We are going to be addressing lupus nephritis, pruritus in patients with chronic kidney disease, and we'll also be discussing a return on investment or a payer impact for a biomarker model of chronic kidney disease intervention. Without further ado, we'll begin with the first talk, which is AURORA phase III Trial that Demonstrates Voclosporin Statistical Superiority over Standard Care in Lupus Nephritis. Our presenter will be Keisha Gibson. She's Associate Professor of Medicine and Pediatrics, and she is the Chief of Pediatric Nephrology at the University of North Carolina School of Medicine. I'm very much looking forward to this presentation. Without further ado, Dr. Gibson.
Okay. Well, I would like to again say welcome to everyone, and thank you to the National Kidney Foundation and all of the sponsors of this meeting that worked so hard to make sure that we could join you virtually today. I have the honor of representing the AURORA Study Group to present the results of our phase III randomized trial, which assessed the superiority of voclosporin in combination with standard of care therapy over standard of care therapy alone in patients with active lupus nephritis. These are my disclosures. As many of you on this call are quite familiar and aware, the pathogenesis of lupus is quite complex. It likely represents the interplay of multiple genetic and environmental interactions that ultimately lead to the loss of a tolerance of self-antigens, and in particular, loss of tolerance of nuclear debris from apoptotic cells.
These antigens can bind to viral particle receptors and get presented by antigen-presenting cells, which then leads to polyclonal expansion of autoreactive lymphocytes and the production of measurable antibodies that we're all familiar with, like anti-nuclear antibody, anti-double stranded DNA, anti-Smith, et cetera. Now, the result of this cascade is a chronic and often disabling autoimmune disorder that can affect over 500,000 people in the U.S. By and large, the overwhelming burden of this disease is seen in women. Lupus is highly heterogeneous and, in fact, can affect almost any organ or tissue system, and in its more severe forms the kidneys are involved, and we can see quite a bit of inflammation and chronic damage and up to 50% of lupus patients, in fact, will develop lupus nephritis.
Clinically, we may see leakage of large amounts of blood proteins in the urine or proteinuria, and this is often a very clinically significant feature of lupus nephritis. When we are lucky and we see early treatment responses in our patients, we know that their long-term outcomes measured by proteinuria reduction is quite good. Unfortunately, in 10%-30% of our patients, despite our standard of care therapies, we see progression to end-stage kidney disease within 15 years of diagnosis. As you can imagine, this confers a huge cost to overall health, quality of life, and excess burden to the healthcare system. We understand that T-cell mediated immune response is definitely an important feature of the pathogenesis of lupus nephritis.
We also understand that the podocyte injury that occurs in conjunction with ongoing immune insult in the kidney is another important factor in the clinical presentation of the disease, and in fact, often leads to proteinuria. Again, a very common hallmark of our clinical presentation. What might the potential role of calcineurin inhibitors play in lupus nephritis? In fact, the influence of calcineurin inhibitors in proteinuria kidney disease has been shown in multiple studies to involve two separate mechanisms. There are clear direct effects on the immune system, resulting from the reduction in NFAT levels, which leads to downregulation of cytokines that otherwise would lead to widespread tissue damage. Separately, we understand that there is an extra immunological effect involving podocyte stabilization. If you look at this figure here on the right, and focus on this molecule synaptopodin.
Synaptopodin is an important molecule in the stabilization of the podocyte cytoskeleton. Anything that damages a podocyte cytoskeleton can cause podocyte effacement, and that in turn causes proteinuria. Calcineurin inhibitors have been shown to block the calcineurin-mediated dephosphorylation of synaptopodin, and by doing this promotes the stabilization of the podocyte actin cytoskeleton, conferring a potential disease-modifying effect of reducing proteinuria. Into voclosporin. Voclosporin is a novel calcineurin inhibitor, and it's distinguished from cyclosporine A by this single carbon extension with a double bond. Now, there are a few advantages that we've found of voclosporin over our traditional or legacy calcineurin inhibitors, and one of these key advantages includes its more predictable pharmacokinetic and pharmacodynamic relationship, which essentially eliminates the need for therapeutic drug monitoring. This is a huge advantage. Moreover, we found that voclosporin is almost four times as potent as cyclosporine A.
Again, another huge advantage of this novel calcineurin inhibitor. Our study group, after the completion of a proof of concept trial, which included seven patients, completed a phase II double-blinded randomized control trial of 265 patients. In this phase II study, we looked at voclosporin layered upon standard of care therapy, defined as mycophenolate mofetil and corticosteroids, to a control arm of standard of care alone. The primary endpoint of this phase II trial was renal response at 24 weeks, mostly driven by proteinuria. Within this study, we found that there was a 14% higher renal response rate in that voclosporin arm over the control arm. There additionally was a secondary endpoint that was assessed in this phase II trial at 48 weeks, again, looking at renal response. There we found a 25% higher renal response rate over the control arm.
Based upon these phase II studies, we went into the phase III double-blind randomized control trial, and the remainder of my presentation will be dedicated to presenting the core analyses from this study. Both the AURA phase II study and the AURORA phase III study have similar inclusion criteria and primary endpoints. In fact, the only differences are really highlighted here in bold. To be included in the AURORA trial, patients had to meet a diagnosis of lupus based upon standard ACR criteria. The majority of patients enrolled in this study had a kidney biopsy within six months of study entry to confirm histologic diagnosis of active lupus kidney disease. This is starred because there is a minority of patients, less than 10% of trial participants, that had a biopsy that was outside of the six-month window, up to two years.
They qualified on the basis of other markers of active kidney disease, including things like doubling of serum creatinine. All patients had biopsy-proven lupus nephritis, Class 3, Class 4, or Class 5, either alone or in combination with a proliferative lesion. All patients had a sizable amount of proteinuria, with a UPC greater than or equal to 1.5, or for our Class 5 lupus nephritis patients, a UPC greater than or equal to two. A primary endpoint in the AURORA trial was a renal response at 52 weeks, and renal response here is defined as a UPCR of less than or equal to 0.5 and the inclusion of all of these safety parameters.
They also had to have a maintained eGFR greater than or equal to 60, or no confirmed decrease from baseline of greater than 20%, and be able to be maintained on a low-dose corticosteroid throughout the study, and needed to not require administration of rescue medications. This slide depicts the design of our study. Patients were randomized one to one to either the voclosporin arm, which included a standard dose of 23.7 mg twice a day, layered upon standard of care therapy, here mycophenolate mofetil at two grams, and oral corticosteroids given as a rapid steroid taper, as you see outlined in this below table. They were randomized to our control arm, which included standard of care therapy alone, again, which included mycophenolate mofetil at two grams and oral corticosteroids given as a rapid steroid taper using the same design.
I would like to highlight that this trial includes a blinded optional two-year extension study, so a lot of patients are rolling over into this extension trial, which we think will provide some valuable long-term data on benefits and risk of voclosporin. Again, I think this is an incredibly valuable component to this study. Overall, 758 patients were screened, and 357 patients were successfully randomized. Most of the screen failures were explained by patients that failed to meet the eGFR criteria of greater than 45 mils per minute or had a UPCR that was too low to be enrolled. 178 patients were enrolled in the control arm, 179 in the voclosporin arm, 147 or 83% completed this control arm, and 162, or just over 90%, completed the active voclosporin arm.
Looking closer at these 357 patients that were enrolled, you'll see that there are really no differences between our control arm and our voclosporin arm in looking at age, sex, baseline weight, baseline proteinuria, or even geographic region of origin. A pretty diverse population. If we focus on specific renal parameters, again, there were no significant differences between our control arm and voclosporin arm in looking at GFR at baseline, again, proteinuria or even looking at histological lupus nephritis class type. One thing I would like to draw attention to here is that this study does provide us a fairly diverse group of individuals in regards to histologic type.
In thinking about the dual mechanism of voclosporin with both the immunologic effects and the non-immunologic effects of podocyte stabilization, I think it's critically important that we have a sizable representation of a lupus nephritis phenotype that is earmarked by podocyte damage. If I had drums, I would play it in the background, but thankfully for everybody on this call, I don't. I will simply say that this is probably one of the most important slides of this talk. The AURORA trial met its primary 52-week endpoint, showing a renal response rate of 40.8% for the voclosporin group, compared to 22.5% for those receiving standard of care therapy alone. With this delta of about 18.3%, this was a statistically significant difference, with patients in the voclosporin arm being 2.65 x as likely to achieve remission over those in the control group.
We're also pleased to report that all pre-specified secondary endpoints were met, including our renal response at 24 weeks. Here, 32.4% versus 19.7%. Partial renal response, defined as a UPCR reduction of greater than 50% from baseline, both at 24 and 52 weeks. Even the median time to achieve a UPCR of less than 0.5 was much faster in the voclosporin arm versus the control arm. If you look at this top graph, you can see that there was a very early separation. Even within the first month, a separation in the number of patients achieving a UPCR of less than or equal to 0.5. If we look at the median time for half of the patients enrolled to reach a UPCR of less than 0.5, you'll see that those in the voclosporin arm achieved that almost twice as fast as those in the control group.
The median time for 25% of these patients to achieve a UPCR less than or equal to 0.5, again, much faster in the voclosporin arm over the control arm. Again, to summarize, in all of the pre-specified secondary endpoints across the board, voclosporin outperformed standard of care therapy alone, as marked by renal response at 24 weeks, a partial renal response at 24 and 52 weeks, and even time to achieve a UPCR less than 0.5. I didn't present this data already, but we also looked at time to 50% reduction in UPCR, so sort of a partial response, if you will. Again, the patients enrolled in the voclosporin arm outperformed those that were in the standard of care arm.
Taking a closer look at the study population, the benefit of voclosporin was observed in all pre-specified subgroups, including by age, by sex, by race, by biopsy class, geographic region of origin, and MMF exposure at screening. As many of you on this call are aware, calcineurin inhibitors can cause some degree of vasoconstriction, which may lead one to wonder if the reduction in proteinuria is in any way attributable to hemodynamic changes in GFR. As you can see here, the eGFR for both groups remained relatively stable throughout the 52-week trial. Folks enrolled in the voclosporin arm saw about a 1.2 mils per minute reduction in GFR over 52 weeks, and those in the control arm saw a slight increase in their GFR of 1.9 mils per minute. Again, this was not statistically different. The story is the same if you look at serum creatinine alone.
calcineurin inhibitors are also known to increase blood pressure in patients. In this study, you can see that there was really no differences in either systolic or diastolic blood pressure between the voclosporin and control groups across the 52-week period. In fact, both groups truly achieved a slight reduction in blood pressure over time, and it was noted even before 24 weeks. You can make the argument that maybe this was due to some reduction in disease activity, and these are analyses that our study group are going to investigate a little further. What about those patients that may have required dose adjustments across the study? Dose adjustments including interruption or reduction and re-escalation were all implemented according to a pretty stringent eGFR reduction protocol, of course, after excluding potential contributing factors.
To recap, overall, there was an 18.3% increased response rate in those that were enrolled in a voclosporin arm over the control arm. If we focus on those patients that required a dose adjustment, but then were able to be re-escalated to our target dose, you will see that there was still a considerably higher response rate in those 31 patients over those that were enrolled in the standard of care therapy arm. If we look at patients that required a dose adjustment because of GFR changes and were unable to be re-escalated to the target dose, again, 16 patients, but again, these patients still had a greater renal response rate over those that were enrolled in the standard of care arm. For me as a clinician, these data are important because this states that personalized dosing may not lead to compromise in efficacy.
I think that's very important. In my mind, safety is just as important as efficacy, and while we are of course excited that this study met primary and secondary endpoints, we're just as pleased to see the comparable safety data between the control groups and voclosporin that was sort of add-on therapy. If you look at adverse events, serious adverse events including serious infections, treatment-related events leading to drug discontinuation, death rates, or disease-related adverse events, there are really no difference between these two arms. Again, despite this being add-on therapy, the safety profile is very comparable. In summary, the positive benefit-risk profile observed in our phase III study confirmed the treatment effect that we saw in the phase II study comparing voclosporin as add-on therapy to MMF and steroids versus standard of care treatment alone.
The odds of achieving a renal response on voclosporin therapy were 2.65 times greater than control, all while still maintaining a comparable safety profile. In my mind, there's no question that we've seen advancements in the care of lupus patients over the last decade, as a nephrologist, I think that we are seeing a therapy to potentially move the needle specifically in the subpopulation of lupus patients with active kidney disease. With that, I will close.
Great. Thank you, Dr. Gibson. That was a very interesting presentation. We just heard the AURORA phase III study, voclosporin in lupus nephritis with impressive proteinuria attenuation. I will ask you to enter your questions into the question box for the faculty Q&A. We will be answering all the questions at the conclusion of this session. I want to thank you for your attention, and we're going to transition from lupus nephritis to pruritus. The next presentation is on the efficacy and safety of oral difelikefalin in stage 3-5 CKD patients with moderate to severe pruritus, a response analysis from a randomized, placebo-controlled phase II trial. We are pleased to have Ahmed Awad present, who is an Assistant Professor of Medicine at the University of Missouri, and he is with the Kansas City Kidney Consultants in Kansas City, Missouri. Without further ado, Dr. Awad.
Thank you, Dr. Vassalotti. I want to also thank you for the NKF team that made this possible. I am honored to be presenting on behalf of our group. These are my disclosures. A background of the study. The traditional thinking is that pruritus is more prevalent in severe chronic kidney disease and in patients undergoing hemodialysis. Surprisingly, 60% of our patients in this study had pruritus in CKD 3. Pruritus is prevalent across all stages of chronic kidney disease, not only in patients undergoing dialysis. It is underdiagnosed, and there's a paucity of intervention because we don't have approved treatment for pruritus. As a nephrologist, it has always been difficult to treat patients with pruritus on dialysis. Not only on dialysis, but also in chronic kidney disease, because we give them gabapentin, we give them BENADRYL or Atarax, and the next visit, the patient is not improving.
A majority or a few do. There is no approved treatment in any country for non-dialysis patients with chronic kidney disease. In this study, it really surprised me that 60% of this patient population were in CKD 3. That leads me to how we were trained about pruritus or "uremic" pruritus. I don't think it is only uremic, but there may be other pathogenesis of the pruritus in our patient population, whether it is inflammation, as we all know CKD is an inflammatory disease, or metabolic disturbances, or dysregulation in the immune system that cause pruritus in our patient population. Difelikefalin, I will be referring to it as DFK throughout the presentation, is a novel selective kappa opioid receptor agonist that does not cross the blood-brain barrier and does not bind to the mu-opioid receptors.
That means, the hope is that there is no addiction from this, there is no dependency, and no withdrawal symptoms once the medication is stopped. Throughout these trials, we have demonstrated that there is no dependency or addiction to the medication. It is peripheral receptors, kappa opioid, and does not cross the blood-brain barrier. As you all know, there was a recent publication in The New England Journal of Medicine called the CALM-1, C-A-L-M-1, from phase III-A trial. IV formulation of DFK demonstrated significant improvement in itch intensity in patients on dialysis. It also improved their quality of life versus the placebo. The study design is a 12-week trial with a seven-day run-in. Small sample of 240 patients were randomized to four arms. The question is: how do we distinguish a dry skin itching versus itching of chronic kidney disease?
Prior to enrollment, patient has to answer a scale called the Worst Itch Numeric Rating Scale, or WI-NRS. I'll be referring to this as NRS throughout. They have to score at least five points or above to be in the trial. One of the inclusion criteria, also, self-reporting experiencing daily or near-daily pruritus during the month prior to screening. One of the exclusion criteria was pruritus must be of CKD and no other. We look at the medical record, we ask the patient whether they've been to a dermatologist, have they been diagnosed with any other dermatological causes for their itch. We really try to weed out other causes of pruritus other than CKD. The four arms were DFK 0.25 mg, 0.5 mg, 1 mg, and a placebo arm, since there is no approved treatment for this disease.
The primary endpoint was change from baseline in weekly mean of daily NRS score. These were the secondary endpoint, proportion of patient achieving more than three points improvement from baseline. Complete response, defined as achievement of more than 80% of the NRS score, equal to zero or one. Itch-related quality of life using the Skindex-10 and 5-D Itch Scale, and I'll show you in a minute what these are. Of course, finally, the adverse event and serious adverse event. The key here was to make sure that patients, when we enroll them, that they have itching of chronic kidney disease. This is the WI-NRS, or the Worst Itching Intensity Numerical Rating Scale.
It's been validated with the dermatologists for their atopic dermatitis or psoriasis, and has been used for our patients with chronic kidney disease, and also has been used in the publication in The New England Journal of Medicine for the IV formulation. It is a scale from 0-10, 10 being the worst itching, and then it's divided into three categories: mild, moderate, and severe. zero to three, mild. Four to six , moderate. 7-10, severe. This is the Skindex-10 scale. It was developed specifically for assessing itching-related quality of life across three domains in hemodialysis patients with pruritus. The higher the number, the worse the itching or the quality of life. It's more personable, meaning that it asks about the persistence, the reoccurrence, the appearance of your skin, scratching, frustration, annoyed, embarrassed.
These are the type of questions we asked the patient when we were enrolling them in the clinical trial. The 5-D Itch Scale assesses five dimensions of itch, duration, degree, direction, disability, distribution, during the two-week recall period. It's basically asking the patient, how long have you had it, the location of the body, the degree, mild or severe, and even includes sleeping disturbance. On the sleeping disturbance, it's a personal story with my daughter that has dry skin and how many times she woke up at night to wake me up or mom to tell us that, "I'm itching, I cannot sleep." Sometimes itching is something we don't think of unless you have a personal experience with it or a family member that had it.
It's very much prevalent in our patient population, not only in the severe CKD and patients on hemodialysis, but also in CKD 3 patients. Patient demographics and baseline disease and itch characteristics is very much similar across the board. What is surprising and interesting here, as you see, the patients with CKD 3, almost 60% of these patients were in CKD 3. Patients were in CKD 4 were across the board very much similar. Hypertension, and this is what I want to bring attention to. For the NRS score, they have to have five points or higher to be enrolled in the trial, and across the board, you see here, the itch scale was seven, that falling into the moderate to severe category, and it was similar across the different arms and, I'm sorry, different doses of the patient.
Looking at their hematology and serum chemistry, really nothing to point out in this slide other than it was similar across the arms. Here's the primary endpoint. Change from baseline in the NRS at week 12, and the 1 mg seems to stand out, and there was improvement by 4.4 points. If they have scored seven, there was an improvement back to three, and that falls into the mild category. That was a statistically significant difference. Just as a reminder, this is a phase II clinical trial, which means we were looking at different doses and which one will be more efficacious in improvement of the NRS score. Looking at when did the effects start, the response started at week two.
As a matter of fact, if you want to look at it, probably one and a half weeks, we saw a response of reduction of the NRS scale. Most significant started at week two and maintained throughout the 12 weeks. Looking at the secondary endpoint, the 1 mg again showed 70% of the patient achieved more than 3 points improvement in the NRS scale. That was the most out of the three groups, whether it's 0.25, 0.5, or 1 mg. Looking at three-point improvement in the NRS at 12 weeks stratified by CKD status. DFK showed positive trend improvement in the NRS across the different stages of CKD. Just as a reminder, this is a small sample, so it may not reflect more improvement or not, and it was not powered for the different CKD.
This is one of the other impressive results of this trial. The significantly greater proportion of patients who received DFK at all three doses level achieved complete response when compared to the placebo. Looking at these p statistical significant difference. As we mentioned before, complete response is defined as achievement of more than 80% of NRS score equal to zero or one. Our patient that has a score of seven at week 12, almost 40% of them reported a zero or one NRS score. All three doses showed significant complete response. Again, the one that stood out was the 1 mg . There was a significantly greater proportion of patient in the DFK 0.5 and 1 mg groups had very much improved or much improved in Patient Global Impression of Change.
You ask the patient one of the questions, much improved or improved, and you see the 1 mg again, there was almost 20% improvement from baseline using the Skindex-10 and 5-D Itch Scale. I think I went ahead in the slides here. This one was not much improved, or this was looking at the Skindex-10 and 5-D Itch Scale. That was the 20% improvement from baseline. This one is looking at the Patient Global Impression of Change scores versus placebo. The 1 mg and the 0.5 mg patients reported that they were improved or much improved when compared to the placebo. Again, the 1 mg seems to stand out when compared to the other doses. Summary of the adverse event. Serious adverse event, death, and what made patients discontinue the medication.
As you see, looking at the death here, there were three patients in the placebo and only one patient in the 1 mg. Looking at the causes of death in the placebo, it was a cardiac or respiratory failure. The one death in the 1 mg group was coronary artery disease-related. Looking at the serious adverse event, the one that stood out was fall, was about 1.5%. Discontinuation of treatment, it was diarrhea, nausea, and dizziness. Most commonly reported adverse event, dizziness. In the 1 mg, the fall. I have to bring this point out that those patients that had dizziness were not the ones that fell, and those who fell did not have dizziness. They were two different reports on these adverse events. For example, an elderly gentleman that fell because he misplaced his walker, and that's why it was reported as an adverse event.
Again, those patients that had dizziness did not have the fall, and vice versa. Constipation and diarrhea were very much similar incidents. Urinary tract infection and hypertension here were no dose escalation of these AEs in those different dosage. AE by CKD. We all know the lower the GFR, the higher the AE, and that's showed across the board. Stage 4 and 5, on dialysis or non-dialysis, had more serious adverse event and adverse event than those with CKD 3. We see that in all of our patients with severe reduced GFR, that they have more adverse event than those with a better GFR. In conclusion, chronic kidney disease-associated pruritus, and I'm using associated pruritus and not uremic pruritus because I believe that there's more pathophysiology and pathomechanisms for cause of pruritus other than just uremia, and could be inflammation.
It is under-recognized but distressing condition which presents across all stages of chronic kidney disease. We saw that 60% of our patient population were in CKD 3A and B. This is the first randomized placebo-controlled trial of DFK in patients with Stage 3 to 5 CKD, non-dialysis and dialysis, with moderate to severe pruritus. As we saw in the NRS scale, was 7. Oral DFK 1 mg met the primary endpoint, demonstrating significantly greater improvement in the NRS scale versus the placebo in patients with CKD-associated pruritus. As we all saw that the treatment effect emerged at week two and persisted throughout the 12 weeks. DFK 1 mg was associated with clinically meaningful improvement in pruritus. Nearly 40% of patients achieved complete response.
As I mentioned before, the definition of a complete response on the NRS scale at week 12, it has to be either zero or one, which was more than 2.5 x greater than placebo. Oral DFK was generally well-tolerated with a safety profile consistent with the prior studies of the IV DFK. Further evaluation with DFK 1 mg warranted in a phase III trial in CKD patients with pruritus. I want to thank you. Open for a question.
Thank you. Thank you. We're going to hold the questions for the end of the session. Please type your questions into the Q&A box, and we'll look forward to answering those at the conclusion. That was a very nice presentation on difelikefalin in pruritus with patients with CKD 3 to 5, a phase II study. We will go from phase III trial in lupus nephritis to phase II in pruritus and CKD, to now we're going to look at something that actually is quite important, and that is the return on investment for interventions in CKD. That's something that can impact decision-makers in our health system.
I'm very much looking forward to the next talk, which is an evaluation of payer budget impact associated with the use of artificial intelligence with an in vitro diagnostic to modify diabetic kidney disease progression. Tom Goss, who is a PharmD and Senior Vice President of Health Economics and Outcomes Research at Boston Healthcare Associates in Boston, will be presenting. Without further ado, Dr. Goss.
Thank you very much, Dr. Vassalotti. I appreciate the introduction, and thank you to all of our participants for joining. I hope everybody's doing well out there. I'd like to acknowledge a couple of my co-authors who've really contributed substantially to this work. Dr. Manasi Datta, Will Birchenough, Dr. Michael Donovan, Dr. Steven Coca, O. James Sterling, and Elaine Wang. All of them have been key participants. I'm honored to be presenting on their behalf. In terms of the topic, I'd like to review briefly the background and aims of our study, go through some of the detailed methods, provide you with a summary of our key results, and then discuss our conclusions. At that point, we'll open it up to Q&A for all of the presentations. Also, I would like to acknowledge that this study has been funded by a research grant from Renalytix plc.
Briefly, the audience here, I'm sure, is well-versed in some of the challenges with kidney disease. Diabetic kidney disease obviously can lead to progressively poor health outcomes and increased cost if interventions are not employed. As patients progress through each successive stage, the disease becomes more costly. Currently, it's estimated that about 37 million Americans have chronic kidney disease, and of them, about 30% have type 2 diabetes as well. We refer to that as diabetic kidney disease or DKD. DKD, why is that important? It accounts for about 50% of patients who will experience a rapid kidney function decline, and they are at the highest risk for progressing to end-stage renal disease and requiring dialysis and transplant. They're a group of patients with high unmet need and a significant opportunity for intervention.
In addition, DKD and ESRD cost the U.S. healthcare system an estimated $114 billion annually and exceeding that. As I mentioned, there's significant unmet need. The current method for DKD risk stratification, it fails to identify about half of the patients who ultimately have rapid kidney function decline. Up to two-thirds of these patients initiate dialysis acutely due to a crash, which is a very costly way to initiate dialysis, but it's also very challenging and creates a huge amount of morbidity for the patients themselves to go through that. Obviously, we know that many patients who are at high risk or increasing risk often don't get referred from primary care to nephrologists early in the stages of their disease when the most opportunity for intervention is actually available.
We feel that there's an important need for a predictive tool that will help us to identify these patients at high risk and improve our intervention strategy. Here I would like to just share with you a little bit about our validation study and the patients who are enrolled in our study. The test, it's an artificial intelligence-based test that's a clinical diagnostic. It's using a combination of both in vitro analytes as well as advanced machine learning algorithms combined with EHR or electronic health record data to really identify and stratify patients according to their risk. It helps us to identify patients at the greatest risk for experiencing rapid kidney function decline.
In the table over to the right, you'll see this is actually the current CKD staging based on KDIGO guidelines, and the group of patients that we are most interested in, where they have perhaps the most variability or ambiguous clinical decision-making and probably the greatest opportunity for intervention that will slow down the progress of the disease, is right here. It's in stages 1, 2, and 3, but excluding, of course, stage 1G1 and stage 2G2. We're most interested in identifying these patients at risk where intervention can take place. The other key points to recognize is that patients in these particular risk strata are approximately 25 million in the U.S. fall into this particular group of patients, and about $42 billion per year are currently spent by Medicare on this exact population.
The population is large, and the opportunity is substantial to make changes that will improve outcomes. On this basis, this test has been designated a breakthrough device designation by the U.S. Food and Drug Administration. It's clearly signifying unmet need. A little bit about the validation that helps us to really identify these patients. It's a combination of clinical variables that are derived from the electronic medical record. These variables are derived prior to sample collection, so pre-time zero. In our validation study, we used banked plasma for assessing the key biomarkers of interest, and the bank samples were derived from UPenn as well as Mount Sinai Hospital. The biomarker and EMR data are combined based on AI algorithms to generate an AI-KD test score.
Based on that score, we followed patients for a minimum of two years from baseline, from sample collection, to assess outcomes based on composite kidney endpoints with a minimum of three measurements. An event, a composite kidney event was defined as rapid kidney function decline with an eGFR slope of five mils per minute per year, sustained 40% decline in eGFR or progression to dialysis or transplant. When we look at the event rate based on our composite events based on AI-KD risk score across the bottom, you can see there's a progression from low scores representing low risk, a high degree of concordance, if you will, mid scores representing intermediate risk, at the top, we have the highest risk population. This is further validated by the KDIGO risk strata.
We've compared the event rates based on the composite kidney outcome, using the KDIGO definition versus our definition based on the AI-KD stratification. There's a statistically significant difference in our ability to identify these cases at high risk in particular. 62% of patients at high risk or who actually had an event that met our composite outcome endpoint, we identified 62% of them with the test, compared to 41% who would've been identified based on the KDIGO criteria. This is important because of course, there are recommendations from KDIGO on how to manage these patients based on their risk. High-risk patients with greater than 60% risk of rapid kidney function decline, they should be considered for intensive therapy earlier, and they should be referred to nephrologists and get aggressive medical management.
Intermediate-risk patients, according to KDIGO, are sufficiently treated with risk of progression at the population level at about 20%, being managed by a PCP or endocrinologist with monitoring two to three times per year. Low-risk patients basically are monitored on at least a once-a-year basis. The goal of our study was to develop a five-year payer budget impact model to assess the potential cost impact associated with the use of the artificial intelligence kidney diagnostic. Our specific objectives were first to identify the incremental cost to payers associated with the implementation of the AI-KD compared to standard of care. We wanted to define and measure the incremental benefit associated with the use of AI-KD compared to standard of care and monetize that benefit, and then calculate the cost savings. In our study, we used a cohort of 100,000 patients tested.
They were type 2 diabetes and DKD stages 1 to 3b, excluding G1A1 and G2A1. We modeled them for up to five years, and then we evaluated the savings potential based on three distinct categories of types of savings. The first was slowed progressions for the DKD stages. The second is the delayed or prevented dialysis and transplant, or third, based on a reduction in dialysis crashes. A little bit more on our methods. Identifying the target patient population and their movement through the DKD stages. We used a distribution of 100,000 patients according to stage of disease based on a recent publication from Wang, with about 28% of the patients in stage 1, excluding A1, about 25% in stage 2, excluding A1, and then stage 3a was about 31%, and then stage 3b was close to 16%. The sum here is 100,000.
We started with 100,000 patients with this baseline times zero distribution, and then what we did is we projected their progression through each stage of disease through each year. The rates of progression, so cumulative progression rates here in the lower right of this slide, these are based on actual data from our validation study in the control group. We know the rate that these patients actually progressed from each stage by year, and we applied that to the standard of care group. For progression, we actually used three different definitions that we were able to evaluate in our sensitivity analysis. We had a least stringent definition where there was greater than one eGFR value in the next stage.
The stringent or the middle, which we used as our base case analysis, greater than or equal to two eGFR values three months apart in the next stage of kidney disease progression. The most stringent definition was greater than or equal to two eGFR values three months apart in the next stage, only in the 21% of the patients who actually experienced a rapid kidney function decline. We tried to use these three definitions in order to do a variety of sensitivity analyses. Basically each group of patients moved through this cohort based on these projected rates of progression for the standard of care.
For the AI-KD group, the model assumes that the patients will benefit based on the use of the AI-KD through a 20% slowed progression rate through the DKD stages by using the AI-KD and implementing more aggressive management earlier in the stages of disease. We did a sensitivity analysis to evaluate the rates of slowing of progression between 5% and 35%, with 20% being our base case analysis. Of the 100,000 patients tested, 16% were assumed to have a high-risk test result. That was based actually on the validation study that I had presented previously. On the right-hand side, you could see The rates of progression based on the use of the AI-KD, these numbers are roughly 20% lower, this is for the base case, than they were on the prior slide based on the validation set.
Since it's a five-year model, we discounted costs by 3% per year. We also looked at the proportion insured by Medicare versus commercial payers. We did a 60/40 split Medicare versus commercial and assigned standardized costs based on Medicare and commercial payment rates. We also have an assumption of 100% adherence to the preventive measures that were recommended by the use of the AI-KD test. I'll get to that shortly. To assign costs, in essence, we derived costs from the literature based on stages of disease. These are well referenced cost estimates that we're using. We believe they're unbiased, and it's basically cost by stage of, its annual cost by stage of disease. Again, it's from a variety of published references.
As you can see, as the stages of kidney disease become more severe, as you would expect, the annual cost of treating those patients increases. This would be the base case cost in the standard of care treatment arm. What we did is we actually added in some additional cost for the AI-KD group, because by earlier recognition, we're actually starting intensive management that usually involves pharmacotherapy and other more frequent visits and other health services. We estimated the incremental cost of earlier intervention by stage of disease. This was based on published literature sources for guidelines for what appropriate management would be. We based our cost on Medicare estimates, and then for the commercial, we actually used an adjustment that's well-recognized within the literature.
The cost of preventive measures were added only for the AI-KD treatment group or assessment group. The cost of dialysis, transplants, and CRRTs over here were based on published literature estimates. In addition, we added for the AI-KD group, the actual cost of doing the testing. We assumed a $950 test cost, which is actually the Medicare allowable for that test, plus a $100 administration cost in terms of incorporating that into the health plan. Based on that set of methods, I'd like to summarize for you our results from our analysis. The net present value of five-year payer savings associated with adopting the AI-KD is estimated to be about $1.15 billion for 100,000 patients tested in our base case analysis. That's reflected by this dotted line right here in the middle.
You could see we're using on the x-axis, the 20% estimated rate of reduction in decline of progression for the base case. Then this is actually in the stringent group. You could see that on the top line, which is the least stringent, so the more rapid progressing group, there would be more opportunities to intervene earlier. The projected savings were higher for the least stringent definition of progression and lower for the more stringent definition of progression. We also varied it across from 5% impact on reduction in the rate of decline all the way up to 35%, as I mentioned. As you would expect, if we by reducing the rate of decline less, the expected savings are less as well.
In all the scenarios we tested here, introduction of the AI-KD in that patient risk group based on the KDIGO categories, resulted in five-year cost savings net present value for the implementation of the AI-KD. In this next slide, I just wanted to share the estimated time to break even by introducing the AI-KD test. If you look at the graph on the right, the red line reflects the actual cumulative cost of using the AI-KD. From time zero to time one, we're actually upfront, we're incurring costs for testing, and we're actually starting to implement some of these interventions. The first year, actually, the cost exceeds the savings generated by the interventions slightly. In our base case analysis, the break even showed that it was about one and a half years based on the 20% rate of slowed progression.
Obviously, a much more rapid rate of slowed progression would result in a more rapid break even or return on investment, if you will. If we use the assumption of the slowest or the lowest reduction in the rate of progression to 5%, the break even on that is somewhere short, a little over three years. Again, in all three scenarios, we're showing that the cumulative savings continue to accrue over the five-year period. Next, I just wanted to show by year where the savings accrue. If you, again, on the graph, the lighter bar is the most stringent, the medium colored bar is the stringent or the base case definition, and the dark bar is the least stringent definition. The costs are reflected by the line.
As you could see, again, during year one, this is the annual undiscounted savings from implementation of the AI-KD test. You can see that the costs exceed the savings in year one, but then rapidly in year two for our base case analysis, all three scenarios show that they're actually generating more savings than the actual intervention cost. The savings for the five years are expected to be $530 million for the most stringent definition, $703 million for the least stringent definition, and $635 million in the base case by the fifth year. The highest net savings, about $645 million for the base case, are associated or attributed to slowed rate of progression. That's this part over here.
This graph shows that the greatest contribution to the overall savings is slowing the rate of progression and keeping patients longer in those earlier stages of disease that are considered to be less costly, where the interventions can keep them in those less costly disease states for a longer period of time. In addition, there's substantial contribution of savings associated with delayed or prevented dialysis and transplantation. In addition, there's still significant savings associated with the reduction in dialysis crashes, which can be costly, unplanned medical events. The range of the net present value of the five-year savings from slowed progression ranges between $403 million in the most stringent definition to $755 million in the least stringent definition. Based on our analyses, we believe that the AI-KD implementation is expected to achieve significant cost savings for payers.
The primary driver of this is the delayed progression of beneficiaries with DKD, and keeping them in the earlier, more manageable stages of DKD for a longer period of time. Through early and accurate risk stratification, patients with DKD are likely to experience rapid kidney function decline with the higher-risk patients. The use of the AI-KD has the ability to generate significant cost savings through improved management at these earlier stages. It would also support primary care physicians and endocrinologists in identifying appropriate patients for whom monitoring can be continued by them in the low-risk categories, and where other interventions and perhaps more timely referral to nephrologists or specialists should be considered in those intermediate and certainly in the high-risk patients.
The use of the overall implementation through the EMR and the artificial intelligence algorithms helps us to really improve all the care of these CKD patients, DKD patients. Last, improving healthcare systems' ability to provide the care conforming to the K/DOQI guidelines at earlier stages should help to reduce the rate of progression from diabetic kidney disease to ESRD, and that would have a substantial clinical and economic impact on the healthcare system. With that, I'd be happy to turn it back over to Dr. Vassalotti for management of attendees' questions. Thank you very much.
Great. Thank you all for your attention. We're going to open up to questions, and we will ask questions of all three speakers. Dr. Gibson, AURORA phase III voclosporin superiority over standard care in lupus nephritis. Dr. Awad, who presented the difelikefalin in phase II study and stage III to V CKD for moderate to severe pruritus randomized controlled trial. Of course, we just heard from Dr. Goss and the evaluation of a payer budget impact associated with the use of artificial intelligence and in vitro kidney diagnostic to modify diabetic kidney disease progression.
I will begin with a question for Dr. Gibson on the AURORA trial. Could you comment on other therapies for lupus in addition to the mycophenolate and the steroids and the randomization of voclosporin versus placebo vis-à-vis hydroxychloroquine, which has gotten a lot of attention recently with our COVID-19 pandemic? Any comments on how that might have played a role or the interaction in your study results?
I think that's a great question. The prevalence of hydroxychloroquine is something that we will likely look at in follow-up analyses. The data that I presented now are part of our initial core data, and I think it's a very interesting question. It's certainly at the forefront of everyone's mind. There are some good observational studies out there that have looked at the role of hydroxychloroquine, and certainly, there is some thought that it may confer some protection for individuals that have kidney disease, but it is not something that has been studied in a rigorous randomized controlled trial, so it's important to keep that in mind. At the most, we might be able to look at sort of historical use within our trial, but that would be something that would be forthcoming.
Thank you. We have a question for Dr. Awad about the opiate epidemic that we unfortunately are experiencing in the United States, and this is a kappa opioid receptor blocker. Were there any implications there?
Any implication. We're hoping that since this does not cross the blood-brain barrier, and it does not bind to the mu-opioid receptors, that there is no dependency or addiction with this medication. We are currently conducting a trial on dependency and withdrawal. In the two publications that we have, one in The New England Journal of Medicine and this publication, we did not see any dependency or withdrawal symptoms or addiction.
Okay. Thank you. A question for Dr. Goss about the artificial intelligence and the in vitro diagnostic. In terms of your intervention in this simulation model that you used, did you consider any specific drug therapies for type 2 diabetes? For example, SGLT2 inhibitors, which have gotten a lot of attention and excitement in nephrology circles lately.
That's a great question, Dr. Vassalotti. Yes, we did. In fact, some of the recommendations that would be included in more aggressive management would be to introduce the SGLT2 or GLP-1s in the earlier stages of disease, as well as, of course, making sure that there's appropriate management with ACE inhibitors or ARBs for blood pressure control. Again, yes, we did include the inclusion of those treatment regimens earlier, and that's actually part of the incremental cost that we showed with the additional treatment with the AI-KD.
Thank you. A question for Dr. Gibson. Do you have data on adjustment of antihypertensives, particularly ACE inhibitors and angiotensin receptor blockers, and the impact, I guess, they might have on proteinuria and, of course, changes in potassium during the trial?
Yeah, absolutely. Again, these are data that are going to be presented later on. Within this trial, there was pretty strict attention to blood pressure and a pretty rigorous blood pressure protocol, if you will. These were things that were looked at very closely, and as you saw the data that I presented, overall there was fairly good blood pressure control in all the participants across the 52 weeks. I think that's going to be additional interesting information that will come out in forthcoming analyses. The adjustments were allowed, for sure, especially in ACE inhibitors, and tightly controlled. Again, data that will be coming out later.
Okay, great. A question for.
I'm sorry. I misspoke. Were not permitted. I think I said were permitted.
Okay. Okay. Excuse the sound there. I'll have to work on that in a second. The next question is for Dr. Awad. With respect to hyperphosphatemia, you didn't present phosphorus data, so that was the comment. Hyperphosphatemia potentially driving pruritus, particularly in patients with advanced kidney disease, and also potentially even low iron stores. Just something to consider as you move forward with your analysis. A comment about are you concerned about hyperphosphatemia-induced pruritus being treated by this medication and affecting compliance of patients' use of phosphate binders? Of course, that would be for more advanced DKD.
Good question. In this study, the phase II clinical trial, we did not measure the phosphorus, but I think it was measured in patients on the previous phase III IV DFK. However, we have to go back and readdress the issue of the pathogenesis of pruritus, even in patients on dialysis. Is it really the hyperphosphatemia that caused the pruritus? Is it really the uremia that's causing the pruritus, or is it just the inflammation in general that caused the pruritus? In my opinion, to label a patient that they have pruritus because of hyperphosphatemia is difficult to do until we understand more about the pathogenesis of pruritus.
Thank you. For Dr. Goss, it's interesting that your model is updated with artificial intelligence. Can you comment in general terms on how that works so we can understand the process better overall?
I would have to say that is not an area where I did the validation. I could certainly take the question and get you in touch with the folks who developed it. In essence, the intervention works through use of the artificial intelligence to combine some clinical data in the EMR, as well as the laboratory analytes, right? The in vitro component, in order to better predict this risk. It's also important to recognize that its implementation, because it's using the EHR data, it's also able to be transmitted back to the physician very timely with specific individualized patient recommendations. In terms of the AI component, that's also regulated by, I believe, FDA. There will be, I think, some element of that in the final approved labeling in terms of how the AI component works.
Thank you. Thank you very much. For Dr. Gibson, regarding the study of cyclosporine and lupus nephritis, we know that calcineurin inhibitors attenuate proteinuria through immune and non-immune mechanisms. Can you consider the role of cyclosporine in other glomerular diseases, or can you give us a sense of where you think that's going in terms of minimal change disease or focal segmental glomerulosclerosis or potentially others?
Absolutely. I think that there is potentially a pretty exciting, huge role for this particular drug across the board of glomerular diseases, especially any of those that are associated with podocyte, podocytopathy, if you will. In diseases like FSGS in particular, where you can directly target podocyte stabilization, I think there may be a huge role for this drug. In fact, there is an ongoing phase II open label study specifically looking at this for FSGS. I really think that as we are sort of moving forward in this era of personalized and precision medicine and really trying to follow the lead of our oncology colleagues, and trying to find specific targets, I think understanding the mechanism of this novel calcineurin inhibitor really lends itself to us figuring out other disease entities where it may be efficacious.
Thank you. I have a question for Dr. Awad about concomitant medication use in the trial. Use of gabapentin, for example, which may be used for neuropathy and may also have implications in efficacy for pruritus, or particularly uremic pruritus.
Yes. In this study, the phase II clinical trial, there were concomitant medication, including pregabalin, gabapentin. Some of the patients were on steroids. As long as they were stable for the last 14 days prior to screening, we enrolled them in the trial, and we did not see any drug-drug interaction, if that was the question. There were concomitant medication, including gabapentin, topical corticosteroid, pregabalin, and some of the patients were using emollients and protectants. As long as they were not new, and they were stable for the last 14 days prior to screening, we enrolled them in the trial.
Okay. There's another question that's kind of related about drug interactions. Can you speak about potential drug interactions in this patient population and perhaps even in the hemodialysis or the dialysis-treated population as well?
For the dialysis patients, we all know when we give them gabapentin and the myoclonic jerking and what have you. There was a question I saw about longer dialysis versus shorter dialysis and the incidence of pruritus. I am not aware, and correct me if I'm wrong, of any studies looked at pruritus in nocturnal dialysis versus the intermittent three versus daytime dialysis, three and a half, four hours dialysis. I am not aware if there was a study looking at pruritus between these two groups. Drug-drug interaction, thus far, we did not see any drug-drug interaction between DFK and gabapentin or pregabalin.
Thank you. I would speculate that we will see less pruritus in patients who were treated with long nocturnal dialysis, but I don't know the data or I can't cite a particular paper, but that's just my speculation. I'm going to continue for Dr. Goss. In terms of using this data, you know you have simulation model data. What's your next step? What is your next plan in terms of your analysis and your work?
Thank you for that question. We are actively working with several integrated delivery networks and payers to actually do additional studies using payer-specific data, and then monitoring that using forward-looking outcomes assessment. That's currently planned and underway.
Thank you. We have a question for Dr. Gibson about, I guess this is really asking about hematuria, cast sediment were not assessed in the study. How can we certain that the study drug is treating nephropathy and not really reducing proteinuria through extraneous mechanisms or, I guess, hemodynamic mechanisms?
Right. No, I think it's a great question. I think the question of how do we look at active urine sediment, meaning hematuria, cellular casts, how does that fit into the equation of looking at drug efficacy and long-term outcomes? What I would say is that there are zero studies that truly correlate resolution of an active sediment on the basis of hematuria and cellular casts in the absence of looking at proteinuria as a correlate of good long-term outcome. There are several studies that correlate long-term outcome with reduction in proteinuria. For this reason, and in thinking about the mechanism of drugs, it made sense to really focus on the proteinuria. To the second part of the question, if we're just looking at proteinuria and not hematuria, how do we know that this is not all related to hemodynamic changes?
I think one of the strongest arguments against that was really in the phase II or AURA-LV trial. Treatment was withdrawn from patients at 48 weeks, and then two weeks later, they came back for measurement of GFR and proteinuria. What we found was that even though there was a return of GFR back to baseline, there was no change in proteinuria. The benefit or the improved proteinuria effect remained even with withdrawal of the study drug. I think that those things sort of help eliminate some of the concern related to hemodynamic changes and proteinuria change.
Thank you for that response. We're having excellent interchange here, so I thank our speakers. I do want to point out that we have a slide that is being displayed now, which shows you the poster number. Please visit the posters, and the presenters have kindly provided their email addresses for interaction, and further thought, and interchange. I want to thank the presenters for that. Turning to Dr. Awad, the presentation on your phase III trial in CKD 3 to 5 is really an oral formulation. We believe The New England Journal of Medicine paper that you referenced was an intravenous formulation of the medication. Can you tell us about the availability of either of these formulations and the current status they're in?
It depends on many factors, one of which is coronavirus now. What I understand, probably mid to late 2021.
That's for both formulations and both indications?
I think the IV first, because the phase III clinical trial already been conducted and published, but I'm not sure about the oral yet. This is a phase II clinical trial.
Okay, great. Then I want to ask Dr. Goss a question about nephrologists approaching their business leaders and their administrative leaders in their hospital systems or their practices or large practices. Was there any advice you could give them? One of the challenges we have is the ROI for interventions of chronic kidney disease, and you have a nice example there that you've presented today. Any advice you would give a nephrologist that wants to lead and wants to direct population health in their local community?
Sure. Well, thank you for that question. It's an excellent question. Certainly, we'd be happy to speak with them and tell them a little bit about how this. It's about more than the test. It's a solution. The test is a key component to better information, better clinical decision-making, and therefore better and earlier intervention with patients who will benefit. The economics are a key piece of course, and can often be used to get people interested to learn more and to think about how it could be implemented. On behalf of the sponsor, I can tell you that it is being developed and implemented as a solution, not just a test and a test result that goes back to sit in an inbox somewhere. Demand is high for changing what's happening with these patients because the unmet need is so high.
There is opportunity for collaboration to be able to improve outcomes in this particular area.
Thank you. A question for Dr. Gibson on AURORA. You alluded to a two-year follow-up study. Are you able to elaborate on patient enrollment and how the preliminary feedback on how that's going?
Yeah. I think we've been pleased with sort of the enthusiasm of the study participants from AURORA rolling over into this extension trial. Right now, over 200 of those patients have rolled over. We're all really excited to see the opportunity to provide the follow-up, long-term follow-up, not only for efficacy but also safety parameters.
I'll just give a follow-up to that is regarding the dose adjustments that were performed in the trial. How can that be translated into real-world practice, real-world management?
Yeah, absolutely. I think that one of the barriers to patients that are exposed to calcineurin inhibitors are GFR changes, especially since I'm sorry, I just lost my train of thought. Can you repeat the question? Dr. Vassalotti?
I unmuted myself. It's about the dose adjustments of voclosporin that were-
Yes.
conducted in the trials.
How that would relate to real life. Concerns with GFR changes. Certainly, if you have people that are maybe on the lower end of what would be considered an allowable GFR, this allows for a little bit of personalization of what we're doing. Balancing efficacy and safety. Again, the data that I presented showed that even in those patients that were unable to be titrated back up to a target dose, we still saw a conferred benefit in voclosporin exposure as it relates to proteinuria reduction.
Thank you. A question for Dr. Awad about there seemed to be some dose effect with falls and with dizziness, although you pointed out that those were not in the same population of the same patients. Could you comment on blood pressure readings associated with those adverse events?
I'm going back to the slide to look at the blood pressure readings. Across the board, we did not see any difference in the blood pressure except in the low dose of 0.2. There was no dose escalation in the hypertension. It was one in the 1 mg and one patient in the placebo. I have to go back and look at how high it was. It was not a statistically significant difference between placebo and the active drug.
Okay. That's the overall trial data. I think the question is about those specific adverse events, but that could be something for further analysis.
Yeah. It's a small sample. We need a larger sample to look at these different adverse events. As I mentioned earlier, the fall and the dizziness were not related to each other. Those who fell were not dizzy, and those who were dizzy did not fall.
Okay, great. I want to thank you for your attention. I want to remind you that if you have colleagues that are interested in our presentation late-breaking session today, that this will be recorded and available through April 29th. I want to encourage you to review the abstract. We have the AURORA is abstract 407. That's the phase III trial of voclosporin. That was nicely presented by Keisha Gibson. We have the efficacy and safety of oral difelikefalin in CKD 3 to 5 with moderate to severe pruritus, and that's the randomized controlled phase II trial.
That's abstract 409. Abstract 479 is the evaluation of a payer budget impact associated with the use of artificial intelligence in vitro diagnostic, and that's KidneyIntelX to modify diabetic kidney disease progression. I want to thank you for your attention. This has been an engaging session, and I want to thank our presenters today.
Thank you.
Be safe and-