Good morning, everybody. Thank you for joining this Cogstate investor presentation. We're really pleased to have you in attendance. My name is Brad O'Connor. I'm the Chief Executive of Cogstate. I really want to welcome you to this presentation, which is the first time we've done something like this. I think it's a great opportunity for our investors to see the broader executive team at Cogstate. We've got an excellent team, and I think you'll be pleased to, you know, get an opportunity just to get to know them and understand their expertise in the industry. We also wanted out of this presentation to give you the opportunity to understand Cogstate's clinical trials business a little better.
I think people have a really good understanding of Cogstate's digital assessments and the role that they play in clinical trials and in the healthcare setting. But I think sometimes we don't do as good a job of explaining the broader services that we offer to our pharmaceutical company customers. So one of the things we want to do today was to give you the opportunity to really understand that. Our clinical trials business represents over 90% of our revenue at Cogstate presently. So it's the major part of our business. And in that business, we act as true advisors and partners with large pharmaceutical companies as they're running global clinical trials and central nervous system diseases. So wanted to give you an opportunity to understand that a little bit better.
We will take questions at the end of today's presentation. If you have questions, there's two ways you can ask that. You can raise your hand and have your line unmuted, and we'll take a, an audio question, or you can simply send in a question via text, and it'll be read out by our moderator. Again, we welcome your questions, but we'll do that at the end of today's presentation. I'd like to introduce our presenters today. We have Chris Edgar, who's the Chief Science Officer at Cogstate. We have Pam Ventola, who's a VP of Science and predominantly works in our rare disease area. We have Rachel Colite, who's recently, recently taken on the role of Executive Vice President of Clinical Trials. I'll let those folks introduce themselves, and then we'll get into the presentation.
Thank you, Brad. Welcome, everyone, from me. My name is Chris Edgar, and as Brad said, I'm the Chief Science Officer with Cogstate. I've been with the company for about five and a half years now. My academic background is primarily in cognitive psychopharmacology, but I've been working in drug development for around 23 years. Formerly, I was with the Swiss pharmaceutical company, Roche, where I was a principal scientist working across their neuroscience portfolio. And my role at Cogstate is to oversee the science function activities across the various elements of the business, the clinical trials, academic research, and healthcare components.
Hi, everyone. I'm Pam Ventola. I'm a pediatric clinical neuropsychologist by training. I've been consulting with Cogstate for about 12 years, and I joined full-time about five years ago. Prior to that, I was an associate professor at Yale University at the Child Study Center, and I retain a dual appointment between Yale and Cogstate, even now. My role at Cogstate, as Brad alluded to, I direct all of our pediatrics and rare disease work, and I also oversee all of our science related to rater training.
Great! Hello, and welcome. My name is Rachel Colite. I'm the Executive Vice President of Clinical Trials at Cogstate. I've been with the company about eight years now, working in leadership roles in various functions, including our decentralized solutions, and currently, I lead our clinical trials organization across commercial and operations. Prior to joining Cogstate, I spent about seven years at ICON plc, a global contract research organization, where I worked primarily in corporate marketing functions across early-phase laboratories and late-phase development groups.
Thanks, guys. So we're going to start today with we'll dig into the Alzheimer's disease clinical trials landscape, and Chris will take us through that. We'll then touch on the opportunities that we see in rare disease. And then we'll bring that all together by talking about the capabilities that Cogstate offers to our pharmaceutical company customers. So, Chris, we'll hand over to you to talk us through the Alzheimer's clinical trials landscape.
Thanks, Brad. So in this part of the presentation, then, the intent is to give an overview of recent developments in the field of Alzheimer's disease clinical trials, emerging trends that address the recent approvals that we've seen, and our developing understanding of the pre-dementia stages of disease, particularly what we term preclinical Alzheimer's disease, and what are the remaining unmet medical needs in the area. And then from a Cogstate perspective, how our decentralized trials approaches, and also how our digital cognitive assessments, can really help to address some of the challenges that we'll see, for the current and future clinical trials that we expect in this space.
So as many of you will be aware, the 1990s and early 2000s saw a series of approvals related to the symptomatic treatment of Alzheimer's disease, and these treatments, the cholinesterase inhibitors and memantine, resulted in some symptomatic relief for patients, improvement in cognitive symptoms of the disease, and some improvements in activities of daily living. But they weren't seen to modify the underlying cause of the disease, so not what we would term disease-modifying treatments. And in parallel to this, there was clearly much work left to do, and a series of clinical trials were run at the mild cognitive impairment stage of disease with the symptomatic agents, and also a number of other mechanisms were explored, but none of these were really successful, and no approvals were seen then over the subsequent two decades of research.
At the same time, substantial effort was undertaken to explore the amyloid hypothesis, which is that amyloid protein is a causal factor in the clinical symptoms of Alzheimer's disease. Whilst over that period, there are a number of negative trials leading to, you know, periods of wavering confidence in that hypothesis, what we now see is that many of those trials fit into a very clear picture now, where lowering of amyloid in the brain is clearly associated with clinical benefit, and a certain threshold of lowering needs to be achieved in order to see that clinical benefit. Aduhelm and Leqembi clearly fit into that pattern.
These treatments are, you know, they're an enormous step forward in providing for us the first approvals of disease-modifying treatments, really proven to slow progression of the disease, and at the same time, establishing a clear regulatory approval pathway. Naturally, though, with these approvals has come debate. The efficacy of the treatments has been challenged to some extent. There's clearly further work to do in order to further increase the level of, of effectiveness of treatment. Then, too, really understanding what are the important thresholds for meaningful change and difference is an important component, and this will help both to understand the benefit to patients, but also to differentiate between treatments in terms of their efficacy and effectiveness, and also to help payer groups to understand value and pricing of treatments.
There are two additional concerns around aspects of safety, dosing, and access to treatment that remain to be resolved. We know that there's this area of amyloid-related imaging abnormalities, which are a potential safety concern in reflecting microbleeds in the brain. This is clearly an area of concern, although very few cases are seen to be symptomatic and even fewer result in serious adverse events. Clearly, a safety concern that drug developers are keen to address. On the next slide, we'll switch gears a little bit to touch on this concept of preclinical Alzheimer's disease, and it's worth noting first, the slightly confusing terminology here.
So we're not talking about preclinical studies that may occur prior to human trials, but rather a very early stage of Alzheimer's disease that's prior to the emergence of clinical signs and symptoms, and it's a stage of Alzheimer's disease that can be defined by biomarkers. So the National Institute on Aging and Alzheimer's and the Alzheimer's Association research framework in 2018 really helped to further define early Alzheimer's disease by the underlying pathological process, and not solely on the clinical consequences of diseases as we used to in the past. And this framework focuses on the diagnosis of Alzheimer's disease, primarily with biomarkers of amyloid, tau, and neurodegeneration, and that's the so-called ATN framework. So the three different pathologic processes occurring in the brain and used to define these stages of Alzheimer's disease.
Aligning with FDA then, these frameworks provide us with a clear understanding of how to define preclinical AD, and also to some extent, mild cognitive impairment and early Alzheimer's disease. They really are a driver for helping us to recruit the right kinds of patients into trials and really helping us to design robust studies that the regulators will be comfortable with as demonstrating a well-defined disease process. Switching back then to the research area itself, clearly, as we were outlining, there are substantial areas of unmet medical need that drug developers will seek to address around efficacy, safety, and access to treatment. The approved amyloid treatments now provide a foundation for combination therapy, and that's a really exciting potential area in the field of Alzheimer's disease.
That we now have this foundation on which we can add additional treatments, potentially with different and novel mechanisms of action that may address further aspects of the disease. You know, we know that the approved treatments may only slow progression by 20 or 30%, so there's another 70%-80%'s worth of improvement that additional mechanisms of action that combination therapies might be able to achieve in fully arresting the progress of disease. Now, this could include things like targeting different species of amyloid, such as the Acumen lead asset, which is believed to preferentially target oligomers over fibrils. Or it can be non-amyloid mechanisms, things like tau propagation, neuroinflammation, or synaptic plasticity. And we see that these targets are being addressed both with small molecules and biologics.
If we then think about route of administration and dosing regimens, this will also be an important area to address. You know, seeking to find treatments which may have subcutaneous or oral routes of administration will aid convenience for patients, and of course, fewer infusions would also be an advantage for patients. We touched upon the ARIA, the amyloid-related imaging abnormalities. There are certainly improvements to safety that can happen, and overall, healthcare system preparedness presents us with a series of challenges to access. We want to improve availability. We want to lower the cost and invasiveness of the approaches to diagnosis.
So shifting away from lumbar puncture and the measurement of cerebrospinal fluid, shifting away from imaging techniques and the use of PET scans, and towards blood-based biomarkers will aid in cost and convenience and efficiency of trial conduct and identification of patients. So it's perhaps unsurprising then that this is an active research area. There's an annual report produced by Jeff Cummings and colleagues that looks at the Alzheimer's disease trial pipeline. It's a rich area for understanding what's happening, but we see that there are over 180 active trials as of January of this year, and something like 141 agents being investigated. So this pipeline review is really helping us understand that it's an active research area.
If we think about the number of disease-modifying therapies that are being explored, something like 79% of that active pipeline is in disease-modifying therapies, small molecules, and biologics that aim to change the disease course. Around eight of these are in this preclinical AD stage, so four phase II trials, four phase III trials are enrolling preclinical AD patients. There are substantial advantages to drug developers in trying to treat these patients. It's a larger population, a bigger market for the drug, and of course, there's a potential substantial benefit to patients in being treated earlier.
In trying to prevent progression at the very earliest stages of disease, the benefit to patients and families, of course, is that you maintain function at a much higher level at the point at which people are not really yet experiencing prominent symptoms of the disease. Of course, though, these trials do face major challenges. They're much longer in duration. Patients may be on treatment in a preclinical AD trial for, you know, somewhere between four-five years, perhaps, rather than the 18-24 months that we might see for an early Alzheimer's disease clinical trial. The studies require larger sample sizes. They have higher screen failure rates, so recruitment and retention are major challenges. And as a consequence of all of these things, the idea of phase II proof of concept trials is somewhat more challenging for drug developers.
Now, we won't tend to see drug developers address the preclinical AD population as their first series of studies with a new drug, but rather, they may seek to generate evidence first in later stages of the disease before they move into the preclinical population because they can generate that evidence more quickly with smaller, shorter trials. So how might we start to then address some of those challenges? Well, the first area which Cogstate, in particular, are well-positioned to address is the use of decentralized clinical trial approaches. So these can include remote assessment and various solutions from home visits through to self-administered and bring your own device or passive assessment approaches. The potential here is really to lower burden.
It's lower burden for patients, lower burden for caregivers and family members, too, and we should remember that for most of these Alzheimer's disease trials, many of the assessments that are conducted are dependent on an informed caregiver or family member to provide information about how the patient is doing. So really, we're enrolling two people into the clinical trial. And one of those, the healthy family member or caregiver, may well have many other commitments on their time. You know, certainly in the preclinical AD population, these people are gonna be somewhat younger than we see in AD dementia trials. They may be working or have volunteering commitments. So, you know, really supporting them over a very long period is a difficult thing to do.
As we touched on, recruitment and retention then becomes really important, so we have to seek ways to lower the burden for these participants in the trial. By supporting some of that assessment at home, we can substantially lower burden. People are not having to come into the clinic to do quite lengthy assessments where, you know, interviews might last for, you know, 30-60 minutes, perhaps, or cognitive test batteries might last for a similar period of time. Many of these things can be conducted in the home. And digital health technologies, too, provide us with opportunities to conduct this kind of remote and at-home assessment. And this then provides us with overall far greater flexibility in study design and conduct, these opportunities to lower burden and support recruitment and retention.
We may be able to use pools of central raters, where we can conduct traditional assessments via telehealth approaches to further support those remote assessments. On the next slide, we'll look at the idea of digital health technologies, which include computerized cognitive assessment. It's clear that these are likely to play a really critical role in the early detection of Alzheimer's disease and in its diagnosis, its prognosis, and therapeutic decision-making. Really, a role for these assessments to play across the journey for patients from early screening through diagnosis and to later treatment and monitoring of that treatment.
These technologies, too, have the potential to create awareness around brain health in the community, and that may, in part, drive important lifestyle changes, but also change behavior around awareness and willingness to participate in clinical trials. There are two elements then that are important to this. The idea that we can leverage these technologies to help with the substantial challenge that may be faced around recruitment.
If as the Cummings report suggests, we need something in the order of 58,000 patients to support the number of clinical trials that are planned, then that might result in screening of, you know, 500,000-600,000 participants, and being able to find those individuals in the community is going to be very difficult, and raising awareness, it will be an important element of that, and digital technologies have a role to play there. Additionally, for the approved treatments, it's going to be important to try and identify patients earlier in the disease course. These treatments are approved for people with mild cognitive impairment, and currently in clinical practice, processes and tools are not well designed to identify those people.
And there's a potential challenge then for real-world evidence if there's a bias, a skew towards treating patients who are later in the disease. It may be that those treatments fail to demonstrate as great a degree of effectiveness as we might expect, or even they may—it may show additional safety concerns. So certainly an important role for digital technologies and for blood-based biomarkers to play in early detection of disease as well. But in summary for this section, we see then that recent approvals have the potential to act as a catalyst for research in this area. But at the same time, there's still a substantial unmet medical need to be addressed.
So we think that there's likely to be, you know, continued effort in this area, and large numbers of trials seeking to address both a greater understanding of how to increase efficacy and effectiveness, as well as safety, but also to address these access challenges, to ensure that more patients get onto treatment. A real opportunity to use decentralized trial approaches and digital technologies in order to address some of these key challenges and barriers that these trials may face.
Chris, that's excellent. I think a really great summary of what's, you know, what's been happening and, you know, what's a really exciting space at the moment. I want to dig into a couple of things before we move on to Pam. The first is, you mentioned, you know, the challenges around recruitment of over 58,000 patients at the moment. You know, I think, you know, our belief certainly is it's fair to say that those recruitment challenges are only going to get harder in the future when we're looking at certainly the exploration of new drugs and other pharma companies coming into this space, as well as the competition that that recruitment is going to have with respect to the drugs that are on market.
I thought that the investors would like to hear from us, you know, some of the activities we've been doing as pharma companies seek to, you know, sort of address that challenge and think a little bit differently about how do they find patients for their, for their clinical trials.
Yeah, thank you, Brad, and it, it's worth, you know, highlighting that, that just last month, we conducted a large-scale screening pilot, on older adult residents in the U.S. using our digital cognitive assessment tools and, also a blood-based biomarker, which was on behalf of a pharmaceutical company seeking to, you know, find out how they can more rapidly identify more of these patients for enrollment into clinical trials. And that pilot's enabled us to demonstrate the potential to screen several hundred patients over the course of just a few days, and this is really important, for us in, really showing the potential of these tools to expand the way that we access and screen for trial participants.
But I think importantly, too, the willingness of potential participants to undertake digital cognitive assessment and to have a blood test, you know, there's strong interest in the community if you can make the outreach directly to them.
It's fascinating. The other thing that I think is interesting to dig into is we've got this, you know, breakthrough approvals of the monoclonal antibodies, and you showed the Cummings paper with the nice graphic of the different areas where pharma companies are investing their resources at the moment. Do you think that the approval of disease-modifying therapies changes the investment mix in terms of, you know, do we expect to see less investment in symptomatic disease and more investment in disease-modifying treatments?
I think disease modification, you know, it already makes up the majority of the investigational drugs that we see. And I think from a science and public health perspective, it's likely to remain the focus. You know, the holy grail for people will be really to prevent disease progression if they can, and I think that's gonna be a major target and continue to be so. I think, though, you know, as we do now, we'll probably continue to see symptomatic therapy make up some component of that mix, and that may be perhaps more and more targeted in certain areas. You know, we see, for example, that agitation and psychosis is a target for symptomatic therapies, and there are, you know, certain categories of symptom that may be particularly amenable to symptomatic treatment.
Yeah, and you mentioned that there's eight ongoing trials in that pre-symptomatic, preclinical area, those sort of prevention studies, as you call them. Yeah, is that something that you think, you know, will increase in number? Is that an area that more and more companies will push into, that Nirvana of, you know, of disease prevention rather than just improvement?
I think for anyone who generates evidence for disease modification at later stages of the disease, you know, but perhaps not even if they have a successful trial, but even if they show ability to modify the disease, that leads to enough confidence to initiate a trial in preclinical AD, they may well seek to do that. There's certainly an expectation that for a disease-modifying treatment, efficacy will be greater at an earlier stage of the disease. And so, you know, I think really people will be looking at the evidence that they have in front of them and whether that warrants moving further backwards in the disease course.
And it may not require that they have a successful readout at later stage disease or an approval, but rather just the confidence from what they see in their data.
It's fascinating. I think, you know, it's a really exciting time, you know, for Alzheimer's disease patients and their caregivers as we start to see, you know, these therapies come through, and as you suggested at the start, there's still plenty of room for improvement. So we'll keep going with the presentation, and we'll hand over to Pam now to talk about what she's seeing in the rare disease clinical trials landscape.
Great. Thank you, Brad. So I wanted to start by just level setting on what is a rare disease, and it's truly defined by prevalence, you know, exclusively. So a rare disease affects less than one in 2,000 people. That's the definition. We also work in what's called ultra-rare diseases, and they're just more rare. They affect less than 1 in 50,000 people. And at Cogstate, we work in rare central nervous system diseases, and this list is not exhaustive by any means, but I wanted to give you a sense of some examples of what these kinds of rare diseases are. So they're listed here. And the rare disease market is very attractive, and it's driven by multiple factors, largely financial ones.
So in the 1970s, there were only 10 orphan drugs that were approved, but in the mid-1980s, there was a law passed in the U.S. that created financial incentives for pharmaceutical companies to work in rare or orphan disease areas. Because the market's never gonna be as big as it is in other indications where there's more patients. But there's still a very much of an unmet need, so there's incentives to do so that extend beyond just amount of possible patients. And what that led to was just this vast increase in the number of orphan drugs that were worked on and therefore approved. So in this time period, you know, there was 564 drugs approved, and their trajectory is just going up, as illustrated in this figure.
To talk a bit about the financial incentives, you know, it's termed the Orphan Drug Act, and there's four specific financial incentives in this law that encourage pharmaceutical companies to develop orphan drugs. First is they have seven years of exclusivity, so that prevents competitors from selling the same product for seven years. There's also tax credits available, grant funding, and FDA user fees are waived to about the cost of $2.5 million. In addition to these direct financial benefits, there's also accelerated approval for the trials, so they go faster. In the next slide, just wanted to talk about the probability of success. It's another factor as to why the rare disease market is growing as such.... You're more likely to be successful if you're focused on a rare disease, with if your new drug focuses on a rare disease.
So there's about a 7% probability of success across the board. It's about 6%, a little less, if it's a chronic high prevalence disease, and we're about 17% probability of success for new drugs focused on rare diseases. Now talking about this strategy for biotechs. Not all the time, certainly large pharmaceutical companies work in rare disease, but it is a particular focus area for smaller companies, so the biotechs. They're able to be quite successful in rare disease using a couple of different strategies. Some are science, some are just inherent to being a small biotech. So from a strategy perspective, one compound in rare can often target multiple diseases. So you can have one treatment and run multiple parallel trials in multiple indications with that one compound.
Similarly, you can have a trial that's has multiple indications, so multiple diseases in the same trial. So as an example, there's rare seizure disorders. They all have a different name. They're named based on the genetic etiology of the disease. And there's rare disease trials that group together people with all multiple different kinds of rare seizure disorders into a single trial. So it increases your market, and it also increases the speed that you can enroll patients. It has multiple benefits, and it's in a really effective strategy for biotechs. As another strategy, and this one's directly related to the regulators: if in many cases, you can make a case for this, if you have a serious disease with no treatment available, you can have approval with one pivotal trial, so one efficacy trial.
So a lot of our sponsors work in, that we work with in rare disease, combine a phase two and phase three into one trial. They only need to demonstrate efficacy in one trial, so it really speeds up the process. And then, just lastly, kind of an inherent sort of approach with biotechs. They tend to be small, so they're they can work very quickly, very agilely. They're, you know, a small group or if not one, kind of decision-maker involved. So it just allows them to, you know, the approval pathway is fast, and they can be fast. So that's, it just allows for quick success. And I wanted to highlight just one recent success in this area. We had our first approval of a rare genetic neurological disease.
This is huge for the field, and it's really exciting for the families and the patients and the field as a whole. So there's a disease, Rett syndrome. With Rett syndrome, the children, adults, it has a reduced life expectancy to some degree, so you might hear me just say children. But the individuals are very impaired, so they don't walk, they don't talk, and they have no functional use of their hands. So it's an extremely impairing condition, and we just had our first successful approval for this kind of disease, and again, specifically for Rett syndrome, and the drug is trofinetide. Neuren licensed...
Did the initial trials, they then licensed the compound to a different company, Acadia, and that's when Cogstate was brought on board in this, approval pathway and in, and in the, the path of this, treatment. And we authored the paper with Acadia, providing evidence for the clinical meaningfulness of the difference in the change, of how much these individuals got better. So as a scientist, you know, I see a change of 3 points, I get really excited. But the payers say, "So what?" So we need to show evidence that that, quantitative change on our measures is clinically meaningful to families.
That's the work that we supported with Acadia, sort of making the connection between the quantitative improvement on their primary outcome measure and directly connecting that to saying that's a meaningful change, that changes quality of life in a meaningful way for these families that have kids with Rett syndrome.
I just wanted to jump in here and provide a couple of examples with companies that PAMA's worked with recently, just to show, you know, to bring some of this together in terms of, you know, why this is an area that Biotechs focus on and what it means from an investment point of view into Biotechs. The first company that we're showing here is Reata Pharmaceuticals. They have just, a few months ago now, had their first approval in their 21-year history. There's a little bit of a background to this drug, where they had a successful phase-three trial in 2020, and the FDA asked to see more data, and they've just had the first drug approved in their focus indication.
Small patient population, you see there, 5,000 patients diagnosed in the U.S., and expected to be around 22,000 worldwide. List price in the United States is $370,000 annually. You can see the jump in their market cap, in, in the NASDAQ-listed company, in the U.S., in March 2023, on the announcement of the successful phase III trial, and the FDA approval. And then you can see just, a few weeks ago, Biogen announced, a definitive agreement to acquire Reata Pharmaceutical. So obviously, a fantastic results for the shareholders of, of that company. One that's, perhaps a little closer to home and that many investors on this call will be aware of is, is Neuren.
For those that aren't aware, and Pam talked about this before, you can see the jump in their market cap with the approval of their treatment for Rett syndrome that Pam just went through. And then again, only a few weeks ago, the jump in market cap when they further licensed the rights to Acadia for the expanded rights for NNZ-2591. If we look at Acadia and so the acquirer of that asset and see what happened, with you know, in respect to their market cap on approval of the treatment. You can see, with the announcement of the approval, not much movement in their stock price.
Obviously, we're talking about a, you know, company here with about a $3.5 billion U.S. market cap, so a much larger company with much larger revenue. And, you know, when you look at the jump post their quarterlies following their first quarter of sales of that drug, you can see a substantial increase in their market cap at that time. It's important to note here that they gave a much broader update, including an update or an upgrade in Parkinson's disease therapy. But, you know, the...
As you can see there, the first quarter sales was $223 million, you know, more than 10x consensus estimates of the sales for that quarter, and they've estimated, you know, third quarter sales in the order of $45-$55 million. So, once the, you know, the broader market understood the financial impact of that approval, you see the jump in the market cap there.
Great. Thanks, Brad. And I'm gonna circle back now and talk about, you know, with this kind of really strong opportunity, why Cogstate's well-positioned for this market in rare. I mean, we have vast experience. We are currently supporting about 40 trials in rare disease across 25 different indications. We also have significant experience with what's called a natural history study. That is a trial that is a non-drug trial, and I'll talk about that more on my next slide. But it's important for rare disease in the sense that we need to do trials to understand the natural course of the disease before we do intervention trials at times. We also do a lot of work with pharmaceutical companies on developing indication-specific outcome measures. So the majority of time in rare disease, the patients are very, very impaired. They're not able to do complex assessments.
They're many times not able to do, you know, a digital battery. They're sometimes not even able to do some of the commercially available standardized assessments on the market. So we need to develop outcome measures that are suitable to these patients and are also sensitive enough to detect changes. So to use the example from Rett syndrome, you know, these patients are incredibly impaired. Again, you know, they're not walking, they're not talking, and they have no functional use of their hands. But the drug was approved because these patients became more engaged. They became more responsive, they were more attentive. It was not, in a sense, you know, curative by any means, yet this small amount of change, relatively speaking, across the disease, was significant, but also very, very meaningful for these families.
And we can measure that level of change, that kind of granular level of change that's still very meaningful when we develop these indication-specific outcome measures that are designed with metrics to assess that level of difference. We also... This field of rare disease is new, in comparison to other indications, you know, in neurodegenerative disorders and psychiatry. I mean, we have a recent history, so there's no clear precedent yet for measures or methodology. So the vast work that we are doing now is incredibly valuable to our customers because we can pull on all our breadth to help them decide what to do and move forward with their trials, because in contrast to these other indications I mentioned, there's not decades of literature that they can pull on. They need to talk to the experts that are in the field now...
And then for Cogstate, these trials are fast. There's fast fails, they quickly work, you know, they're moving on to the next phase, kind of in parallel, very quickly, sequentially. So it allows us to iterate on smaller trials. It's a model that scales for us very easily. So in this next slide, I want to talk more about the point there about natural history studies and our experience there. It's really relevant to rare disease. So again, the natural history study is a trial that does not involve a drug. You're just following the patients over time, without any intervention. It allows us to understand the course of the disease, and this is really important for pharmaceutical companies because some of these diseases, we don't know how the individuals change over time.
You know, we see them, you know, when they're five years old, when they're 10 years old, maybe when they're 20 years old, but we don't understand the trajectory of the disease. These natural history studies also allow pharmaceutical companies to gain some information to inform their endpoints, particularly around feasibility. What can these patients do? What can they not do? What's going to work? And then, very importantly, from a regulatory standpoint and, you know, further on past the natural history study, in some cases, these natural history studies can serve as a control condition. So in traditional trials, you have, you know, a group that's on drug and a group that's on placebo.
In rare disease, sometimes there's not enough patients for two groups, and in other times, if you're doing a treatment such as a gene therapy trial, that is long, you know, they are usually about five years. These diseases are so impactful to the patients, it's not always ethical to have a placebo condition, particularly for that long. So these natural history studies that are conducted at the beginning of the program, at the beginning of the pharmaceutical companies program, they can often serve as the control condition, so you don't need a placebo group then. Currently, today, we are supporting four natural history studies. I just wanted to highlight one here. We're working in collaboration with a foundation. It's called the Lulu Foundation. They're working on an indication called CDKL5 Deficiency Disorder. It's a rare disease, highly impactful to the patients.
The Lulu Foundation has developed a partnership with seven pharmaceutical companies that have come together for this natural history study. So these seven pharmaceutical companies are working in collaboration to run this natural history trial. My hypothesis then, is that these seven companies are going to then run intervention trials using the data from the natural history study that was collected in conjunction with the foundation. And it's really important for Cogstate because we are supporting this natural history study. You know, it positions us very well to then support these additional seven pharmaceutical companies that will likely work in this area. Then next, I wanted to talk about another kind of point of interest asset of Cogstate that sets us apart. So we have a large team of neuropsychologists that work with us on a consulting basis. We call them our leads.
They're local expert advisors, just our term for them, but, you know, they're, they're consulting neuropsychologists. And we have this, they're a global team, and we can use them as clinicians for trials to actually collect the data. So this, what this allows, is you can use fewer clinicians. So that's the figure on the left. So I collated data from multiple trials, collapsed it, and to show that for these several trials, to collect data on 138 data points, so 138 assessments, we needed 53 people. So there are 53 raters collecting data for 138 assessments, and that's because this is rare disease. No one site's going to have a lot of patients because these patients are so geographically spread. And that creates multitudes of problems. It's not efficient. You increase scientific variance.
It's, it's not a great model. So Cogstate's offering this alternative where we have what we term central raters. So it's our team of neuropsychologists, and across multiple trials, we were able to collect data on 150 assessments using only seven clinicians. So the operational efficiencies are there, the financial efficiencies were there, and the scientific rigor was improved because we decreased the variance. And then there's another way we use our team of neuropsychologists, is to score some assessments centrally. So some assessments you can't do remotely. You either have a baby, or you have a test that involves a lot of materials, like tangible manipulatives. You can't do that remotely, but what you can do is have a site rater collect that data and then have someone centrally score it. And did a small study looking at the benefits of this kind of model...
What we saw, this was about 70 administrations. There were 37% of those administrations that had errors in scoring, that were able to be corrected with our central rater, kind of rescoring the assessment and correcting these data points. So it dramatically improved data quality using this approach. So in summary, let's say we have a lot of scientific support, a lot of scientific publications. The work we're doing, we collaborate with our sponsors to get the work sort of out in the field, for peer review process. It demonstrates a scientific merit. Some of these papers I am illustrating here involve the indication-specific outcome measures. I mentioned some around methodological considerations for rare disease, and some talk about how to determine the clinically meaningful change.
Like, is that difference enough, that two or three-point change you saw in your measure, is that clinically meaningful, and how you go about this? And we work again collaboratively with our sponsors to get this out. This is also then from a Cogstate standpoint, you know, taken up by the regulators to inform future approaches, which helps our business 'cause it brings people back to us as well. So then in summary, in rare disease, there's been really exciting progress recently. I mean, exciting scientifically, huge financial benefits for, you know, our biotechs, and Cogstate is just very, very well positioned to take advantage of this, large opportunity.
Thanks, Pam. That's wonderful. A couple of follow-up questions there. I mean, you, you talked about the first approval of a rare genetic neurological disease or the first treatment in that area. Your, your thoughts in respect of what that'll mean in terms of future opportunities, do you expect that to lead to an increase in investment in rare neurological disease?
Absolutely. I mean, they were the first ones to show that this kind of trial can work. We can change this kind of disease. I mean, that really de-risks future investments. I mean, it shows it's possible. It also shows that in order for a drug to get approved and then to get payer support, it doesn't need to be curative, and that's really important for these patients that are highly impaired. Just moving the needle is enough, and that's been demonstrated now very clearly. So I think it is gonna dramatically, you know, sort of increase the market.
Yeah, it's almost proof of lowering of the bar and proving to biotech companies that, you know, small improvements are really meaningful.
That's right.
You talked about your regulatory interactions. I think people would be interested to hear some of the ways that you engage with the regulators, either with or on behalf of, you know, Cogstate customers.
Yeah. So we actually do a lot of interactions with the regulators. It's a really important kind of work that we do. Sometimes it's indirect, in the sense that we advise our sponsors based on prior interactions and knowledge that we have, and sometimes. So that would be in helping them develop the methodology of their trials, selecting endpoints based on the experience that we've had. In other cases, it's direct interactions, so it's attending meetings, communicating with the regulators, particularly around endpoints that are new. So these are, these indications, again, they don't have a long history. We're trying new things. So it's educating and collaborating with the regulators to help them understand these endpoints that they might not be familiar with, and how to use the endpoints.
What kind of data comes out from them, how to think about that, and how we can apply them to rare disease trials.
Fantastic. The thing that fascinates me is the natural history studies you talked of, and you know, and the way that they can replace a placebo group in these trials and the logic for that makes a lot of sense. How long do those natural history studies take? You know, what's the normal timeframe to conduct those? And in respect of the you know, the example you use of the Lulu Foundation, I think it's fascinating that it's got seven you know, pharma companies working in a pretty competitive way. When does that natural history study you know, finish? And you know, so when do we expect you know, new things to come from that in terms of new opportunities?
So, you know, the duration of natural history studies, they can vary. You know, how rare is the disease? How long do we want to follow the patients in a natural way? So they do vary, but even with that variability, relatively speaking, they're quick, two or three years. And pharmaceutical companies can launch them simultaneously with their, intervention trial. So it's not that you necessarily need to wait the three years. No, but I wouldn't expect them to wait the three years necessarily for it to wrap up before they move on. And then with Lulu in particular, that one was three years, so about one year from now. It's ongoing. Yeah.
Fantastic. Thanks, Pam. Fascinating stuff, and, you know, again, we're... Pam will be available for questions at the end of the presentation. So what we're gonna try and do now is bring this all together, invite Rachel Colite to, to speak to this, just to sort of-... You've, you've had some, you know, we've had some deep dive now into Alzheimer's disease and rare disease. What we wanna do is talk about how all that comes together in terms of our offering for pharma companies.
That's right. Thank you, Brad. You can go to the next slide, please. So before we jump into, excuse me, before we jump into capabilities, we wanted to provide a quick picture of some of the key vendor organizations who typically collaborate closely with Cogstate in the delivery of CNS trials. So I've highlighted here where Cogstate sits in this, but this ecosystem dynamic really provides for us an opportunity for channel relationships, and it really requires that we have strong capability around commercial partnering and interoperability. So this is something that Cogstate has focused on as a competitive advantage in particular with the group listed number one, the clinical research organizations who are running the trials as well as number four, electronic clinical outcome assessments or eCOA organizations who support data collection for a wide range of the assessments.
So we'll, we'll talk about these a little bit more as we go through. So now we'll get into how we bring these, these services together through science, technology, and operational excellence, with a focus really on delivering better, more conclusive research data, to our pharmaceutical sponsors. Next slide. So it, it really starts with scientific consulting. We have, teams, as you've heard here, such as Pam and Chris, who've really earned trusted partner relationships with our, our, our pharmaceutical sponsor, customers.
They engage quite early in the trial planning process, which is really important for us commercially, and they inform things like trial design, selecting which measures to use, as Pam described, designing the quality program or the data quality monitoring programs, and then all the way through to statistical analysis and interpretation, and some of those FDA regulatory interactions that we talked about. So once the design is finalized, and the measures are selected, this is when we oversee the licensing for any third-party license holders or test authors, as well as overseeing any translation or cultural adaptations or validations for use in global studies.
So, I guess the point here is we support endpoints that go well beyond those that Cogstate offers, and so it really requires that we work with third-party license holders. And we've developed a real in-house capability around the nuances of this process, and it can be quite involved and not terribly interesting, but something that if you don't get right, it can really have dramatic impacts in terms of study startup timelines and also data quality. So these capabilities and relationships with the license holders are important for supporting that sort of complete solution in clinical trials. So electronic clinical outcome assessments or eCOA, as we call them, these are primarily conventional paper assessments that are deployed in an electronic format, so think a digital form.
Cogstate partners with technology providers in this space. We work with them and then closely direct the paper migration activities. We do this by infusing it with our clinical experience and expertise to inform the instrument design so that we can really squeeze out any opportunity for error prevention. These technologies come with a lot of capability for observing things like incongruent values, but you really have to have a deep understanding of how these instruments are used and what you would expect as an incongruent value in order to really make the most of technologies like this. So we find it's really important to pair our clinical scientists with the technology in order to really make the most of error prevention, which then helps us pursue that goal of overall data quality.
I think it's also important to note that these eCOA partners are important for us as operational partners, but also as commercial partners. Thank you, Brad. So rater training is a really significant part of Cogstate's offering for those conventional assessments, as these assessments can be quite error-prone and quite variable. So while the industry standard was previously this live instructor-led programs, often at investigator meetings where everyone would come together, we've transformed our offering over the years with technology to be more multimodal and really with more of a focus on e-learning methodologies. So in that time, we've also moved away from more of a one-size-fits-all training.
These different, more remote approaches have allowed us to also, in parallel, develop more bespoke certification pathways that could be more tailored to the specific experience level of the individual rater. So this matters to the sites and to the raters, but it also matters a lot to sponsors because what this does is, it supports on-time study startup and, and getting the training off the critical path, which ultimately shortens their, their timeline to market, which is, is quite important to them. Next slide. So central monitoring is really just an extension of the training program itself, but into the study. This is where our global network that Pam described of over 200 clinical scientists, I think they're supporting trials in over 40 languages.
These are mostly PhD neuropsychologists, and they'll review audio or video recordings and also source data, and database records, from the individual rating sessions to ensure that the scoring and administrations were done accurately. Scoring errors in this way can be corrected, as, again, as Pam described, and then administration errors can mean remedial training for the raters. So this is something that we're closely monitoring across studies to make sure that the ratings are of high quality and that we can intervene if we see raters beginning to drift from some of that training that they received at the beginning of the study.
The second set of eyes of having additional neuropsychologists review the work of other neuropsychologists is obviously very cost-intensive and time-intensive, which really shows the importance that sponsors place on data quality in these CNS programs, like the ones that we support. So next, we'll talk about digital cognitive assessments, and this is really where Cogstate got its start. I think this is what a lot of people think of when they think of Cogstate. And it's still a very key part of why pharmaceutical sponsors engage us to support the broader cognitive assessment programs in their trials. We offer among the most scientifically validated compliant platforms, and we have a large and growing test menu covering many aspects of cognition. So I've listed some of those here.
This is something we're adding to over time as we understand the needs of different sponsors. Recently, we've been de-developing some psychomotor vigilance tests to support our work in areas like narcolepsy. So this is a dynamic test menu, but one that has a pretty broad domain coverage currently. The platform really allows for these tests to be configured into specific batteries. So sponsors are taking a subset of these tests and putting them together in different combinations to address the research questions that they're seeking to explore in the programs.
And I think it's really important that computer-administered tests, they don't require a rater, or many of them don't require a rater, and so they're faster and easier to deploy because there's not all of that rater readiness and training and certification at the front of the trial. And they also dramatically see fewer issues of scoring and administration errors because it's really taken out of the hands of humans. And so this can really help bolster signal detection when you're taking all of that noise out of the trial. So that's really what we see as a driving factor in the selection of digital endpoints in many cases.
So here, you know, you heard a little bit about this from Pam and Chris, but I wanted to wrap on our decentralized or at-home data collection capabilities. So this is increasing in the clinical trials that we support. And you know, as Chris pointed out, it addresses patient burden, and as Pam pointed out, it also addresses data quality. But it importantly, there's been some FDA and other regulatory agencies making guidance around the need to increase representation of underrepresented minorities in research, and these approaches can also be really helpful in pursuing those goals. Cogstate has unmatched expertise in this area, and that includes large late-phase regulatory programs.
That's really what has set us apart, is we're, we're moving beyond small pilots, we're moving beyond certain niche use cases and using these approaches with sponsors in large clinical programs. There's two ways that we support remote assessment. The first is with our digital assessments. These have been really optimized for self-administration, with things like learn modules that are embedded into the test themselves, that allow the participant to understand the rules of the game before moving into testing, and to really make their way through that in a reliable way on their own. The other way that we support this is through central rating and telehealth technology. This is mostly related to the conventional assessments that we've talked about, such as clinical interviews.
This is where Cogstate clinical experts, that network of our over 200 leads, as we call them, they're conducting the assessments internally using this, a smaller, more highly trained and calibrated pool of raters. So this approach is common in areas like rare disease, that Pam leads, and it's growing in adoption in other areas, such as Alzheimer's disease, where there's now trials that are targeting a younger and quite cognitively healthy population, who are well suited for the approach, and also who have other time demands. You know, Chris talked about the importance of the caregiver and their considerations. But as we move earlier in the disease, the patients themselves are also quite well.
They're younger and also, you know, have quite busy lives, and so these remote approaches can fit better into their lives and encourage their participation in the trials, which can be quite burdensome and quite long. So we see this as a real growing capability for us. To wrap up this section, I thought I'd give a quick case example of how our range of services that we provide, they come together to support the needs of sponsors. In this case example, it's a phase III Alzheimer's disease study that's targeting the preclinical or presymptomatic stage of disease.
So these are cognitively normal individuals who have amyloid or tau biomarker of disease, and it's a difficult population to define or to find in the community because they are quite well. Your typical Alzheimer's patient may be seeking care for their symptoms, but these individuals may not be. So the sponsor needed to a real patient-centric study design to engage the several thousand participants that are required for this study, which follows them over multiple years. And so this study allows for all of the cognitive assessments to be done at home versus requiring that there's a travel into a medical center. So Cogstate's engagement in this started out with consulting. We worked with a sponsor on endpoint selection and optimization, and that included several Cogstate tests.
We also trained two distinct cohorts of clinical and psychometric raters to conduct all the rating sessions remotely, including the primary endpoint. This was all conducted via telehealth. And we also deployed our full data quality program and services in this study, where we are doing the central monitoring and rater training to ensure that these raters were trained to really high standards. So the trial's ongoing, but it's been a wonderful example of our close collaboration with sponsors and vendor partners to achieve a really innovative approach that could progress the aims of finding this particular patient population, which is quite difficult to find via traditional clinical trial recruitment strategies.
And it's similar to what Pam pointed out in the rare disease use case, just a slightly larger scale, but we're seeing tens of raters, you know, a few dozen raters versus hundreds of raters to support a program like this one. So that obviously has really important implications on data quality, where we can invest all of the data quality resources and focus those on a small, really tightly controlled group of highly trained raters.
Thanks, Rachel. That's, I think, fascinating, and I think hopefully gives everyone a much greater insight to the range of services that we're offering. We finished on a decentralized clinical trial example, so I wanted to sort of start with that. You know, I think people are interested to understand the shift that we're seeing from site-based assessment to remote assessment, you know, now that sort of... You know, we obviously saw that take up through COVID and, you know, and those COVID restrictions are now gone. You know, what level of shift are we seeing? Is that still occurring, that movement to decentralized trials?
Yeah, it is. It's not a monumental shift. It's not an overnight shift where we saw all of a sudden, you know, all of our trials move to fully remote. The case example that I gave, it is not the norm in Alzheimer's trial, certainly. In Alzheimer's, we still see a lot of our studies are in mild disease or MCI, so we're getting further into the... As the disease progresses, you're seeing less openness to doing trial designs that might involve additional technologies and the interfaces that are required with those technologies in some cases. But as we see more preclinical studies, we are seeing more of an interest in these approaches because it does really lend itself.
We're also seeing that sponsors are just taking pieces of decentralized methodologies and using those to improve the way their mostly site-based trial is conducted. I think these are really important shifts that we can differentiate our offering and leverage this expertise that we have, but also it really helps these conventional trials sort of borrow from the DCT methodologies to make it more patient-centric.
Yeah. A question for Pam and Chris. I mean, Rachel talked about the scientific consulting. I think people would be interested to understand what form that consulting takes. And also, I think, when are we brought in for that consulting? And how does that, the consulting we do, how does that either work with or differentiate from the scientific advisory boards that many companies have?
Do you want to go first, Pam?
Sure. So we, we do both, right? So we consult with pharmaceutical companies directly, you know, just in one-to-one relationships, and then we also serve on multiple scientific advisory boards. So... And the goals of both types of consulting is often very similar. We tend to get in very early, like, before the protocol is finalized, because the questions that I'm often asked, How do we measure change in this population? So we help direct and inform the endpoints and the statistical approach, and that, that is, it's before the protocol is developed. And sometimes, again, that's individuals. Often, you know, they get a group of people together, and that's their scientific advisory board.
So the content's very similar, the format differs, but either way, it's, it's a great opportunity for Cogstate to get in early, develop these relationships, and sort of inform the protocol in a way that's informed by regulatory interactions that we've had, as well as our deep scientific expertise.
And oftentimes, one of the unique things that we're able to offer is the breadth of experience. So we have scientists within the company who may have specific therapy area expertise or specific scale expertise, but at the same time, as a company, because we work so intensively in certain areas, we far more experience of the regulatory interactions that may occur, the study design questions that might be posed, than many of our pharmaceutical partners can have or could have, because we work in multiple studies within that indication in a way that they will not. So we're able to leverage substantial expertise in that way.
And then, too, you know, we try and stay involved in the science, you know, outside of that direct client interaction, you know, to be part of public-private partnerships of pre-competitive scientific advisory boards. So we maintain that level of scientific expertise in the areas in which we work.
Yeah, it's a really valuable resource that our customers take advantage of, and I think, you know, it's important for investors to understand that that scientific consulting usually has us involved in discussions before protocols are finalized. So we do get an opportunity to influence that protocol design. So it's a really important part of what we do and part of what seeds our commercial opportunities. I think the last thing I want to do before opening up to questions, and I'll just remind people that there's two ways you can ask questions. You can raise your hand and have your line unmuted, or you can type a question, and they'll be read by the moderator.
Before we get over to the open questions, Rachel talked about central monitoring, which I think is probably an area that, you know, a lot of people wouldn't necessarily understand that we do, that we use our pool of consulting neuropsychologists to centrally assess patients in trials via this telehealth assessment. I think it's interesting, you know, to talk about why that's happening, why pharma companies are moving to more central monitoring.
I guess so, you know, to start with the basic level, and then, you know, Pam might add some additional and more novel detail to that. At a fundamental level, because of the nature of many neuroscience CNS clinical trials, we're dependent on clinical outcome assessments. So they'll often be assessments that are administered and rated using clinical judgment by a clinician or rater of some kind, and those instruments then are prone to two broad kinds of errors. You can have errors in the way that the assessment was administered by the rater and errors in the way that the assessment was scored by the rater. All of those errors contribute to increased noise in the data, and more noise means less signal.
So it's, you know, it's a factor in the signal-to-noise ratio, and by reducing that error, by reducing that noise, we hope to have more successful trial outcomes at a fundamental level. So our biopharma partners will seek to address that, typically in a risk-based way. So, if an assessment is more prone to errors, they may spend more time on error reduction strategies, and at the same time, they may also focus far more on primary and key secondary outcome measures or at the pivotal trial stage of clinical development. So they'll take an error-based approach, and we'll support them in trying to make those decisions. And then we have a number of tools available to us.
You know, we can monitor directly the data itself that's generated and things like forms and worksheets and eCOA form instances. We can monitor audio recordings, and we can monitor video and audio recordings, and all of those things can give us some insight into the way that the tool has been administered and scored and help us to understand whether there are errors present and to correct and remediate those. And there's more and more focus that we can put on those things over time.
Yeah. And just to add to Chris's with a lens from rare disease, you know, we think about, again, about the signal-to-noise ratio. No data quality is perfect, that's our noise. But in rare disease, there's so few patients, each data point is critical. So we see this effort to check for data quality, to do central monitoring in rare disease quite a lot because they want to put every protection possible in place on that data because of that signal-to-noise ratio, which is inherent to not having a lot of patients in your trials.
Fantastic. I think we'll open up to questions now. And just, so, Ruth, I'll hand over to you to see if we've got any questions.
Fantastic. Thanks, everyone. My name is Ruth, I am a senior marketing manager here, and I will be walking through several questions that we've had from the audience, and I just want to take this moment, too, to thank all of our, our presenters, for this really lively discussion. So jumping right in, We've got a few questions around screening and recruitment, particularly around the AD realm. So this question goes: Last year, the company suffered prolonged trial recruitment delays, some of which are due to patient recruitment difficulties. So it's great to hear about the development of biomarkers and more awareness campaigns to facilitate future recruitment. So here's the question: Have you seen improvement already the last few months on that front?
As there are increasing preclinical trials starting, should investors take recruitment delays as almost a common thing for the business?
So I'll start with this, and then I'll hand over to Rachel. But I think there's two aspects that investors can focus around there. So obviously, during the fiscal 2023 year, we talked to recruitment delays, you know, as compared to our expectations, and therefore, revenue recognition or revenue earning related to those trials. So there's both the issue of delays in terms of recruitment, and then there's also the understanding, either via the sponsor, as well as by Cogstate, as to when those activities are likely to occur, and therefore, what our revenue projections are to look like.
So I think what we can talk to here is, you know, so certainly, you know, as we go through more and more presymptomatic or prevention trials, what we're doing is getting a better understanding of what that recruitment timeframe will look like. So we just get better over time at that predictive part of it. But, Rachel, you might talk to, what's happened in respect of some of our specific ongoing presymptomatic trials and how recruitment is looking in those trials currently.
... Yeah, I think in each of these, especially these trials that are going into populations, that it's a bit of a new frontier. I think the recruitment or pre-screening protocols for these types of efforts are also in development. And so there's trial and error that we're seeing play out with our sponsors, and I think as these trials go on, they are learning a lot and applying those learnings to really understand what it takes to identify these participants, and what efforts can be taken to characterize them earlier, to understand who's gonna be the right fit for the trial, and then hopefully expedite the patient recruitment process. So those...
We are seeing those learnings being applied, and we're seeing a more steady state in terms of how recruitment is going in those trials. The other part of the question, I think, was around, are we, you know, how we're supporting that in certain studies. Oftentimes, those early recruitment or pre-screening activities are a discrete set of activities from the clinical trial itself. A lot of times it's quite decentralized. It's happening at the sites. It's happening in all different ways at the sites. In other instances, the sponsor takes more of an active role in providing tools, infrastructure, campaigns to support that activity. It really ranges across the board and across different studies.
But the recent example that Chris highlighted, where we're working with a sponsor to do in-community pre-screening, where we are using Cogstate tools and technologies to try to characterize patients, and combining that with things like blood-based biomarkers, to come up with what will hopefully be predictive algorithms for directing people to the right trials that fit their patient profile. Those are the types of tools that we're seeing being employed by some sponsors, and that we really believe will be the future of how patient recruitment will go in the Alzheimer's space, in particular. Is there anything you would add to that, Chris?
I think it's probably worth noting, you know, what that shift to preclinical Alzheimer's disease is likely to mean for trial sponsors. The one element is that in the past, where sites would have traditionally relied on their own database of potential participants and then local advertisements, that strategy is no longer likely to be sufficient in and of itself. There are large numbers of patients who are, you know, entirely well, from a clinical perspective, that we're asking to, you know, think about enrolling in a clinical trial, and so you're having to go much broader, and really reach out into the community to find those individuals.
Another component to that is something that Rachel was mentioning earlier around the need and the expectation that sponsor companies will recruit traditionally underrepresented populations, particularly in the U.S., and the fact that these populations will not be in those locations where clinical trial sites currently exist and have capability. You know, again, it behooves us to go out into the community and find those people.
Yeah, and I think that's, you know, it, it's important to note there that the role of digital technology, that digital cognitive assessments have in pushing into the community and beyond those traditional Alzheimer's disease research centers. We see a significant opportunity for Cogstate in the future there. Thanks, Ruth.
Yeah. Thanks to all of you. Certainly a lot going on here and, and much to consider. So we do have a hand raised, so I will go ahead and unmute the line of Dennis Hume. Dennis, I'm gonna go ahead and unmute you. You are now unmuted. You might have to unmute on your side as well, and then you can go ahead and ask your question.
Great. Thanks very much. I was just wanting to ask, we can see that with digital... digital cognitive assessments, there's a big advantage for Cogstate. Can you talk a little about how your offering compares to your competitors for, say, an Alzheimer's trial that wants to use a traditional endpoint like CDR Sum of Boxes?
Yeah. So thanks, Dennis. It's a good question. I think, I think it's really important to understand the interaction between what we'd call traditional, you know, assessments, so that, CDR Sum of Boxes, for example, and the role of cognitive assessments. Chris, I think as a starting point, what you might talk to is how many different cognitive assessments you'd be likely to see in a phase III Alzheimer's disease trial.
Sure. So, you know, the burden in a typical trial can be pretty high. So, we may see, you know, upwards of five different assessment approaches being used within a single trial. They may be attempting to cover things like cognition, activities of daily living, different domains of cognition, quality of life, caregiver impact and burden, resource utilization. So there's a whole range of areas of potential clinical benefit that sponsors may seek to measure and various kinds of tools with which they may seek to do that. I suppose, you know, a particular advantage of the digital tools that we would seek to focus on and the comparison to the Clinical Dementia Rating is a good one.
If you take that, the intent of the Clinical Dementia Rating is really to be able to assess the functional impact of cognitive impairment across the disease course. So from people who are cognitively normal through to the mild, moderate, and severe stages of dementia. In order to conduct that assessment, typically, you're looking at approximately a 45-minute interview with the patient, which is preceded by a 15- 20-minute interview with the caregiver. It's a pretty substantial burden. So it involves interviews with two different people, it involves interviews being conducted in a certain order, and it also requires a clinical expert with experience of the disease in conducting the interview in the past. So really, really heavy burden and something that we know is never used in clinical practice.
So this is not being used by primary care physicians or even particularly by specialist memory clinics in trying to diagnose disease. It's by and large a clinical trial outcome measure, unique instrument. So the advantage then of the digital tools is to do things like provide more sensitivity at early stages of disease, have an instrument that's substantially lower burden, have an instrument that's easier to conduct in an unsupervised setting, have an instrument that can be conducted in both clinical practice and clinical trials, and can provide that link from clinical trial into real-world evidence. So, you know, a huge range of potential benefits and, you know, in contrast to that traditional assessment approach.
I think what's important as well is that often we're not seeking to compete with the CDR in many instances, even though there's a long list of benefits of digital over the CDR. But we often see it where there's a sort of a combination of psychometric performance-based assessments in the trial, as Chris mentioned, along with the clinical assessments and the clinical interviews, and so Cogstate's developed a capability to support the CDR. So when we see that in a program, we're typically thinking through all the ways to make it work really well in the program. And so we offer things like our central rating capability, where we have a whole group of CDR raters within the organization, and so it's something that we routinely support alongside our own digital tests.
Thanks, Rachel.
So we've had several questions on the competitive landscape. Of course, Cogstate isn't operating as the only provider of these services, and so kind of combining some of these, how do we as a company maintain our go-to status with sponsors? And what are some of the main reasons that Cogstate is awarded the opportunity to support a trial? And I'm gonna keep throwing them at you, but this last one: how do we foster these sticky relationships with customers so they, we have repeat business?
Yeah, look, it's a great question, and we do operate in a competitive landscape. I think a couple of comments before I open it up to the group, and I'm conscious of time, so we want to wrap this up relatively. But I think certainly the fact that we offer the support that Rachel was just talking about with respect to the CDR Sum of Boxes, for example, and those kind of assessments, as well as our own digital assessments, makes us fairly unique in the marketplace. So we do have a differentiated offering to those we compete with. I think it's the level of expertise that we bring to those discussions.
Pam and Chris talked about the scientific consulting, the fact that we can advise both pharma companies and scientific advisory boards, that we can help them in their interactions with regulators, and help them make sense of of the outcomes of their trials, is really important, that position us as a trusted advisor. In terms of how do we win work from new customers, or you know and from incumbents from our competitors. I think being part of you know really important breakthroughs in the industry is a critical way of how we prove our bona fides.
I think we're—as a company, we're really proud, for example, of the work that we did with Lilly in respect of their donanemab program, that really successful phase III program, where we're looking forward to the regulator's view of that data that's now been submitted in Alzheimer's disease. But similarly, we're really proud of the work that Pam did with Acadia in that first ever, you know, breakthrough treatment in rare neurological disease. You know, so, I think, you know, it's a combination of just continually really good, continuing to advance our digital technologies and the role that they can play as, as an industry, everyone pushes further and further into the community, and continuing to then leverage off the success that we've had.
As I say, I'm really conscious of time. We've gone over 90 minutes now. Just to finalize, a final comment, I think that one of the things we wanted to draw out today that is in the two areas that we work most, which is in Alzheimer's disease and rare disease. In the last 12 months, we've seen breakthrough treatments in both of those areas. Our hypothesis is that that breakthrough will lead to further investment in both of those areas. And hopefully today, what we've been able to do is give you some insight as to why we think we're so well-placed to benefit from that increased investment and to help our customers in that space. So with that, I thank you for your attendance. I thank Chris, Pam, and Rachel for doing this.
Hopefully, it's been informative for our investor group. We welcome your feedback in relation to that, and to the extent that you would like further of these, I think the group would be really excited to conduct them. So thank you again, everyone, for your time, and we look forward to speaking to you soon.
Thank you.