So I'd like to thank Gene and uh Eden for their excellent presentations. And before we close this symposium, I want to do two things. One is talk about the cases that we presented at the beginning uh very briefly and then look to the future where we are going with the continuous glucose part, right? So the first patient uh remains on mixed insulin with uh different ratios and his time and range has increased uh not quite enough, but he's getting less hypoglycemia, which is an important first step. So uh we need to focus a little bit more on his diet, uh postal excursions uh and, and make further adjustments. The second patient uh uh glicozide was stopped and the confusion cleared. Uh And you now see uh at least no hypoglycemia, we still have to address the hypoglycemia in this particular patient. So years before and after at least you stopped the problem that the patient was having. We now need to move into using some other therapies that will bring the glucose down without uh hypoglycaemia. And we are fortunate to have many medications that are now available for that. Let's look now to some of the newest studies with CGM. Uh and, and perhaps talk a little bit about the future. And I want to start with something that's being presented at this meeting uh uh at in San Diego this year. And this is about promoting patient engagement. I think this is one of the really untapped metrics uh and, and things that we've always talked about motivating our patients and educating our patients, but we've not given them the tools to get more engaged in what they do. And I think CGM has been a game changer in relation to that. It has really allowed change in behavior and, and uh we all talk about this a lot but documenting this has been difficult. And I uh want to congratulate the uh authors of this particular study that's been uh uh uh presented here. It's a study done from Canada where they have used a self management questionnaire and a diabetes distress scale and tested it before and after CGM uh to see how uh uh motivated they are. And uh they looked at things like people's capability, their personalized knowledge, uh opportunities, better relationships with their, with their uh health care providers, better social uh relationships uh very clearly. They have patients have grasped on the opportunity and motivation uh that, that uh to improve that glycaemic control and this has reduced that diabetes distress considerably. We often uh dismiss things that about patients having anxiety and depression uh or terminology and ignore this diabetes distress, which is disease related. And CGM allows people to overcome that. So this psychometric uh uh characteristics of this scale uh has the potential to screen people with diabetes for engagement about their diabetes uh self management and and see the improvement uh with CGM and look at its uh impact on patients capability and opportunities and motivation to improve their glycaemic control. Another study I want to point out is a comparative study looking at uh this was presented at recent European meeting, looking at different uh uh glucose meters and their accuracy uh at various levels. We we was very used to looking at this so called MA RD uh uh graphs which always seem to correlate very well uh in my view. But here you're looking at comparisons across various uh uh meters old and new, the older Dexcom, uh the newer ones, uh the older Freestyle Libre as well as the newer ones. Uh And I'm very pleased to see that both uh the Dexcom G7 and the Freestyle Libre three have ex ex excellent accuracy, not just in general, but at each level Ooo of blood glucose, less than 70 70 to 1 80 greater than 1 80. Uh whether you want to be within 15% within uh 20%. It, it all looks very uh very good. Here is another uh uh a paper that was uh uh uh presented published recently comparing three different uh types of uh blood glucose monitoring systems. Uh And comparing it with uh a, a lab, blood glucose which is here in, in fasting glucose. And it compares, it shows you you as a presty libra performing very well. Uh and uh a number of errors in, in, in another system. Uh Here are these uh this kind of equations that you often see the MA RD. Uh It, it compares in dialysis patients and I think that's important because uh these people fluctuate blood glucose, fluctuates a lot as you know, sometimes insulin is extracted. Uh uh Sometimes it's not extracted as efficiently as it should. People may get hypoglycemic because they don't eat on dialysis. So we need good accuracy across a range of blood glucose. Uh And uh here is text from G six I uh uh uh and, and here is a freestyle libre as new meters uh come out, we will be seeing more and more of these kind of things. And I think in dialysis patients where it's important. Uh the really big advance in in uh use of continuous glucose monitoring has been linking it up with insulin delivery devices, the so-called E ID or automated insulin delivery. Uh traditionally in the US, in the last few years, we have been using this with the uh Metronic and uh uh Dexcom CG MS with the Metronic pump and the uh tandem and now with the uh uh uh with the non tube. Uh uh tubing, uh uh uh insulin batches, uh Freestyle Libre has now been approved uh for a continuous glucose monitoring which allows an A ID system. And uh the uh the uh uh companies partnering with a variety of partners. And in Europe, they have partnered with a company called IPSO Me and CAM diabetes to have the first A ID system with a Freestyle Libre. So, uh this is a very low cost insulin delivery system. So I'm looking forward to uh uh making this uh A ID systems more affordable across the world and it allows automatic adjustments of insulin delivery based on freestyle Librate three sensor readings. Uh So the blood sugar is dropping low. Uh it would cut down or switch off the, the insulin delivery. If it's high, it would deliver more and you can still get uh readings through uh the the systems that are available. So here are the components of the system or you are close so-called closed loop system. Uh You need uh the, the, obviously the sensor and the delivery system and a communication between the two. There's a Bluetooth con uh connectivity between them uh with the Ipso Bump uh and that controls the insulin delivery. And here is an example of how it works. So you can use it open loop uh in auto mode or you can use, put it on, but it becomes a closed loop system so that uh it will deliver the right amount of insulin. And uh what is illustrated here, you could see somebody who's uh insulin is not being changed because the glucose is, is where you want to be. This is a little bit more detail uh that I I won't go into every little detail of it. It shows you as the glucose is dropping the insulin delivery, uh uh is cut down as the uh uh glucose rises, the insulin delivery increases And you try and keep uh blood glucose on, on a pretty level, Kel and the patient has less variability, certainly less hypoglycemia and less hypoglycemia. What's the future? Uh We, we are looking at a variety of things I mentioned, uh you know, the discrepancies between A one C which has been the gold standard and time and range and we need more studies to show how well time and range and other uh c geometrics correlate with complications of diabetes and how changes in that will lead to a reduction in complications. We also need to track multimodal monitoring systems. Everyone's into variables and, and using their phones to, to measure things. So, uh you know, I can see the day where we have one simple little thing on the wrist that tracks on one device either on the phone or on the, on the watch your ketones, your glucose, your heart rate, your blood pressure, heart rate variability. We're still not there yet. I mean of all the things the most challenging one is to actually measure blood pressure on a continuous basis. And I think it's actually very important. So one day we'll be able to a patient call anybody and we'll all be using this to see all the time where we are and have reminders about other tests that are needed and can be done. Many tests can be done at point of care. Today, we have terrible metrics for measuring urine microalgae. Although we have very good treatments for chronic kidney disease. Uh this could be done at point of care. Uh lipids can be done at point of care can be done uh in, in a pharmacy, for example, or maybe at, at, at your workplace and the same with eye exams. And there's a lot of data now on artificial intelligence recognizing diabetic retinopathy with a within one minute. So uh that's going to change how we manage diabetes and A I derived precision nutrition based, you know, the NIH has launched a precision nutrition initiative using the all of us uh database. There are a few other precision nutrition uh studies going on uh based on uh continuous glucose monitoring. Uh uh They we we're looking at a variety of things uh at, at Hopkins, they're doing a thing with a dash diet and looking at continuous glucose monitoring. Uh ultimately will all insulin treatment be done with closed loop systems, not just with pumps, but maybe with the smart pens. And uh we, we will be able to be very accurate in how we manage uh patients with diabetes. Keep them all in perfect glycemic control all the time with very little variability, very little hyper and hypoglycemia and a very low rate of complications. Thank you very much for your attention.