe that we remain absolutely a standard in in uh in in the cancer care the problem to be solved is to homogenize the distribution of center for radiation therapy. Thank you very much. Thank you. Thank you, Professor Oria. Now, artificial intelligence is uh creating new possibilities so across the cancer care pathway um in particular by helping us uh make better use of increasingly complex uh clinical um and imaging data. And now I'm pleased to invite Mr. Gayorg Lungs. He's professor of machine learning in medical imaging at the Medical University of Vienna. He's presenting AI for smarter cancer care, turning data into better decisions. >> Thank you, excellencies, ladies and gentlemen. Good morning. Thanks a lot for having me. It's an honor to be here. I'd like to give you an update about the status of AI in cancer care. So, where is the impact? What has reached clinical routine at the moment? What will come next? Because we have the scientific evidence that I think is strong enough. So to move that into clinical care in the next um evolution and then what we are starting to investigate um and where we are learning quite a lot of new things about how we can use AI in this uh context. So what has arrived in the clinic? Um I'm part of the um comprehensive center for AI and medicine at the medical university Vienna. That's my colleague, one of the group leads um G vitam. He is a neurosurgeon and he was involved in the development of a technology that allows them to during the neurosurgery take tissue samples, perform spectroscopic imaging simulate agent E staining, which is the staining that you need in order to classify tissue and automatically tell whether that's a tumor or not. And that's really critical because it's hard to see the boundaries of tumors during neurosurgery. And that has changed a lot how they do surgery because before that took around 40 to 45 minutes to get this information. Is this still tumor or healthy tissue and now it takes about 5 minutes and that changes the visibility because now they can do that lots of times during the surgery and that has a big impact on the outcome for these patients. So we see that AI does not only replace things that we do but it really changes the workflows and what that means for the patients. Second uh big area of what has arrived in the clinical reality is AI for image analysis. So we see systems that can detect um findings that can detect nodules that can detect uh and and predict the risk of cancer for individuals and I think the maturity of many many different um applications in the image analysis and the use of AI in image analysis have also used have also led to a le CRP um initiative that is building up a global observatory uh to detect new diseases. So not only diseases that we know and can diagnose but also to detect novel emerging diseases in the patient population because we have learned from prior pandemics that the clinics and the imaging is usually the first point where we can describe a new disease and uh this observatory as part of the zodiac initiatives will help to do that globally help to do that fast and also will be a platform that allows quick data sharing during the very early stages of the new pandemic because that's one of the limitations that we learned from co zodiac. So this is in the clinic and this is on also the transition to research. What's happening in research right now but what I think will um enter the clinic soon is that we are seeing that AI moves the role from classifying and diagnosing to predicting based on not only imaging data but on multimodel data. This is an example out of our lab where we are working together with oncologists and new um enco here is to investigate whether we can help uh breast cancer patients that are undergoing new advent chemotherapy. So chemotherapy in order to downgrade the tumor before surgery is performed. That's a very successful strategy. But for some of these patients it does not work and we would like to detect early based on imaging data based on sequencing like gene expression data that is coming out of biopsies of the tumor whether this therapy will work or not because if it doesn't then we can spare these patients the the remaining therapy move them to surgery. The other way around is also becoming more and more frequent that during surgery we realize that there is no valid tumor tissue left. So we could have spared these patients the surgery and we would like to come to a place where we can tell that in advance and not perform surgery in a safe way on these patients and still retain good or even better outcome. So predicting based on multimodal data. Second uh point which is here is uh the results but I'll move to the second point um about the use of AI in the development of new treatments. Right? So we have seen what we can do with existing treatments to help us to decide when to treat, what to treat, what's the dose, what's the kind of treatment where these patients might benefit most. There's a whole other part of healthcare which is developing new treatments and we see that there is a big need for accelerating that because there is a lot of uh a lot of conditions, a lot of treat diseases where we cannot treat as well as we would like. This is an example um out of neurooncology. This is uh a patient population all of the uh central nervous system primary lymphoma patients in Austria and we investigated together with uh neurosurgeons and neurooncologists and neuropathologists whether there is a predictive signature in the tumors that we or in the imaging data of the tumors in the MRI imaging tumor uh data and if there is a correlation if there is a link between what we see in the imaging what we see in the phenotype of this tumor with the underlying genome. type in this case with metilation profiles of these tumors that tell a bit about what genes are switched on and off in these tumors or which are effectively steering what the tumor is doing. And we see that there is a link um and that's good because we can predict for individual patients. But the actual benefit here is that we can use real life clinical populations in order to identify possible target genes for new targeted therapies. And in this study, Alad took essentially the output of the machine learning algorithms that linked high-risk phenotypes in the cancer imaging data to specific genes in the tumor genome that might be good targets for targeted therapy and did the first invitro experiment, the first proof of concept study in order to actually show successfully that these are actually good targets. And I think we'll see more and more of this type of research where we use machine learning in order to understand what is going on in the clinical routine population and then move that into uh the development of new treatments. So I think these two lines right multimodal imaging prediction algorithms in order to inform pre-treat treatment decisions machine learning in order to inform where is a good directions in order direction in order to develop new treatments are things that we will see more and more uh soon in reality. One thing that we are starting to investigate right now across the community is to tackle one question and that is many of these algorithms that are working right now give something like a probability they tell us well probability of successful response is this and that the risk is this and that that's the diagnosis but to integrate all of that with many other points knowledge observations of the patients into an actual decision that's still very much uh on the expert side but we see that I think there is the opportunity to use technology like large language models to also support this and this is one example coming out of our lab um together with others where we and now let me see if I can start it here where we um investigate how we can use large language models in order to have conversations so where we let these large language model extract evidence trigger the gathering of the evidence and then combine evidence that is coming from pathology radiology oncology molecular pathology ology in order to not only give us a probability score but give us an actual proposal for treatment decisions together with the rational with the reasoning pathway that led to that proposal and I think that is very much at the beginning so we are only learning how these discussions how these deliberations among agents can be shaped how they can be audited how they can be traced and explained so that we can actually make that a useful tool in the clinic but I think this is something that will come with the next wave And with that, I'd like to thank you for your attention. Thank you. >> Thank you, Professor Lungs. Now, innovation is not only limited um to diagnosis and treatment. Uh it can also transform how we are training uh cancer care professionals. And um I'm now pleased to invite Miss Humera Mahmood. Uh she's director and chief oncologist at Nori in Pakistan. She'll be presenting virtual reality training and education and Nori's role in research. >> Asalamaikum and a very good morning to all of you. Before I start my presentation, I would like to thank international atomic energy agency for giving me this opportunity to talk about how virtual reality modules as an innovative approach can help in education and training. And the second part of my presentation is related to the role of my hospital that is atomic energy cancer hospital Nuri Islamad in research in Asian region and I will be talking from the perspective of radiation oncologist. So our exposure to virtual reality modules started in uh March 25 when we were handed over two sets of these modules covering uh training related to intra cavitatory cervical cancer breakchie therapy and uh we were provided these uh sets by the division of human health international atomic energy agency under the framework of agency aimed at providing the best possible cancer care and uh equitable access to radiation medicine the worldwide. We were really fascinated in starting using these modules considering a huge uh gap in human resource particularly in radiation oncology which is true not only for Pakistan but for most of the countries in lower income area. So we started using these modules in September the same year and also a study was designed. Uh so uh for a huge population serving cancer burden which is expected to rise beyond 2.2 million by the year 2030. We have uh 39 radiation oncology setups in the country. So uh a stud pilot study was designed by international atomic energy agency with the support of uh Moffett cancer center the same year in 25 involving five uh countries. We were lucky to participate in the study. So we recruited 18 uh residents in radiation oncology belonging to different stages of training from first year to fourth year. So they participated in using uh these modules on uh virtual reality headsets and all of them were made to uh fill questionnaire both before and after the training. And you can see for all the three parameters including knowledge, skill and quiz score. All of them improved significantly after training on virtual reality modules for all the five participating countries. Moreover, uh abstract of this study has already been approved for oral presentation in 68th annual meeting of Astro going to be held on 27th September. So when using these modules, we found an uh more advantages and fewer limitations. The most common uh or the most important that I found was uh that in our culture male doctors are not allowed to do uh breakchie therapy uh for cervical cancer in our female patients due to our cultural barriers and the same is true not only for lower middle inome countries but also for higher income countries. Moreover, uh getting training through these virtual uh reality modules uh without going anywhere or without waiting for any supervisors or trainers. Uh these are more feasible, more cost effective, easy to use and these are not time bound. Moreover, our younger generations that is Gen Z and alpha generations, they are more used to using search VR modules in different scenarios. And another important thing is that these can be used for training our radiotherapy technologists and our oncology nurses who otherwise uh get the least number of opportunities of getting advanced training outside their workplaces. So the limitations that we noticed were of course including the number of headsets of course the number of tools is important but these can be used repeat as many times and for as many participants as possible. then uh you always need a viable internet connection. Uh moreover, real health scenarios are different. Patients anatomy is not as ideal as is in virtual reality modules. But still uh these can be used for training a large number of personnel through national training courses as well as uh regional training courses. The second part of my presentation is the role of atomic energy cancer hospital Nuri Islamabad in research in Asian region. Uh so we are participating in a number of academic programs as well as research not only related to international atomic energy agency but we have developed a very strong collaboration with a number of organizations and societies notably amongst these are farro uh Amstro Astronet St. Jud's pediatric oncology network and MD Anderson particularly uh mentioning here uh under the umbrella of farro which is actually federation for Asian societies of radiation oncology comprising 16 countries from Asia. We have been able to get published a couple of manuscripts and uh I feel pride in mentioning that one of the published studies was launched from the platform of Nuri and it was related to breast cancer practices in Asian region. Another two studies have uh been proposed from Nuri and these are about to be launched very soon. So concluding virtual reality modules can play an important role in radiation oncology as an innovative approach particularly a field which is rapidly invol evolving in terms of both radiation techniques as well as equipment and secondly Nuri is playing a pivotal role in fostering research in Asian region. Thank you so much. Thank you very much, Miss Mahmood. Um, so our next presentation now is going to look at innovation from a sort of broader um, health system perspective at how research, education, and clinical care can come together to turn innovation into impact. And I'm now very happy to invite Professor Ingi Wo. uh he is group chief executive officer of Singapore Health Services, Singh Health and he's presenting from innovation to impact how Singh Health is shaping the future of cancer care. >> Yeah. So very good morning. Uh we are honored and privileged to be the latest uh member of the race of hope banker center. So um um I think as in this is our well-loved triangle in sing health where we believe that uh to define the medicine of tomorrow. We really need to do three things. We need to transform clinical care. We need to train and educate the future generation of healthcare professionals. And lastly to continue to do research and innovation. I think cancer care is no different from the rest of medicine and that to define and inform and improve cancer care and cancer outcomes for the future, we need to invest in clinical care transformation, research, education and training and innovation to to really define the cancer care of tomorrow. Um the the key ingredient um for us in Singh Health over the last 20 years has been this academic partnership with Duke and US Medical School and through this partnership we have we have um established 15 academic clinical programs which are specialty defined clinical programs 17 SH Duke and US disease centers which are interdisciplinary and alter centers uh based on a disease entity And lastly we have also established 19 joint research institutes. So um in particular and of relevance to cancer care our academic program is uh anchored in oncology where we bring together all specialists involved in oncological care medical oncologist radiation oncologist and so forth within one academic clinical program. Some of the disease centers of relevance to cancer is the um breast cancer which brings together all specialists involved in the treatment of breast cancer a genomics medicine institute blood cancer center and head and neck center that really brings together all the disciplines in the interdisipary and multidis center to coordinate cancer care in a diseasebased setting. Some of the relevant joint institutes that have helped us to bring about innovation in cancer care are the academic medicine research institute which actually gives uh clinicians the support statistical support grant writing support for research. The educational institute which coordinates and brings and helps faculty to develop their educational skills. a cancer institute and an uh academic u AI medical institute that really brings together artificial intelligence competencies throughout the whole healthcare cluster and ecosystem. So to illustrate uh one such center I I'll just highlight the example of the breast center which brings together all all specialists and healthcare professionals medical oncologist radiation oncologists uh nurse practitioners alli health professionals together and looking really looking at care at the end to end from community looking at breast cancer screening programs to early diagnosis using advanced technologies interdisipri treatment, early access to treatment all the way to postcancer recovery such as the management of lympadeema and survivorship as well as paleation for those at the end of life stage. Um uh I think as in all areas uh driving the cancer care of tomorrow really brings really requires the development of talent as in I think all institutions either thrive or perish on the absence or abundance of talent. This is a busy slide and suffice to say that we look at talent development from the entire lifespan of a medical pra uh practitioner from from undergraduate medical student days uh talent programs tailored at that level through residencies post residencies when they become specialist uh junior specialists to give them certain uh developmental programs specific to their to their uh career and and then at the senior senior clinician level. So the talent develop program really looks at the entire life course of a clinician from medical school post-graduate into the practicing uh practitioner stage and we look at uh developing talent in a few broad areas. Firstly providing the structural support. I mentioned uh grants writing uh developing that culture and also in unique settings such as our women in science program that understands that certain populations within our community such as women may may require some special support and some of these niche and boutique programs would actually provide that support for for boutique and uh specific groups of our community. The other the other uh big broad group of funding would be financial funding looking at pilot funding and also looking at gap funding for for clinician scientists that fall between the gaps of funding cycles. We also provide formal uh funding for mast's program and doctoral programs to actually upskill our healthcare professionals. And then lastly is this the area of faculty development to invest and to develop that culture and to provide ongoing uh career support for clinician scientists and clinician researchers. So um and I think innovation is important um is an important area and hence we believe that innovation needs to be local and hence it is important to bring uh innovation facilities and support to where clinicians actually work and where they have act close access to patients. At Singhal, we have four healthcare campuses and hence we have established through a generous philanthropic donation of $50 million. We've established four campusbased innovation centers where clinicians can actually go to and collaborate with industrial partners and other academic partners. And to date, we have as we have partnerships with over 100 commercial partners and industrial partners. Uh key focus areas moving forward. I think we um we've heard about AI medicine. I think AI certainly is an big area and our AI medical institutes helps us to actually bring the academic partnership and bring AI into medical research and innovation. We need to be a learning health system. Frequently we we frequently say that organizations are data rich but insights poor. by establishing our data infrastructure, data architecture, bring having anonymized databases as well as um you know developing having a systems where we can analyze data. We want to move from being data rich, insights poor to datari as well as insights rich and and lastly digital transformation, digital platforms. This whole journey of digital uh transformation will provide the technologies and platforms to enable us to become a AI enabled academic medical institute and to be a truly datadriven learning health system for the future. Um and and I think it's at at the end of the day innovation is not about uh we we hardly see a paper publications really creating that impact. I think end of the day it's important for us to translate research and innovation to bring about true patient impact. We do that through partnerships and increasingly uh the Singapore General Hospital Singh Health and SGH have multiple uh regional as well as international collaborations. We are happy to have worked with the IAEA over the last six months and gone through a very robust evaluation process and we are very excited. It's an honor and privilege for us to join this global network of the raise of hope and anchor center and I think moving forward we will uh with this establishment of this formal partnership with the IAEA we will work towards uh understanding the needs of the community better uh also evangelizing and being a and publicizing that SG health SGH and NCCS is now a anchor center to bring about the greater awareness within our ecosystem and amongst our stakeholders. uh I think there is a lot of opportunity for us to anchor and to improve accessibility of care within the region that we are uh in Asia and I think there are also opportunities for us to partner with our fellow Southeast Asian uh anchors anchor center that is based in Bangkok, Thailand and and lastly I think we it is a great opportunity for us to learn from this uh fellowship of network of anchor centers where we can learn and work together to provide greater accessibility and better cancer care for for the for the global for the whole for the world and for the region. Thank you so much. Thank you, Professor Inji. And for our final presentation uh in the session, we're going to look at um uh radio pharmaceutical innovation um and its potential to help us advance uh precision medicine all while addressing um the disparities in access. And for this um I'd like to now invite Mr. Eduardo Savio. uh he's head of the radio pharmacy department at the center for molecular imaging in Uruguay and his presentation is titled pharmaceutical innovation for precision medicine the IAEA research bridging gaps in equitable access >> thank you very much for your introduction good morning ladies and gentlemen I'm very pleased to be here and well we are going to address how the international atomic energy agency has support research to bridge the gaps and to promote equitable access and mainly to to focus our presentation which is the role of radioaceuticals uh in this important area of nuclear science in order to promote accessible cancer care. We know that when we develop preclinical development and research there is a great gap that is usually called the the valley of death of that great ideas that finally cross this gap and transformed into the clinical practice. So we are aware that nowadays we can't really identify from the point of view of molecular characterizations uh new targets but the still there is a lot of work to be done and how innovation can impact into translation and gap. Then we we are quite aware that there is a scientific breakthrough that that not automatically reached into clinical practice and also we need a lot of things in place to this job be properly done. We need infrastructure. We need training the staff. Uh we need GMP quality assurance, clinical evidence and also a standardized and sustainable productions. Luckily in our region we have a regional programs through the archalic operations that is addressing all these issues through approaches that is strengthening the availability in high quality safe and cost effective radiooticals to improve cancer management. But not only the regional cooperation is important also when you customize uh the needs to an specific country through the national projects that is a privilege that we have and the agency has say intimate us to work together with one health approach and so three different institutions thean center of molecular imagine kudim the public university, national university as well as the main delivery systems as asset that manage 70 different hospitals in the whole country. We are working together and which is our role there. Our role is to introduce new radiooticals. It will be an alpha particle emitter radio in the framework of chemical clinical trial. We will evaluate uh which is the role of oer meters and also we will start drafting a project not to be because now we have two cyclrons to add a third one in in the near future of higher energy 30 mv electrons volts and not only to have this in the Christmas wishing list but starting having as a specific project. So radioharmaceuticals innovations uh is where science meets clinical needs and in this coordinated research project has play a significant and very important role in in the framework of this um CRP. We have worked with many options of different radioharmaceuticals in previous in the present or in future CRP with diagnostic radio as technesium 99M or gallion 68 or silicon 89 or in the future with turbion 161 or present with actinium 225 and working in a CRP with actinium 225 we carry out an experiment where we um expose three different groups. One's only treatment with a lutium radio formatia which is beta meter, another with actinium which is alpha meter and another group with a combination of both and the combination of both in the end point of this experiment they have no evidence of cancer demonstrated what by imaging. So we were very enthusiastic and committed with next future research that the combinations of beta and alpha meters. As now you can combine different chemotherapy treatments with combining different linear energy transfer and different ways of delivering the energy to the tissue and diminishing the amount of activity that is administering and diminishing the toxicity inside the effects could be something that could be achievable in the near future. So why coordinated research projects has been and are so important for nuclear science development? Because they gather people with different extrens of developed countries and not developed countries to work together with a specific objectives with different levels of experience. And I think that this is really the way of sharing and moving faster to putting all together in in the same environment with the same mindset with the same objectives. But if we see in this alpha atlas, we can appreciate that all the production sites of new uh radionuclides emitting alpha particles are only located in the north of the cuador in North America, USA or Canada, in Europe or in the Asia-Pacific, China, Korea and Japan and Australia. And there is no production site of alpha meters neither in Africa neither in Latin America. And there is a huge amount of population that deserves to have access to this new technology. So terraaggnostic is really a challenge and is a model of precision oncology that needs and challenge us to have integrated precision and collegate platforms to manage properly new tracers and ready nuclear to manage properly this new technology and to manage properly how we are creating new evidence of the impact and the suitable use of these new radotical and these new technologies. So building capacity in innovations must be must be sustainable and when really innovation is meaningful in in if we are thinking in terms of radio pharmaceutical this could be produced in a hospital radio pharmacy in house it could be produced in a centralized environment it could be produced in an industrial radio pharmacy whatever it would be pet karma would be for particular meetings alpha or beta it doesn't matter what it really important that this huge infrastructure impact into changing things for for people so I believe really that we have started operation 17 years before now and in UA we have implemented and translational ecosystems working together different institutions rather pharmacies working together where with imagine molecular imaging groups the university the clinical sectors um also we can believe and we can dream that this impact could be not only in a national environment it could be also extrapolated to uh regional one we are very proud that in our national admin administrative board. We have representatives from the ministry of health, from the national university and from the agency of science and innovations. And we think that working all with different perspective with different commitments and with different um objectives is our main strength. So delivering the promise of phrase of hopes is when real innovation must become capacity and capacity must become access and access really uh become into better outcomes. Thank you very much to Selvi and to Aruna Corde for their support and I do appreciate your attention today. Thank you very much. >> Thank you Mr. Savio for that presentation and thank you to everybody for your presentations. I'm just going to do maybe one question to each of you now. Please get your questions uh ready. Uh everyone um we'll make sure that we can get those in. Um Miss Kish, I want to start with you um because you took us through your uh presentation which was focused on prostate cancer contouring guided by artificial intelligence. And I wondered why AI um as opposed to manual contouring. It's Thank you for your question. Uh manual contouring is time consuming and various a lot uh between clinician and uh AI helps uh standardize uh contour and uh reduce this inter observer variability and save time uh for clinial teams. >> Okay. So timesaving in essence. Um, Miss Tulia Silva, um, could you share some practical examples of how your center is already preparing to act as a regional resource for for neighboring countries? Um, so out of Kazakhstan into the rest of Central central Asia in terms of capacity building and technology transfer. >> Well, thank you for the question. Uh firstly what we started uh is harmonization and standardization of all the procedures uh which are there in radiation medicine is for Kazakhstan. Uh so we can actually transfer all this needed standards to other hospitals that there are in the region and secondly we already started to prepare the uh training courses training programs like the small ones like one week two weeks or uh really long fellowships. So especially for radio pharmacy and for medical physics because we have we're really lacking of the uh of the good u training programs over there. So at the moment we are on this way. >> Thank you. Um Miss Poe um it was very clear in your presentation that nuclear techniques um can sort of reveal problems that are missed by just looking at weight and BMI. what then is the next step in terms of translating that knowledge into an intervention that can improve uh the outcomes for children with cancer? >> Yeah. So just having the techniques that I described is not enough. Like you have the techniques you apply in some research like what we do in our countries and then and then what? So what we want to know is which of the which of these techniques has produced uh results um that is promising and how it can be incorporated into routine clinical care and if it can be included in uh incorporated into routine clinical care um then we will need to train the people who are involved in those um so that they can use the findings from this um techniques um that is useful um in order for them to uh create targeted therapies or targeted interventions um looking at the nutrition of their patients as well because I think everyone here is like radiologic oncologist or medical physicist and so on and I'm probably like the only nutritionist here today so don't forget the nutrition of your patients That's all I'm saying. >> Thank you for that, Professor Oreo. Um, radiotherapy is now especially in in the western world, this is an established component in in cancer care management. However, access to this treatment modality is of course limited um for people. So, how what what needs to be done now and in the future to ensure greater access uh to radiotherapy? Radiotherapy remain and will remain essential in therapy because you have to consider that today the concept of modern oncology is to uh multimodality approach and also intermodality approach means that uh also we need some uh new professional profile bioengineer chemistry and and informatics and so on. From the from the point of view of uh of progresses uh of course um we need to be to be faster uh to be faster in uh in delivery but also to be faster in the implementation of the machine. uh we need a robust uh machine but also robust uh uh treatment planning system because uh probably there is a space there is room to amilarate the dose distribution. This is particularly true when we move uh to charged particle because uh airbe is uh is is not the best. we have to to move to other type of uh uh evaluation of the dose effectively given uh to to to the target and um in general we have to develop uh a community a community an international community because uh uh what is emerging is is a is not enough training is not enough collaboration is not enough collaboration also inside with the world of medical oncologist. My personal speech is to be radiation oncology and medical oncology. And I believe that today this different is out of the time. Radiation oncology have to know drugs and uh uh medical oncology have to know uh uh race. This is the only way to to work together better than in the past. >> Thank you, professor. And please maybe hand it over to Professor Lang next to you there. In your presentation, we could see how AI could guide in real time brain surgery. It could help predict um how a breast cancer patient would respond to chemotherapy. But for for those of us in the audience who are not scientists, essentially what is this then? this knowledge help in terms of for the patient and is it something that doctors are using today or is this more for is is in this research phase now more for the future? >> Yeah, thanks for the question. So it's it's very much in use. So doctors are using it and the the reasons why they are using it is in order to improve outcome, right? So and we see the evidence that it is happening um in a couple of of of directions. So one directions for example as we saw in surgery we see the impact on the outcome of these patients. it's more accurate surgery. So there that the um kind of the the time to progression becomes longer, the overall survival becomes longer. So we see this evidence not only in terms of can we do some metrics about the accuracy about some algorithms but we really see it in the outcome of the patients. In other applications we see it in in early detection of cancer in more kind of precise steering of patients towards other diagnostic um procedures like biopsies. So we see there is an advantage in kind of avoiding unnecessary biopsies in in turning the time to treatment from detection to treatment um shorter for patients. So I think we are very much in this phase where the applications that are in the clinic are showing impact and that is also why they are in the clinic. And we also see that and we've learned during that phase that it's critical to have the applications early in the clinic in order to develop this evidence. So don't wait for the evidence because it will only come if you introduce them into the clinic. If you observe what is changing and the things that are changing are the outcome of the patients. But very often the necessary step to get this outcome improvement of the patients is not only to put the algorithm in place into some established workflow but also to think about how you can change that workflow like for example in the surgery. >> Thank you professor lungs. Miss Mahmood if I can come to you. Have you checked the the retention of the knowledge gained by the uh doc's uh train through VR modules? It should be on. Uh thank you for your question. Uh being lower middle income country with limited uh resources in terms of manpower in terms of finances we are always looking towards uh cost-effective innovative approaches. So uh when we did uh this study last year we really found the results promising. So we didn't stop there. We have repeated this exercise and uh last year in this study we made uh 18 residents to participate and this time we have involved 33 residents from our hospital to receive training on intraervical cancer breakchie therapy using uh virtual reality modules. uh and we don't want to limit uh this training to our own hospital. We are planning to organize national training courses and later on regional training courses. Already we are arranging those uh courses by using different indigenous uh techniques on our own. So I think uh this should be continued. >> Thank you. Professor Inji one for you. So many healthcare organizations excel either in research, in education or in clinical care. So very few are able to integrate all three of those effectively. Could you maybe tell us a little bit about how the academic medical center model um has helped sing health translate innovation into better cancer care outcomes? Yeah, I I think at the end of the day, academic medicine I believe is the is the model to bring everything together. Academic medicine really helps us to build the culture. uh as as I alluded to in the opening slide, the much love triangle that we embrace that uh the the three missions, it it's frequently a a clinician who can do all three >> uh who can deliver outstanding clinical care, teach and educate the next generation and do groundbreaking research is frequently known as a triple threat among clinicians. So, so I believe that it is important to to understand that actually you need all three to deliver outstanding care uh innovate care for the future, train and educate the future generation and continue to invest in research and innovation and that those three are the foundation that would ultimately improve patients lives. So it is the the bit building the culture establishing the structure and systems to promote that culture and having the human capital to deliver that and that belief that the three are important foundations to improve patients lives for the future. >> Thank you professor and to the audience I'm going to take one more question up front and then I'm coming to collect your questions. So get those um ready. Mr. Savio uh just the last one for you for this moment. Could you share your experience as a CRP um participant how the achieve results impacts um after concluded with an example? >> Yes, thank you for the question. Um we participated of a CRP that address gallium 68 roificals from 2011 up to 2014. Immediately the next year 2015 we started on routine basis uh performing patients with prostate cancer with gallium 68 PSMA1 and we were the first country in the Latin American region to do this based on our knowledge that we acquired in this previous CRP and also um the amount of patient of protest cancer started increasing a lot Because the national high reimbursements up to 2020 was only for biochemical relapse and then it's improved and also uh incorporated for reimbursements other indications as stratification of the patients and so the numbers of patients increased three times and luckily as we achieved to publish in 2017 a methodology to GMP production of florine pm May 11 through the ALF methodology. This enabled to cope with this huge increase of demands based on the experience we have acquires in previous CRP. >> All right. Thank you Mr. Savio. Now I'll come to the audience. Uh if we have any questions in the room, please show by raising your hands. Okay. I see one question over there. I see another one here. What we'll do is we'll collect both the questions. Please briefly introduce yourself and then indicate which panelist your question is addressed to. We'll start with you sir. >> Uh thanks very much Christine for the good moderation and also the rest of the participants for the wonderful uh deliberation. Um mine again is more of a comment. Um I think often times especially uh in developed developing countries uh when you're introducing treatment techniques uh usually collaborating institutions there's a lot of resistance when it comes to using newer technologies. people to push you to older technologies thinking that maybe newer technologies are more complex you know for you to reign. I don't know why people think people in developing countries are have challenges in learning what would be new technologies because most of these new technologies there's high precision in terms of treatment for example so for example people do resist uh they say no no no go first of all to older technologies then you slowly migrate which which I believe if newer technologies there's high precision uh less side effects, less toxicity. There should be less resistance to allow you know countries adopt newer technologies uh quicker. uh but also I just wanted to make a comment on the issue of uh AI because I know from the experience from Sher M Johansburg for example they they were able you know to treat far much more patients and reduce the waiting uh time you know for the patients uh because of uh issues of introducing uh artificial intelligence for instance and in one of the new centers in Malawi Last point quickly. Uh we are able to use artificial intelligence and uh this was a new center. There were no problems at all. Uh those were my quick comments. Thank you. >> Thank you very much. We'll see if somebody wants to respond but for the moment we'll take the next question. >> Uh good morning. Thank you very much um to such a a panel of uh and and the information shared that is really um eyeopening. I've learned a lot myself. I'm Katherine Mava. I'm a radiation oncologist based here in the division of human health. Uh my question is to anyone uh because AI seems to be the buzzword and my question um even when I practiced are issues of what challenges do you find in adapting and implementing AI tools in clinical practice? And coming to I think I saw a slide where there was gen Gen Z's and uh uh the alpha generation they're very quick obviously to adopt and embrace technology but there's also a concept especially when I look at LMIC's in terms of the quality of data because AI did not come up it had to learn uh to create these automated uh tools across um the the spectrum of clinical care. So it would be interesting to just uh learn a little bit about challenges and strategies uh to address challenges in implementing these tools and adapting them to clinical care so that we do not get a a case where now we have geographic misses because um a tool was used in an inappropriate setting. Thank you. >> Thank you very much. I'll come back to um to the panel now. Nobody specifically was addressed but if you want to respond to the comment uh or tackle the question directly please pick up the mic and go ahead. >> Thank you. So so I would like to talk a bit about this question about challenges. So I think there are several and the three ones that I feel are the most strong ones. One is very simple to explain which is the resources of IT department. So we very often see that it the resources that are needed in order to introduce that in hospitals are strained and so that causes delays because the it needs resources on the IT side on the integration side into a hospital to bring that into place and I think a lot of the efforts right now is kind of to streamline that and in order to do it once and then replicate it easily. The second point is second challenge is um that we very often see that it takes a while to once you have the technology to find a good workflow around it. So just plugging it in into a existing workflow sometimes slows you down and you need to adapt a bit and learn a bit how to to organize in order to get the the advantage out of it. But then it's there and I think there it's really helpful to also work with the the producers of these softwares because they are I think very open to to learn how they can be more useful. And the third challenge is I think the representativeness of the data. So how is the training data and how is the data that the patient population the health care systems the circumstances of health care the biases the confounders that we see everywhere and that are different everywhere. How well is that represented in the models and which of those do we actually not want to have represented in the models? Right? Economic factors that influence the care pathways of patients we might not want to be reflected in that. We would like to have the biology reflected. And I think initiatives like the Sora project that is uh that is led by IEA which really tries to say well we would like to do validation data collection on a global scale. I think these type of initiatives are necessary in order to have models where we are confident that they are reliably working on a broadwide patient population. >> May I add just a short comment on on technology. So technology is not good by definition. So we have to test technology >> and we have to consider the environment in which technology is placed because need both good technology that has demonstrated to be useful in the outcome. So mean health technology assessment and also place it in envir environment that is able to manage and and and to treat uh the patient with with sufficient expertise. This is the reason because uh also the initiative of this agency is h is is very useful to open all the center with technology more than now for training of other of other people and for artificial intelligence uh uh we we we need uh to control we need to check because uh every day I in Italy I work in Milano but I believe that is the same in other part of the world of in Europe in the United States every day there is one new product >> without any type of validation and if you put uh bad data in a in a in a system maybe the more sophisticated but the exit is bad data. So I believe that uh need need to be to to be to to be find some rules for that. >> Okay. Thank you professor inj I I'll I'll respond to the question about how do we you know how do we facilitate the adoption of technologies within the health system and I would say that we need to do three things. The first thing is I think we need to manage the change process. Frequently we think about the adoption of a technology as a technical change but in reality it is an adaptive change. It's actually cultural change is organiz organization the way we work and and hence I think we can't just train the individual who's using the technology. We need to train the entire team and the ecosystem that's involved with the technology and bring everyone along that change process. So the first thing it is really managing it as an adaptive change rather than a tactical change. The second point is humans are resistant to change or rather we like change when the change happens to someone else. We don't like change when it happens to ourselves. That is known as the paradox of changing and hence we do want to try to adopt the technology in the most painless and seamless way and not to disrupt the usual work process as much as possible so that people don't resist that new technology within the workflow and I think the very last point is we have to align the incentive systems we do need to ensure that the technology has the proper financial remuneration insurance government uh you know private sector and so forth. involved and also to ensure that everyone involved in the whole system change have their incentive systems aligned so that they will effect that change together as a whole team. >> Uh Miss Makmuras, you wanted to say something. This is the last intervention I can take before I have to wrap up our panel. >> I mentioned about Gen Z and alpha generations. Everybody would agree that younger generations are more ready to adapt or embrace newer technologies. For instance, uh when we started the use of these virtual reality modules for training in uh cervical cancer breakchie therapy, all of the residents, they were eager to learn through these modules. Although uh as I mentioned that our male doctors are not allowed to do cervical cancer breakchie therapy but after all they have to get through the exam and then they have to learn for their independent future clinical practice. Moreover, all of us have moved gradually from 2D to 3D then to IMRT, TVMAD, then stereotactic radiation and now we are doing MR based breaky therapy etc. So gradually we have managed to adapt to the changing requirement of uh precision radiation. >> So I think there's always resistance to change but uh if you are willing to change yourself you can do it otherwise no >> right >> thank you everybody. We've run out of time because we have to make way for the next session which is starting at 11:30 promptly. But I just want to thank our speakers today. Thank you so much for your presentations and your insights here. I know we could have really gone for more questions but we have run out of time for everybody in the room. Our closing session will start promptly at 11:30. So it's probably best to stick around here and not uh go anywhere unless you need a very quick toilet break. But please let's be back here on time for the s speakers at the closing session. Please let's assemble in the frontier at 11:25. Thank you once again everybody. Much appreciated. Thank you.