Unlocking the Brain- Innovations in CNS Drug Discovery and Neurodegenerative Treatment

Good afternoon, everybody. Welcome to Oxford Global's Thought Leadership webinar on Unlocking the Brain - Innovation in CNS Drug Discovery and Neurodegenerative Treatment. This session will start with our 20-minute interview with Emma Mead CSO Alzheimer's Research UK, from Oxford Drug Discovery Institute, and will delve into the strategic direction of this institute, the advances in CNS, shuttle technologies and translational approaches that bridge research with clinical applications. And the 20-minute interview is then followed by a 30-minute panel discussion on Innovative Approaches to CNS Drug Delivery and Neurodegenerative Therapeutics. Thereafter, we'll answer a few questions posted by the attendees. 

So, Emma the first question is, what are your current priorities at the Oxford Drug Discovery Institute in terms of CNS therapeutic development? 

Thank you Cerlin, and so, yeah, at the Oxford Drug Discovery Institute, we're really focused on finding new targets and validating these for prosecuting them as potential novel therapeutics for Alzheimer's disease, Parkinson's disease and other neurodegenerative conditions. So, we really take a lot of our targets from the GWAS datasets, looking at potential genes that are dysregulated in disease and determining whether these might be tractable for therapeutic intervention. And the GWAS datasets have really pointed us towards neuroinflammation as well as endolysisomal and organelle dysfunction as key kind of drivers of pathology. And these are really kind of sources of potential therapeutics for us to follow up on. We also have vascular dementia as an emerging area, and this is really due to co pathologies that we see in many neurodegenerative diseases. So, it's often the case that patients who are diagnosed with Alzheimer's disease have a mixed pathology of vascular dementia as well, and we see that as a really important and promising source of potential therapeutic intervention. And we're really keen to try and prosecute these in a variety of ways, looking at how we can validate these targets appropriately, using human IPSC models, and then taking them forward into potential screening cascades and bringing forward the best and most promising small molecules that we've identified and taking those into validation studies. 

That’s great. So, what scientific or technological developments are you most excited about in Alzheimer's drug discovery today? 

So I think a lot of the technologies that we're using, particularly in target validation center on Human IPSC technologies, and we've created a pipeline that enables us to genetically edit a variety of Isogenic lines that allows us to really interrogate specific genes of interest that we can then validate further and kind of on the basis of this, we've been developing a lot of mixed and CO culture capabilities. So, we've been focusing a lot on generating complex tri culture assays that enable us to really determine the impact of particular genetic drivers or genes that are influenced in pathology on different cell types within that culture system. And that's been really helpful for us, and I think is perhaps a step away from some of the more complex organoid cultures, which have been shown to be really informative in understanding what's happening in the pathology itself, and also helping to validate potential novel targets too. So, I think from the target validation perspective, some of the most emerging and exciting technologies would be some of these exciting IPSC capabilities. In terms of screening, there's lots of exciting and novel developments that are being made, and a lot of these are around advances that take advantage of technologies like alphafold and the AI and machine learning approaches to understanding protein structure. And this is really helping us develop pipelines for virtual screening, for example, which is helping to open up a range of different modalities that we might be able to follow up on, for prosecution, for potential development of new therapies. And here we can see that there are a lot of advances in the field of for example, PROTACs, which have been previously considered to be not particularly amenable to CNS drug discovery, but we're now understanding that with some of these new approaches, we might be able to use some of these novel modalities to target CNS related disorders. And there's also a lot of technological advances in discovering new biomarkers, for example, which is crucially important. For us, as we drive our programs toward clinical readiness, lots of new techniques are emerging using things like the new lives of technologies, for example, enabling us to find bespoke biomarkers, which is really kind of helping us to be very specific in terms of understanding the impact of our therapies and potential drug like molecules, but also in patient stratification as well. So that's a really exciting advance, but maybe taking it right back to the beginning in terms of target identification, there are huge advances in using artificial intelligence and machine learning, which has been applied to genome wide association study data sets, and this has really enabled better target prioritisation and assessment of tractability. So, I think from beginning to end, we're seeing that there are some really exciting advances in enabling us to find novel therapeutics. 

Yes, indeed, with regards to the latest advances in the CNS shuttles and drug delivery, could you explain a little bit more about the concept of CNS shuttles and their potential to overcome the blood-brain barrier? 

Yeah, so this is such an exciting area of research at the moment, and I think there are some huge advances that are being made in the field. So, it's well known that the brain is not the easiest organ to target in terms of drug discovery, and we've had to develop potential new ways to enable us to get therapeutics into the brain. And obviously the blood brain barrier is very good at keeping things out, so we need to find ways to circumvent that. And in recent years, there's been an advancement in the development of CNS shuttles, and this can range from different sort of modes of delivery. So, there is a lipid nanoparticle, for example, but most commonly, at the moment, the technology that's being developed is in sector mediated transport and the transfer and receptor is a great example of a receptor that's been harnessed to enable delivery of potential therapeutics across the blood brain barrier. And this has been really well exemplified by companies who are really sort of exploiting that technology to be able to deliver antibody therapeutics, in the first instance, into the brain. And we see that there are some developments in this space, with companies who have developed some of these amyloid beta monoclonal antibodies with the transferrin receptor ligand attached, and that's been shown to be very effective at allowing these antibodies to get into the brain more easily and also to spread across the brain more evenly, so that all the areas of the brain can be can be sort of exposed to these antibody therapeutics, rather than specific areas. And I think that this is a really important advance that's going to unlock our ability to be able to use a variety of different modalities. So as I said, antibody therapeutics are currently in development and are in the clinic for Alzheimer's disease, but now we're going to be able to unlock our capabilities to pursue other therapeutic modalities, such as PROTACs and larger classes of small molecules, other types of biologics, such as peptides, and this is really going to enable us to treat a broader range of diseases at different stages of disease as well. 

I see that's great. Thank you. Thanks for that. So, what are the some of the biggest challenges you've encountered in developing or evaluating CNS shuttle systems? 

So, I think that there's a variety of challenges, and I'm sure we'll delve into this in more detail in a moment with our panel discussion. But some of the challenges, for example, with receptor mediated transport, is the distribution and expression of some of these receptors. So, the transfer and receptor is not specifically localized to the brain, as an example, and it's expressed across endothelial cells in different tissues. And so I think that that could be one concern or challenge that we need to try and overcome to make sure that we are getting a good amount of our drug in the brain, and it's not being kind of directed to other tissues throughout the body, but also the affinity of some of these binders is really important for us to consider. You know, we need to make sure that our binders are not too tight, which might cause receptor degradation. And you know, for example, if receptive, if our ligands are too weak, perhaps they're not being internalised so well. So, we need to make sure that the kind of binding site and position of our potential ligands for these receptors and receptor mediated transport is, is appropriate? And that's an interesting question to address, and structural based drug discovery is obviously helping us understand ligand, you know, whereabouts on these receptors we should be binding, potentially avoiding the ligand binding site itself, so that we're not impacting the function of these. And transporters, which is really crucial, and that's really, you know, as I say, the structural based drug discovery is really guiding, guiding and guiding our knowledge in this area. So that's really, really been helpful. There's also kind of concerns around lipid nanoparticles, for example, compatibility and where those lipids become targeted as well, because sometimes these mechanisms can lead to accumulation in different parts of the body as well. So, we need to be quite careful when we're using strategies like that, that we are getting good brain distribution also, and obviously avoiding any toxicity that some of these lipid nanoparticles might elicit in the brain is really crucial as well. So, there's, there's quite a lot of kind of things that we need to consider in this space, and certainly there are huge efforts at the moment to try to understand this better as well. 

Sure, definitely. So, are there any particular shuttle strategies that you mentioned, you know - receptor-mediated and also nanoparticle-based - you find most promising for translational success? 

So yeah, but at the moment, there seems to be a lot of information and a focus on receptor mediated transport. And there are a range of different receptors that have been highlighted, such as the transfer receptor, but also solute carriers. LAT1 is a really interesting carrier, which has been exploited for CNS drug delivery as well. But there are some other interesting approaches to CNS drug delivery that don't necessarily use these processes. And some of these are things like low frequency ultrasound, which is a really interesting area where we're seeing that, yes, I say, these low frequency and ultrasound can open up the blood brain barrier for short periods of time to allow therapeutics to enter the brain. And this could be something that could be easily exploited in a clinical setting, which is quite exciting, and there's a lot of active research around this at the moment as well. So, I think that there are both, you know, advantages to us understanding more about the pharmacological processes, but also the non-pharma pharmacological processes that could be, you know, interesting to follow up on. 

Yes, with regards to translational science and pre-clinical models, which you mentioned just now, how do you approach target validation and pre-clinical assessment in a complex disease such as Alzheimer's? 

So, a lot of target validation is performed using human systems, and that's obviously particularly important as we're trying to tackle this sort of complex human disease. And as I mentioned at the Oxford Drug Discovery Institute, we really have an emphasis on using human IPSC models, and particularly Isogenic lines, harbouring the risk and or resilience snips and genes of interest, and using these complex culture systems can really help us model disease better, so that we can determine whether genes of interest that are dysregulated in certain cell types have a particular impact on the disease that we're studying. So, this is a really important way for us to sort of genetically understand the impact of the targets that we've identified. But it's also really important for us to pharmacologically validate some of these targets as well before we or in parallel to mounting screening campaigns to find small molecule modulators, because we really need to understand if these targets are properly tractable and druggable. So, performing that in vitro target validation in parallel with identifying potential binding pockets on proteins of interest is really crucial, and in this way, in silico modeling is quite helpful to understand target validation too, so that we can really get to grips with knowing whereabouts on the target of interest might be particularly tractable and could be amenable to modulation and manipulation. And you know some of these kinds of technologies, such as alphafold, you know, where the capabilities, and that's basically a kind of increasing every day almost. It's, it's great to be able to use that to really understand protein structure and potential tractability in greater detail. And now there's the opportunity to perform quite, you know, ultra large virtual screening, which enables us to find potential drug like molecules that we can test in silico and then assess efficacy and determine whether our targets can be pharmacologically modulated in a cell system. And that's really helpful in informing us whether these targets that you've identified are truly pharmacologically and. And kind of what can be manipulated pharmacologically. 

I see, thank you for that. So, what are your thoughts on the reliability of the current animal models for neurodegenerative diseases on the whole, and how can they be improved? 

So, I think that's a really interesting question, and I think we all can probably kind of agree that animal models do have a useful and important place in drug discovery. But at the moment, there is no reliable model of neurodegenerative diseases, particularly Alzheimer's disease, that sort of faithfully recapitulates all aspects of pathology. And I think that this is a challenge, because some of the models are really quite focused on amyloid others on tau. And as we know, in a human, you know, the story is quite different. Where we see pathologies from, you know, we see amyloid plaque deposition, tau deposition, but also contributions of the vasculature that drive disease and inflammation obviously being an important hallmark of pathology. And I think taken together, this can't really be sort of fully, fully recapitulated in a mouse, but we can glean quite a lot of information from the models and in terms of understanding what happens in certain disease states and environments. So, if we are particularly focused on a particular specific gene of interest that we know impacts a particular type of pathology, then I think that it's very useful for us to be able to use animal models to understand better what's happening in the brain. And of course, animal models have an important place for understanding the kind of pharmacodynamics and preparing us for sort of clinical developments. We really need to understand whether our drugs are having some sort of effect in the brain, and that, for that reason, mouse models can be, can be really useful. And there's been some really big advances in this field now. And in particular, there's been a lot of emphasis on generating humanized mouse models, particularly of some of the known genetic drivers of disease. And I think that this is really opening up our ability to understand better or use mouse models kind of more effectively in our research. So, there's certainly scope, but also when we think about different modalities. I think mouse models are quite you know, can be useful for that. When we start to think about if we can use genetic sort of AAV or ASO modalities, for example, we can really begin to test proof of concept of those types of modalities in a mouse or a rodent system. And that's particularly helpful as we kind of move into these different spaces. So, there's certainly huge scope for using mouse models in research.  

I see that's great. So, thanks very much for that. I do have one last question for you, which is, what advice would you give to other institutions aiming to bridge the gap between early research and clinical development in CNS disorders. 

I think, you know, I've thought quite a lot about this, and really for me, I think being really clear about the target validation experiments that are being performed is essential. Because I think, you know, if we don't have the right targets, we're never going to make the right therapies. So thinking about, you know, whether we are, you know, what experiments we need to do that are going to really give us the essential information to confirm that the target that we have identified is involved in disease is really, really crucial, and making sure that we do those experiments kind of efficiently and also kind of in the right systems. So, using humanised systems is really important for that. And you know, really kind of pinning down what the key, kind of key focused experiment should be, will really help us drive that decision quicker. And I also think that kind of building in some of these clear go, no go milestones into programs is crucial. And, you know, stop that really does stop us from working on things that are not really going anywhere. And I think that that's really important for translational research, and crucially, kind of not being afraid to use those decision points is really, really important. I think we need to be more kind of judicious in the use of, particularly no go decision points, so that we are making good, informed decisions and only taking forward the really kind of good, well validated targets that can be prosecuted in kind of screening campaigns and downstream clinical development, which is, you know, what we really want to do. We really want to try and get therapies to patients. And as I say, using those decision points and milestones is going to help us get to that point more quickly, and also sharing those findings to helping the community understand, you know, which targets are good to work on and which are not good to work on is equally important. So, creating an environment where we're able to share some of these, you know, potentially negative data is. It's really important also to make sure that we're all working together and moving programs in the right direction and potentially moving, hopefully therapies, toward the clinic. 

That's brilliant. Thank you. Thanks very much, Emma. 

So, I think we'll now proceed to the panel discussion, which is a very important discussion following the interview, which is about Innovative Approaches to CNS Drug Delivery and Neurodegenerative Therapeutics. And so, I would like to welcome again Emma, to moderate the panel discussion for 30 minutes. And as panellists, we would like to welcome Moein Moghimi, who is a Professor of Nanomedicine and Pharmaceutics at the School of Pharmacy Newcastle University. Shadi Farhangrazi, CEO of SMDG Discovery Group, as well as Raph Minter CSO of Alchemab. Welcome, and please go ahead with the panel discussion. 

Fantastic. Thank you. It's a pleasure to moderate this session, and I think it's wonderful. I think we're going to have a really great discussion today about, you know, these innovative approaches to CNS drug delivery and new generation and development of new therapies. But I think I'd like to begin really by asking our panel members, particularly Moein, you know how some of these CNS shuffle technologies are revolutionizing drug delivery? I know Moein is an expert in this space, so it would be great to perhaps turn to you first and hear about your thoughts on that.  

Well, thank you very much, Emma, and it's a great pleasure to be here. I mean, in the CNS drug delivery, I think it's been going on for many years, and there has been a whole range of technologies that people have applied and coming back into that. I mean, the these technologies, not only are based on, on adenoviruses, and we have seen, you know, many, many efforts in terms of using even exosomes as a kind of a new technology for delivering, particularly nucleic acids into the brain and also antibodies, but unfortunately, I mean, from my own perspective, none of these technologies have really stuck to their promise. I mean, people are trying it, trying to make these systems better, but their behaviour is quite erratic, and the reason is, we still don't understand the cell biology of the blood brain barrier, and unless we put more effort into that, I think it would be very difficult to design a carrier system that can target the blood brain barrier in a very efficient way, negotiate its way through endothelial cells of trafficking and again, what proportion of that can actually cross in intact form and get into the brain parenchyma, if not only that, but also how those particles that actually get into the brain parenchyma can find their way and get to the actual target cells. And considering that both BBB and also the brain. Perennial is quite hesitanious. I think it's a daunting task. It's not going to be easy. We have seen a lot of issues with AAVs, particularly when applied to other type of diseases such as cancer lymphoma, the toxicity is pretty serious, and it's very difficult to imagine what's going to happen in the brain with exosomes. A lot of investment was made, and again, a lot of work has been actually stopped effect zone because of the erratic responses. Sometimes the target, sometimes they don’t, and the quantities are not sufficient. So again, we don't know where we stand with them. With antibodies, we have seen some clinical product coming out. And again, depending on what they are, and we have heard a lot about kind of toxicities or bleeding, blood brain barrier level perturbing a lot of biological processes there, including figuring immune system reactions, inflammatory reactions. So again, we have to be very careful if we are going to use antibodies at the end of the day. The question is, what is it that you want to carry into the brain, what is the therapeutic molecule and how you are going to design a system that actually works for these reasons? I think a lot of people came into using a synthetic carrier like nano particles and trying to decorate them with different type of ligands. And unfortunately, again, has also been quite disappointing, because the problem is we cannot make this type of nanoparticles with the right avidity and right affinity to engage with the receptors again, cross the blood brain barrier and engage with the target. And most of the studies don't even quantify it. That is the interesting bit, that they don't quantify it and they don't really study what actually happens in the brain parenchyma, then these carriers will actually get in there. So, from my perspective, there are a lot of work that has to be done from fundamental issues, from not only understanding how transport process actually work, but how to translate them to make something really feasible and also cost effective at the end of the day. Again, nanoparticles could be an interesting way of delivering nucleic acid, because if you understand the principle or the basis of many of these diseases, perhaps genetic intervention could be the most efficient way. But again, for any type of disease, at the end of the day, you need combinatorial approaches, combination therapies and so on. And maybe nanoparticles can offer this type of treatment in different ways. But again, with lipid nanoparticle, as you mentioned yourself, especially the ionizable lipid and cationic lipid, because they're highly poor inflammatory and you have a disease condition like Alzheimer's disease, or, I don't know, Parkinson's, the last thing you want to do is to induce even more inflammation in the brain. Although there are advances with some of these lipids, people trying to make it better, but you have to have a kind of a more holistic view, my much more systems approaches, in order to understand what happens to the carrier system from beginning to the end. So, to cut the story short, I mean, in a nutshell, we still need to understand a lot of fundamental issues. Learn from nature itself. There are some, for example, examples like podge display or bacteriophage that exactly how they actually work, how they engage with their target. If we can translate those things into a delivery system, then we are in a much better position in order to cross the blood brain barrier and get into the right target locations.  

Thank you Moein, you've raised some really interesting points there, and I think maybe one that I might just touch on is that the point you made about models for the BBB, as you highlighted, we really don't know very much about the blood brain barrier. It's a complex kind of system selling the system. And I wonder if maybe you had any thoughts on some of the good or best, best models that are available at the moment. I appreciate there are some organ on chip models looking promising, but yeah, any thoughts on that, not just making a model.  

The point in here is we still don't understand what happens to BBB as a disease is progressing, because it's a dynamic environment at the end of the day. So, as a disease is starting to progress, the function and the permeability of the BB is actually changing. And again, it's very heterogeneous in one location of the brain. It may function differently depending on the blood flow and what is in the blood and what is in that environment. When we have so many cells controlling the functionality of the blood brain barrier. There are different subsets of microglia. We have different type of neurons sitting around so we still don't understand we are in a very kind of a naive stage. And the models that we have are very simplified models. So, it's not a true reflection of the blood brain barrier. Even you know these very advantages that we have seen in terms of the kind of ad models or even micro fluidic models of BBB based even on IPCs. Again, we don't understand how that model is really relevant to a patient. So, but again, we need something to work with, and we need to understand those. And maybe that is where AI could actually help in the future by understanding what is happening in the brain pathology that is the human brain, and look at the animal models that we actually have and trying to use AI to see how we can use all this information in order to make a better BBB modeling, not only in this flow, but also how to make a better animal model through genetic intervention. And that is, I think AI has potential in advancing the models at the end of today,  

Thank you. You also touched a little bit, on sort of antibodies. And I maybe wondered if I could turn to Ralph to ask, is that, obviously that being your area of expertise, Ralph, do you have any kind of experience or thoughts around the use of antibodies in terms of circumventing the blood brain barrier and as a CNS shuttle? And perhaps if I wondered if you could comment a little bit on some of the points that mer made around, some of the caution that needs to be taken around using antibody therapeutics and shuttle technologies for CNS disorders. 

Yeah, absolutely, yeah. Thank you, and thanks for the invitation to join the panel. So yeah, I've been working antibody discovery for some time, over 25 years. And I certainly remember discussions about 20 years ago where we wouldn't consider taking an antibody into the CNS space, principally because of the blood brain barrier. So, the belief was that because antibodies are given peripherally into the bloodstream, and we know that maybe point 1% or thereabouts of the injected dose actually makes it to the brain that was believed 20 years ago to not be sufficient to get a good pharmacodynamic effect. So, I think a couple of things have changed in recent years. So, some of the amyloid antibodies that have been taken forward in the clinic, even without BBB shuttle technology attached, have shown that you can actually get a pharmacodynamic effect for a peripherally administered antibody. And I think that was somewhat surprising for the field. Some of the doses given are relatively high in the periphery, but it's certainly possible to have dramatic effects on amyloid clearance, even without shuttle technology. And then, much more recently, I think some of the shuttle examples, certainly some of the Phase 1 data that's come out in the last year suggests that you may even be able to boost that around tenfold by using things like transfer and receptor to get more drug across. So, I feel perhaps a bit more optimistic about the about the future when it comes to applying antibodies to CNS disease. I think some of the specific points, you know, it's good to talk about how, you know, there have been some bleeding issues, things like ARIA with amyloid antibodies, and also some of the kind of inflammatory angle around FC receptor interaction. But I think those are also things that are tunable in the antibody space, so the amyloid antibodies deliberately engage FC receptors in order to clear amyloid via microglia and FC receptor engagement is something that can be switched off in antibodies if inflammatory signals are a concern. So, I think a lot of these potential challenges can now be overcome.  

Well, that's really interesting. Thank you. And maybe like to turn to Shadi now and ask about your kind of experiences with the CNS shuttle technologies. I know that you have a breadth of experience in this field, and I guess kind of picking up on some of the points that have been made here around also antibodies, but also the nanoparticles. And I wondered if you could maybe comment on the pros and cons of some of these from your experience. 

Thank you very much, Emma, thank you for the invitation. I actually just want to comment on a few things. First of all, thank you for that really in-depth outline. I'm happy to say some of the things you mentioned, including using IPS C cells, complex tri cultural assays, vascular dementia. We were actually working on this as far back as 20 years ago, and we were talking about vascular dementia at that time, and we were also using in silico modeling. Obviously, we have a lot more capability now than we did at that time. I think that with antibodies, I agree with Ralph that I do remember 20 years ago that we were talking about antibodies, but I believe that even though we have made huge advances, there is still a number of issues and challenges. I was actually interested in what Ralph described as antibodies are working, because we still cannot explain why you're seeing, and to me, 27 to 30% is actually a lot of percentage of people who are getting inflammation, brain swelling, brain shrinkage and the fact that the people who actually need some of these drugs, they avoid the people that the Alzheimer's patients that were employee for, they cannot get these drugs. So, we have really major challenges in front of us, and that's why I've. So I have said in meetings in the past that we do have a lot of challenges in front of us, with antibodies, what we have, I believe that patients put patients who I speak with, they are asking for something better, even though we do have approved drugs that are in the market, and that's perhaps why countries like UK, they have not approved it. Part of it is a cost. You have to bring the cost down, but the other part of it is looking at major safety issues. The other thing is that I, I'm happy to say to both, I think moi knows this, but to the other people here, that when it comes to receptor mediated delivery, into this brain parenchyma. We have done it our technology and nano ligand carriers and nano ligand blocks, they show unprecedented safety and efficacy, and we have a lot of this data is public, and you said probably 10, 15% of data we have is published, publicly available. So, we believe that it is doable. When it comes to nanomedicine and nanoparticles, there are issues. I also agree with both Emma you and Wayne that I don't believe lipid nanoparticles are really the solution. I think there are major challenges with LNPs, the people who have actually described it, even so, people are saying they're seeing a lot of it in the brain. I don't think that that actually quite common in a lot of the studies I've seen and investigators have spoken with but they do believe that there is promise, and especially with receptor mediated transferring receptor is one. We are also looking at rage receptor. And just my last comment, I'm so glad you mentioned, I think one of the first things you mentioned was neuroinflammation. We are huge believer in in really kind of tackling. In fact, what we believe in our company is that the future of treatment of neurodegenerative diseases is very much like a number of other diseases. We have to have a number of different modalities, cocktail of drugs. And I actually believe there will be a time that patients will walk into a clinic, maybe once every two months they get a maybe IV treatment. And for maybe a nucleic acid, and then they get another medicine that could be anti-inflammatory. So, I believe the future of neurodegenerative medicine, a future that we believe in, in our company, will come with a copy of drugs for every single disease. And it goes towards a number of targeting, a number of things, I'm going to stop. 

Thank you Shadi, I completely agree with you. I think, you know, I hope that we are moving towards a spot where we're able to give patients, you know, a variety of treatments that suit the stage and type of disease that they're presenting with. And I think that that's absolutely the ambition, isn't it, to try to get to that point. But so, I'd really like to pick up on that and ask our panel, what do you think the sort of the best type of modalities at the moment? Because obviously, as Ralph highlighted, we've had some successes with the antibody therapies. You know, perhaps the gold standard might be small molecules, so that patients can take medications in their own homes. And obviously we're seeing some progress in that that space, but, but maybe Ralph, I might, I might turn to you first to perhaps comment on some of the advances that are being made in the antibody therapy space, because I understand that there are potential, kind of, you know, different formulations that are enabling kind of different types of different types of treatments, of antibody therapeutics, or sort of similar types of biologic therapies that can be delivered in an environment that isn't in the hospital. I wondered if you could perhaps comment on that a little. 

Yeah, I mean, I think you know when it comes to how do you deliver antibodies. Obviously, there are different ways to do it. So, you know, in more severe disease settings, it's normally more acceptable for patients to go into a clinic and have an infusion, you know, which may take, you know, one to two hours. What we've seen in recent years is an increase in the number of self-administered subcutaneous injectable antibodies, where people can actually deliver the antibody themselves. At home, there's obviously some logistical challenges there, but it saves the patient having to go in for, you know, these long clinic visits. And I think, you know, I'd point to the kind of the weight loss space has been a lot of excitement around weight loss drugs that are self-injected. They're not antibodies. But it shows the principle that, you know, if there's enough motivation, people will be willing to use injectables. It's never going to be as convenient as a pill. So, I think you have to weigh each modality up based on its efficacy. But you know, we're talking about, in the case of Alzheimer's and Parkinson's, we're talking about severe neurodegenerative disease where I think people would be willing to either take an infusion or a self-administered injection. 

And yeah, I think that you've pointed out there, the sort of learnings that we're having from the weight loss space is quite helpful, isn't it, to think about whether we can use some of those, those learnings new generation that's really interesting, and so perhaps Shadi and Moein and I might turn to you now and ask, what, what sort of novel and emerging modalities do you think are going to hold the most promise for patients? Perhaps I can turn to Shadi in the first instance. 

Actually, I was going to say I think Moein should take that question. 

Yeah, please. 

Great. Okay. I'll take that - from my own perspective. I mean, the first important thing to me, I think, is inflammation, and inflammation is the root of all. I mean, we have inflammation for a reason, because it's a signalling to the body that okay, there is a danger, there is a problem, and when it's not controlled, then everything goes per shift. So, inflammation is very important. And what is again important in here is that we have the highest number of polymorphisms in genes that controlling inflammation, and that could actually explain why we see different responses in different patients. And if you can understand that level of polymorphism and how those products actually working, maybe we can do much better in terms of personalising these treatments, and probably we'll get better results. And then coming back to the inflammation and when we're using antibodies, because antibodies are also perturbing innate immunity, so when they get into the brain, when they bind to a target, they still don't understand how they protect innate immunity locally, particularly inside the brain. Are they going to trigger a complement activation? Are they going to trigger some activation of receptors on microglia and through signalling processes, maybe we are doing something else in the brain. So again, we need, we need to understand, I mean, again, is the lack of fundamental knowledge that we have in terms of these effects. And apart from inflammation, again, we don't understand the molecular basis of many of these neurodegenerative diseases, whether it Parkinson als whatever, and there are wonderful hypothesis, wonderful ways people are trying to test different pathways, different signalling molecules and so on. But diseases integrated. I mean, we cannot just pick one thing that is what we want to do. God will be very simple if, if you have one specific target and we can address that, would be wonderful. But it's not like in reality. It's not like that. So, if we can understand the molecular basis of those, maybe gene therapies are the are the future. Maybe gene therapies are, are the answers genetic intervention would be the answer, not by yourself, but you need to add this inflammation at the same point. So, if you can do that as a kind of an integrated approach, having a much more complex kind of therapeutic profile, rather than having one carrier system or one specific drug. I mean, as it is, we cannot, even, you know, correct many other types of disease, and never mind the brain problem. But again, that is what, what we need to study, and we need to look into. So, if you do that, and I think a combination of genetic therapies, inflammatory kind of you know, addressing the root of the inflammation in many conditions, and let's don't forget, we're always trying to focus on the brain. Maybe, maybe many of these diseases can be adverse at the vascular level, maybe outside the brain. If you can control many of the properties outside the brain, you will reduce the burden of all these problems in the brain, and maybe things will change. 

Yeah, it's really interesting. And I agree. I think, yeah, when we think about Alzheimer's disease and neurodegenerative diseases across the life lifespan, there are so many influencing factors aren't there, which, which need to be taken into consideration. I wonder if I could maybe kind of touch on, sort of pick up on some of the points that you made there, Moein, and you know, you're talking about kind of different areas of the brain being affected and inflammation being quite important in, we know, being very important in driving pathology. I'd like to maybe sort of focus our discussion now a little bit around targets and how we find. Targets, because we know that genome wide association data is informative. But I wondered if the panel thinks that there is, you know, what are the technologies help us find good targets, but now we have so many kinds of omics databases that we can assess and things like spatial omics, so I wonder maybe Shadi, if you have any thoughts around that in the first instance. 

Thank you, Emma. Actually, it's interesting, because I was in another meeting about three, four days ago, and somebody asked me a similar question, and I gave an example. I said, if I'm driving from London to Edinburgh and my car brakes on the way, I don't change my destination. I actually change my car. I actually believe that one of the major challenges we have had is we have not really had enough, I think, good enough, tools to study a lot of these targets. Look at Alzheimer's disease. I mean, we have known for a long time this, you know, the whole discovery about the different employee, 234, variations, beta amyloid, APP PAU, is we have had a number of targets to work with. What we haven't had have been really good tools. So, my comment has always been, look, we need to look and see how we can actually find those better tools. And that's really where our company is looking at, we are we are providing better tools, not just to deliver genetic medicine, but also to better study some of these targets that they have had, the same thing across the board, other neurodegenerative diseases. So, I don't know if I'm answering your question, what is the best target? We are continuously finding other targets, another disease we are working on, ALS that my colleagues I'm working with, just in the last three, four years, they have discovered two different mutations of ALS. You're working on those different mutations. So, I think the key here is one better tools. The second would be, I think it will be your next question, partnerships and the third thing is that really, we should be open to new innovations, not try the same thing over and over again and expecting a different outcome. 

That's great. Yeah, no, and I will certainly get onto partnerships. But before that, I would just like to turn to Ralph, perhaps, and ask, from your perspective, you know, perhaps in the setting that you're working in, you know what, what to you, makes a well validated target, and what sort of data is needed to build confidence that a target is worthwhile pursuing therapeutically? 

Yes, great question. And I think you know, fundamentally, if we're talking about CNS, we need to prosecute more targets. You know, I mean it, I know I focus on antibodies, but, you know, we've only really seen success with amyloid so far, and that's one target. So, we need to take a lot more targets forward into pre-clinical and into the clinic. I think I would look at it at different levels. I think you mentioned GWAS as being a, you know, a fundamental way that we discover and prioritize targets. I think there's emerging technologies now with things like spatial transcriptomics single cell, which adds another layer to that and tells you this target is expressed on the pathogenic cell type in the right disease compartment, that can add further validation and de risk the process. There's coming technology around single cell proteomics that could similarly, you know, build confidence. And then what we do at Alchemab is kind of a slightly different approach, where we want to understand what resilient humans actually make antibodies to, and that's our kind of way in to finding targets. So, we, each of us, have, you know, a huge repertoire of different antibodies in circulation. What we find really fascinating is when two people who are resilient to, for example, Alzheimer's or Huntington's have the same antibody, and we really want to understand what that antibody binds to, because this could be a way to really shortcut the whole process and find out which the most compelling antibody targets are. So, I think ultimately a good target is one that ticks several of these boxes. So, it might have support at the DNA level, the transcript level, the protein level, and maybe even at the immune level. And we're looking for the intersection of those things. 

That's really fascinating, I think, yeah, trying to understand what causes that resilience is crucial, isn't it? And so, in your hands, you know, what sort of technologies or models are you using? Are you using? And I assume human IPSC systems. 

Absolutely, yeah. I mean, the process starts with human antibody analysis, but then when we get to doing the biology downstream, we're very interested in IPSC monoculture systems, but also the co-culture systems you mentioned. I think a dream for us would be to be able to go all the way to the clinic based on those types of data, rather than having to prove efficacy in a in a mouse model that doesn't necessarily replicate the human disease. I don't think that's realistic right now. I think we're still tied to mouse models of disease and in the drug discovery process, but it would be nice to see more drugs going forward based on these kinds of translational human models. So, I'm a big, big supporter of those. 

That's brilliant. Thank you. So, I'm aware that we've not got too much longer left, and I think we have quite a big topic to discuss now around you know how we progress our programs through collaboration. And we all know that there are some certain advantages of working together across academia and industry, so maybe Shadi. I'd like to turn to you to ask this question, what do you see as the main opportunities in academic and industry collaboration to advance CNS drug discovery. 

I actually think that the question we should ask is, how could we all collaborate much better and easier? And I think that really that goes across is academia, industry, nonprofit organization and even investors, and I say that, and sitting here as a businesswoman, both neuroscientists and a businessman saying that, but I think we need to really look at the model, the model, the model hasn't worked for neurodegenerative diseases. The model hasn't worked for neurological diseases. So, we need to come up with better model. And I believe the better model is for us to work, to work much better. Some of the things that I think has happened in the past, I think, for example, the pharma, this whole question of not the concept of not invented here, for those of us who work in innovation, so not invented here. I know that Pharma is more and more interested, but they're going after the same things. Many of the tools that they're looking at is the same things over and over again. So, we should be open to more innovations. We should make it a lot easier take shorter time for pharma to work with academia, maybe work with nonprofit institution coming to investors. You know, I believe that investors need to educate themselves. Recently, I heard of a company that was founded on that, but they say the founders had had discovered their receptor. That receptor was, was actually discovered in 1980s Are you telling me that the investors are actually not reading the papers, not going to read it? So, there are a number of different factors here. One is that go after innovation, be open to innovation. Train the next generation of scientists, so those young people who are coming after us, we need to really do a much better job of training them. And the second thing is that for everybody to educate themselves, there are a lot of things in the literature that people are not reading, especially investors are not reading it. So, and my last comment is that beyond your friends, you should also be open to working with everybody else. 

Thank you. That's it. Yeah, I agree it's important for us all to work together to tackle these challenges, but maybe just picking up on something you say there about kind of training the next generation scientists. I'd perhaps like to turn to Moein and ask you what your kind of perspective is on, you know, collaborating across the sectors and thinking about how we can encourage our younger scientists to work more collaboratively. 

Yeah, that’s an excellent question. I mean, what we have experienced is, I don't think we are training the next generation as good as it should be. And the problem in academia is that students, when they come, they want to achieve something very quickly. They want to see positive data. They want to see positive results. And unfortunately, that is not how science works. And 99.9% your theory is wrong, and serendipity is always there, and it takes you to a new direction, and you end up doing something else, something different, and that is something that students usually do. Accept. And the other issue is that they want to publish something, they want to publish something quickly. And you try to tell them that you need to practice patience in here. You need to see what happens. You need to see a bigger picture before you commit yourself to a publication. And most of the time when these papers comes out, they are not giving the right information, or is not detailed, or maybe something is wrong with them, and unfortunately, now we are using even these type of information to feed into AI and ask AI to make it even better for us. And again, I think that that would be a disaster in a long term, because we don't know what we are feeding into a system and what the system is feeding us at the end of the day. So, I think this training aspect is very important, because becoming a very kind of a dynamic world now everything is so fast. Everybody wants to achieve something very quickly, and we have lost that patience. We have we have lost that freedom of sitting and thinking and try to take our time to actually look into a problem in much more detail. And unfortunately, this is, this is imposed by the by the system we are set up, and we need to go back. We need to go back to what we had before we need to step back and look at the problem from outside the box. That is where you see collaborations starting to work, because now people are not under that pressure. And unfortunately, this, this has, it's actually destroying the field, not only in here, but, I mean, for the whole science at the end of the day. I mean, you look at now, we have so many journals, so many online journals, so many kinds of, you know, opportunities that you can send it here or there and that is what people are trying to do. Publish more and more and more. But at what expense are we solving the problem? And unfortunately, this is, I mean, it's not only me, and I think many of my colleagues are saying the same thing, but we have become a victim of the system, and we need to go back and correct that, and try to be much more calmer, try to be patient and try to look at the problem from a different perspective. And unfortunately, you know, with this kind of system, with the kind of the fundings that you get, the expectation that they have from you, is not going to be very fruitful in the future, in my view, unless we change. 

Well, thank you. That's some interesting perspectives, and maybe sort of following on from that, Ralph, I'd like to perhaps Derek's question to you. But as Moein says, there's a lot of conflicting literature around the field that we work in. And you know, when you're thinking about collaborating with academia or with other institutions, what would be, you know what would perhaps be a piece of advice in terms of what you'd be looking for in a in some science that you might want to take forward? 

Yeah, I mean, I think we, we’re in biotech. We've benefited greatly from academia collaborations, whether it's, you know, talking to clinical PIs, who really understand disease resilience way better than we do, whether it's accessing cutting edge preclinical models that are not broadly available. I think the only thing that that challenges us, and won't be a surprise to anyone else, is that you have to get these things kind of agreed in some kind of contract form before you can work together. And that is still, you know, in some cases, a six-month delay before you can actually do any work, and in other cases, it means you don't do the work at all, which is disappointing. But I do think there is enormous value in collaborating between industry and academe. 

Brilliant. Thank you so much. So, I think that we are just at time, but I'd just like to check whether there are any other questions that we should be covering. 

Sure, we have four questions from the attendees. But I think the most poignant one, would be the first one, which is what will be the preferred CNS drug modalities over the next five to 10 years, considering the various different brain shuttles technologies currently being invented? 

I'm not sure if, maybe, maybe Shadi would like to address that question. 

I think I'm going to ask Moein to answer that, because somebody who's working on future technology and medicines. 

I mean, from my view, I think the future lies in gene therapies, because that is a kind of a universal solution to many of these diseases, whether we are just in inflammation through gene therapy. Addressing multiple problems by delivering maybe multiple gene therapies into the same patients. And the advantage in here is maybe you need to administer once or twice during the year, so in terms of patient compliance, you are much, much better. It may be is much more even cost effective, and you probably get much better results at the end of it. That's a quick answer. 

That's great. Does anybody have any more comments from with what he's mentioned before we end? 

No, that's great. Well, thank you ever so much for the very illuminating panel discussion, and we thank you very much for attending and joining as panellists. And Emma, thank you very much for the interview and your time. We shall stop recording now and thank you for attending. Thank you.