Good afternoon and welcome to this joint webinar between Amiga and Abzeena. My name is Hilary Pollard and I'm a Product Manager of Amiga. I'll be hosting today's webinar. Always look on the bright side of cell death cytotoxicity assays for drug, antibody drug conjugate and development. So the agenda for today is we have two presentations for you, the first from Amiga and the second from Oxima. In the first talk, Darren Hayward from Amiga will introduce optimised assays for drug discovery in 3D cell culture. In the second presentation, Grant Harridans and Robert Francis will discuss discuss their use of cytotoxicity assays for antibody drug conjugate development. After both presentations, we will have a live journey with experts from both Amiga and Avzina. Please submit your questions at any time during the talks and we'll get to them at the end. On your screen, you'll also see a list of resources along with a short survey. And we really appreciate the thing you said. I'd like to introduce the first presentation over to you there. Thank you, Henry. So my name is Darren Haywood, and I'm one of the product managers at Promega. And today I'll be presenting on optimised assays for drug discovery in 3D cell cultures. So over the last 20 years or so, there has been a significant shift from people using 2D cell cultures and migrating into 3D cell cultures for screening drug compounds and drug discovery. Now several factors have driven the need for 3D cell cultures in drug discovery and those key drivers are this need for enhanced physiological relevance. So in 2D cultures, cells are confined to flat surfaces which alters their morphology and they failed to replicate the natural cell interactions and organisations seen in 2D or in vivo. So there's this need for better prediction of clinical outcomes. So drug responses in 2D models often fail to accurately predict what happens in animal studies or in clinical trials. Limited utility for drug screening. Also, this is the need for more accurate tumour microenvironment. SO2D cultures lack the complexity of tumour microenvironment with uniform nutrient, oxygen and sickening conditions which do not reflect the heterogeneous nature of tumors. Also there is this need for maintaining the cellular differentiation phenotype, so cells growing in 2D often D differentiate using that tissue specific features, which makes them less representative of the tissues that they're supposed to be modelling. So drug development and screening in 3D cultures, as we can see that there's a need to go from 2D to 3D and that's because with 3D, it obviously offers several advantages over traditional 2D models. So for example, they offer enhanced physiological relevance. SO3D models mimic the structure and the complexity of M vivo tissues, leading to more resistant cell behaviour. They will show offer improved predictive power, so drug responses in 3D models are often more aligned with vivo outcomes compared to 2D cultures. Also, they offer better tumor modelling. SO3D cultures more accurately replicate the tumor microenvironment, capturing nutrient gradients, hypoxia, and extracellular interactions, which are essential for Cancer Research. Also, they offer accurate insight into drug resistant mechanisms. SO3D models provide a better platform for studying drug resistance as they mimic the physical barriers and conditions present in real tissues that can contribute to resistance, and they also offer more reliable toxicity profiling. So cells in 3D culture often maintain a higher level of differentiation and exhibit metabolic activities that are more similar to those tissues to actual tissues even it's more realistic results. So as we can see, so there's definite advantages to using 3D cultures, but obviously there are challenges with using 3D culture as well. One of those challenges or some of these challenges can be they're quite complex to establish, but difficult to grow some of them. And, and sometimes there's this lack of standardized protocols, but one of the main challenges is the availability of 3D optimised assays. Now the challenge with this is many of the many assays have been optimised for 2D cultures. They don't really translate that well to being used in 3D systems. So they're not as effective. And if they're not as effective, they have had an impact. So these assets can affect the ability to measure these key outcomes like by relative and proliferation effectively. And therefore the results that are obtained by that can be quite variable. So absolutely there is a need for optimized between cell culture assays for measuring these key outcomes and by relative proliferation etcetera. And this is where primarily you come in. So Pramika, we have various optimised 3D cell based assays and protocols for monitoring key outcomes in 3D models. So we have our cell health assays, which is cell viability assays, cytotoxicity assays, apoptosis and Adm mean assays. We also have metabolism assays for example, like we have energy metabolite assays, oxidative stress, and assays looking at dinucleotides. Now in addition to these, we also have manual and automated systems for analysing the genome or looking at changes in gene expression. Now the majority of these assays, they fall within 3 modes. And those modes are lytic endpoint assays, media sampling assays or these non litic live cell assays. Now with some of these assays, it can be a mixture. So some of it can be LITIC or media sampling, depending on what assay that is a more protocol that you use with those assets. So what I'd like to do in the next slide is just look at these three modes in a little more detail. So the three modes of cellular assays that we have. So we have litic endpoint assays and these assays measure an enzyme or biomarker inside the cell. So here you have your cells in culture, you add the essay reagent that lies in the cell and it produces a signal, in this case a ruminescent signal, and that signals into a portion to whatever you're measuring. With these assays you, you generate a single data point per assay. So moving on to the non related assets, we have these media sampling assays and these assays measure an enzyme or biomarker released from this cell into the cell media. So with these, you have your cells in culture and what you do is you take a small volume of that media and you put it into a separate well. You then add the assay reagent and that results in a loomolescent signal. Now, because you're taking the small volume of media from that initial well, it means that you can do multiple samplings from that from that original well. So we these assays, you generate single data point per sample. Now the other non bitter assay, these lifestyle assays, all the real time assets with these assays, they continuously measure an enzyme or a biomarker in the same sample well over time. So with these assays, you have your cells in culture, you have the assay reagent, which then which which results in a signal, your luminescent or fluorescent signal. Now because these assays are non litic, that means that you can monitor this production of this signal over time. So with these with these assays you generate a single data point per read. So to look at the Primoga 3D cell based assays. So all our all these assays are validated for use of 3D cell cultures. So for example, if you validated for use in spheroids and organoids with some of these assays also like the media sampling assays can be used in other assets in other systems like organonic chip or microphysiological systems. But our assays are really simple to use. So they always follow this admit to measure assay format. Our assays are scalable. So the majority of our assays are 96 or three or four world plates, but they can't some of them they can be miniaturized down to 1536 world plates, meaning that they are suitable for heightened applications. Also, our assays are sensitive. The majority of them use bioluminescence and they're Multiplex friendly as well. And also when reading the signals from these assays, you don't need a specialized piece of equipment. You just need a plate reader that has luminescence and fluorescent capabilities. So looking at some of these assays in a bit more detail. So when you're adding a compound to your cells, one thing that you may be interested in looking at is how does that compound all that treatment, how does it affect viability? So how do we measure viability? So one of the first assets I want to talk about, and this is one of the assays that Abzena uses the network is the cell tied to Globe cell viability assay. In this one, I'll be talking about cell type to Globe 3D. And as it says here, it's becoming the standard for measuring viability in treats in culture cells. So with this assay is as some of you may know, it determines a number of viable cells in culture. So whether the assay works, you have your cells which are packed with ATP. You add the assay reagent, it lies as the cell releasing that ATP. That ATP is then used in the reciphering cipherase reaction to generate the luminescent signal. And that luminescent signal is then proportional to the amount of viable cells you have in culture. Now with cell types of glow 3D, it's, it has over 2000 hits in the Google Scholar and it's been used in lots of different assay systems. So for example, you've been using hydrogels in different matrixes and hanging drop cultures and bioprintic tissues, for example. So moving on to one of the real time assets. So one of the things that you may want to do is you may not want to look at emitting assay. You may want to see measure viability over time. And this is one of the assays you can do to measure that. So it's the real time glow empty cell viability assay. And this measures the reducing potential of the cell, which is a metabolic mark refiability. So the way that the assay works, so you have your cells in culture, so you add the real time reagent and that reagent has a approach substrate to the molecule on the left hand side and you have nano luciferase. Now the pro substrate is 7 perm so permeable where nano emuciferase isn't. So when you add the SO reagent, the pro substrate diffuses into the cell and goes it's reduced down to a red Oct reaction. It then diffuses out of the cell is a substrate from nano euciferase. So that's substrate 5 from nano emuciferase and generate luminescence. Luminescence signals then proportions to the amount of cell coherent culture and because this is non litical, you can monitor the production of this luminescence signal over time. Now this doesn't happen in in dead cells purely because they're non metabolic. So therefore you don't get pro subject to subject conversion binding to the luciferase, you don't generate luminescence signal. Now with this asset, you can continuously monitor viability in real time for up to 72 hours. With this assay, you can add it when you plate your cells, when you dose the cells, or you can use it as a live cell which you like endpoint assay, which can be added at any time during your experiment. Let's look at viability. Now with this assay, during your experiment, if you have any, or at the end of your experiment, if you have any remaining cells, those cells can be assayed further. So you can add other cellular assays or you can do downstream DNA or RNA isolation. OK. So that's two assets that we've got for looking at viability. But on the flip side of that, you may want to know your compound cytotoxic. We have an assay for looking at cytotoxicity and one of the assays that I want to mention is the LDH glow cytotoxicity assay. So LDH glow or the lactic dehydrogenase glow I say measures lactic dehydrogenase that have been released from dyne cells into the culture media. So the way that this has to work, so you have your cells that are packed for LDH. So when you stimulate your cells in your drug or whatever you were treatment, as the cells die, they release that LDH into the media. So then what you do is you take a small volume of that media. In this case it's two to five microliters. Once you've taken that media, there's you can add it to a storage buffer, then freeze that media down or analyzing at a later point. When it comes to analysing it, you don't have the detection reagent and the when you add that detection reagent what happens is that you lactic dehydrogenated media it catalyses the oxidation of lactate to pyruvate with a concomitant reduction of NAD plus NADH. Now in the reagent you have a reductase which takes that NADH and it produces luciferin from the pro luciferin. That luciferin is then used in the luciferin luciferase ATP reaction. You generate an inescent signal that is then proportional to the amount of dead cells that you have in culture. As I've mentioned, this essay allows you for repeated sampling and from that from your culture, allowing you them to track the seller response over time. Now these this media sampling essay is great for cultures that are under flow or dynamic conditions to like example like organometry or microphysical systems. Now, similar with the other assets, because this is an analytic essay, any cells that you have remaining at the end of your experiment, they can be assayed further with other cellular assays or you can do downstream DNA or RNA isolation. So we looked at viability and we've looked at cytotoxicity, but one thing that you might be interested is looking at the mechanism of cell. And this leads me onto an assay called the Real Time Globe and Actin 5 apoptosis and necrosis Assay. And this is one of the assets that I've seen it uses in their work. So the real time glowing Actin 5 assay, it measures the real time exposure of fossatol serine on the outer eucalyptus cell membrane. So how this assay works? So it utilises nano luciferase same similar to the the real time glow energy cell hybridity assay. But in this instance, what we've done is we've taken that nano luciferase and we split it into a large subunit and a small subunit. So a large brick and small brick and that is collectively known as nano brick. And what we've done with that with that split recipherase is conjugated it onto an XM5 shown here. Then in the assay reagent, we also have a necrosis detection reagent, which is a cell in permanent all dye. So how the assay works, so you have your cells encounter. So this is, this is a healthy cell and in a healthy cell or viral cell, the phosphatol serine is confined to the inner part of the cell membrane. So when you add the SA reagent, because it means that the annexing tribe cannot bind to that phosphatol serine because it's on the inside of the cell, the crisis detection reagent can't penetrate into the cells. So you with both in this situation you don't generate any luminescence or fluorescent signals, but as your cell goes into apoptosis you get the spot and time serum flipped from the inside to the outside of the membrane, meaning that your Nexium 5 can preferentially bind to that. Once a Nexium 5 is bound to Fosotel serum, it brings the two hearts of that luciferase together, and in the presence of the nano vuciferase substrate, it generates a luminescent signal. Now within the crisis detection reagent, because the cell membrane is still intact, that means that this can't penetrate into the cell, so you don't generate the signal. So in this situation, you're only generating a luminescent signal. But as your cell progresses from apoptosis kind of going into secondary process, you get more of that posture time theory flipped to the outside of the membrane. It means more ineptified combined to it. And in the presence of the substrate, you generate a larger luminescent signal. And because in this situation, the cell membrane becomes compromised, it means that that next sort of necrosis detection reagent inside the cell binds to DNA and generate fluorescent signal. So in this case you can generate a luminescent and fluorescent signal. So the real time indexing 5 assay is no wash one step connecting 5 assay. It allows you to continually monitor the cell state to determine apoptotic concept. It allows you to separate priming necrosis from secondary necrosis resulting from apoptosis. It's scalable and it can be using 96 and three and four. Well, So in summary, so we offer a range of these 3D optimize cell based essays that are designed to monitor cell health, metabolism and gene expression in advanced 3D cell cultures. So that concludes my part of the talk. And before I hand over to Abzina, I would just like to ask you some polling questions. So one of the point of questions that we have is, are you currently using 3D cell cultures in your lab? So we have 4 answers. So A is, yes, actively using them for various projects, B, occasionally, the specific experiments, C, no, but planning to start soon and D, no, not using them yet. So I can see that we're starting to get some, the attendees are starting to, to click on some of those answers. It's great. I'm going to give you a few more seconds to make your choices. Great. Thank you for for that. And interestingly, the the results that I can see are fairly split between those 4 answers, so thank you for clicking on those. Now the the last polling question I'd like to ask is which method do you most frequently use for culturing 3D cells? So select all that apply. So A do you use Stafford based cultures? B Hydrogel embedding to use hanging crop methods to use ula Plates or rotating more vessels, bioreactors, organonic chip, MPs or other. So I'll just give you a few more seconds to to answer those questions to select the answers that are applicable to you. Just just a couple more seconds. I can see some answers coming through. Thank you. So those the results are interesting. Thank, thank you for thank you for answering that question. So this leads us on to the the second part of the webinar, which is presented by Absena. So without further ado, I'd like to hand you over to Grant and Robert to from Absena to present on their their slides. Thank you. Thank you Darren. Hello everybody. They're a great pleasure to be able to present today. So myself and my colleague Robert here are going to present a talk entitled Always look on the bright side of cell death. So cytotoxicity essays for antibody drug conjugate development. So I'm Grant Harridance I I'm a manager within the by YSA department. I've seen Cambridge UK and I'd like to introduce my colleague Robert. Hello. Yeah, so I'm Robert Francis. I'm also a manager here at Absena and also the microscopy lead. So before we delve into the talk proper, I just wanted to give you a bit of an introduction to Absena itself. So for those that may not be familiar with with with our company. So we are a complex biologic and conjugate focused partner research organization and our USP is that we are a complete end to end solution provider throughout the drug discovery process from the early research and development right through to commercial in the clinic. So we focus on biocongent and complex biologics, fully integrated R&D throughout with commercial capabilities and then we have a stream streamlined regulatory support that's tailored to our partners research programs. We have a comprehensive global reach. So we have facilities both in the US and in Europe. The US sites based in San Diego and Bristol, PA, they, they focus primarily on biologics and ADC's, whereas in Cambridge, early R early R&D activities are centered here. So that's where we look located. But the most important thing is that we produce results. We get significant amounts of repeat business, which manifests itself in multiple integrated programs. So to do this, part of the, what I've seen really focuses on it's de risking the drug development and really making sure that the biologics can be developed right away from the research stage, right away to the clinic. So to do that, we asked 2 fundamental questions. Can we make it? And you know, can it be produced at the small scale to start with and then right up to the large scale for use within clinical trials and then on to patients? And then does it work as well? So we have to make sure that when we produce a biologic that it can be throughout the whole of the development processes that it's doing what it needs to be doing. So we use design principles to to do this. So focusing on the manufacture of ability, the immunogenicity and safety and the binding and function as well. So developability is a continuous process you right at the start with the target ID in the validation, we go from a hundreds of biologic of the biologic candidates and we whittle this down to one or two then which really are like our key candidates that we want to go forward. And then we need to be able to optimize those. So we might do small adjustments to make make them better for for use within patients. And again then we're going to break those down to three to six and then finally to the to the lead candidate that then needs to go on to the clinical trial stage. So bioassays the longest development process have different selection criteria. So at the start when we are screening hundreds of those antibodies, we want to make sure that the in that the bio assays that we're using our mode of action reflective that they are cost effective as well because we're going to be using the map scale. Then we're during the candidate screening where we want to be choosing those lead ones to take forward. We want to make sure that they are high throughput, sensitive, robust and reproducible. And then further on in that process of the development of of your drug of choice, they we need to make sure that the that the drugs are doing what they're supposed to be doing. So they need to be that mode of action reflective again and inform us really whether they're going to be successful in the clinic because of the cost that it takes to produce these these new treatments. And then finally, when the these drugs are ready to be used in the clinic, we have to make sure that they can be produced at scale and that they can then be comparable between each of of the the batches that are produced. So through these lot relate release assays. So they have to be accurate, precise, sensitive, robust and reproducible. In the in the next part of our talk we're going to focus in on some cytotoxicity assays for AADC development. But before we go into the actual assays themselves, I just want to give a bit of a background and introduction to those that may not be familiar with antibody drug conjugates some their key design elements which are illustrated on the left side of this slide here. So really it's there are three key elements to it. So first of all, you have your, your map which allows for specific delivery of, you know, payload to the ancient expressing target cells. And then you have a chemical linker which ensures that the payload remains attached to the the map in general circulation, but ultimately allows it to be released into the payload inside the tumor cell. And then the final part of that free part compound is, is the payload itself. And as there's such a small proportion of administered agencies actually reach the, the tumor tissue, it's imperative that highly potent payloads are required to, to end us end us to achieve therapeutic efficacy. So turning to the schematic on the right of this slide here, it's just a nice illustration really and just the the the multiple step step mechanism action that is necessitates each specific requirements for the the component of the ADC. So if we look we look in at the antibody to bind to the receptor on the cell surface and then it gets internalized by a receptor mediated endocytosis and then endosymal lysosome fusion occurs resulting in the lysosomal degradation, the release of the the free drug and ultimately killing the cells. But once the free drug has been released, it's a good essential need to look monitor any effect on any neighboring cells, the so-called bystander effects which needs to be analyzed. And that's something my colleague Robert here is going to go into more detail as as we go through this presentation. But turning to the back to the antibody drug conjugate itself for this complex mode of action, we really need an optimal assay readout for this. And and we found that the the cell tighter globes system from pramiga meets our criteria. And so as Darren's already alluded to in terms of the the assay principle, it works by determining that number of viable cells in the culture based system on the quantitation of ATP present and luciferase reaction is direct leads to luminescence directly proportional to the amounts of. ATP in the we choose, we choose it because it's robust, reproducible and reliable and it's across many different applications. So in this, in this example that you see here in the early discovery phase where we're looking to select lead candidates from a larger ADC cohort, it's it's a great benchmark in I say for that. And in this example that we show here, it also shows it's adaptability to for automation and thus reduce use use of variability. And as I've previously alluded to, we choose this because it's robust and reaping. Hi there, everyone. It looks like we're having a little bit of technical issues with Abzina. They keep dropping out. So we're going to bear with them for a little bit and see if they come back. And if not, we'll scroll through their slides. I might talk through some of the notes and we'll see if they can join us. None. So. Are the differences in the clinical activity. So for Cyler they're not effective in heterogeneous tumours and in her two they are effective in heterogeneous tumours, for example, gastric cancer and metastatic breast cancer. And these characteristics are something to to bear in mind as we go through the case study. So the first asset that we present are that is that. The. The real time apoptosis and secondary necrosis I say, which Darren has gone into into great detail within his talk. So in in the case study that we present here, we've got running the the the consoler and her 2IN in parallel with her too high and her too low expressing cell lines. So a dual a dual readout as well. So early apoptosis detected by luminescence and then the secondary necrosis detected via fluorescence. And we're getting a readout using a plate reader accruing data every 60 minutes for 72 hours. So if I move now to the the results. So what you can see here is the the key differences in kinetics observed with the cut siler and in her two. So it's evident here it's an increase in apoptosis at earlier time points with the her 2 high cells noted and then apoptosis and secondary necrosis of the her 2 high cells increases over time with both the CAD siler and the her two. But you can see there are key differences that are are noteworthy between the two cell lines and between the two lead candidates as well. And it's evident the secondary necrosis of her 2 low cells increases over time with the CAD siler. That's something that we will come back to later in the talk as well. But ultimately the take home messages from here are that the real time glow, I say is a valuable tool to monitor kinetics and the mode of action of lead candidates, which is great. But moving forward, if we want to capture more information such as the proliferation rates, alongside this data, we also have a real time cytosdoxisity assessment, I say, which utilizes life cell imaging. So just a brief overview of the workflow here. We, we seed ourselves and we Co culture these with test compounds that in this case the Consilin and her two Co incubated with dyes to, to quantify apoptosis and necrosis Co culture for 96 hours. And then we've got a readout using fluorescence with a lifestyle imaging system. And I should iterate as well that this assay also has the capability of multiplexing of a cell Titiclo system. So if I move to the results now you can see here that's the in this example that I see here, you can see the cells are proliferating over time with the untreated cells and trusteuzumab incubated cells, whereas with the inheriting the Kadsila model cells are showing cytotoxic effects and reduced proliferation. So that's a great qualitative data that can be accrued using this, this assay. But also in parallel to that you get quantitative data as well. And what we we do is we utilize the the close otometry gating principle in order to monitor cells as they pass through early and late apoptosis in this example across across time. And that culminates in us being able to get quantifiable statistical data. So with that using that cell by cell analysis principle. And you can see see here that this kinetic assay shows a great deal more information and understanding as you acquire the data regarding your kinetics of your test molecule. And in this data set, you see here, the consoler is showing the strongest apoptotic and necrotic effect. So again, this is all well, good, but 2D is a great system. But ultimately cancer is a 3D disease and that's where we utilize the large assembly engine again with applying 3D spheroids. So in this workflow that we present here, we we transduce our cell line of interest with a fluorescent site sites like red dye and then seed them on ultra low attachment spheroid plates allow 72 hours for a spheroid formation which is illustrated in the the video here. And then after the 72 hours of spheroid formation, the compounds are then added and then Co incubated with the cells for a further 6 days. And then that culminates in in the results that you see here. And then so here you can see that the spheroids are yeah, the cervaroids are established from the her two cells are destroyed by both the and her two and Kurt Siler after 48 hours of treatment or higher concentrations. And then we know as with the 2D cell cultures, the Kurt Siler responses is more pronounced. So that's the the red line that you see on this, this graph here. And that ultimately results in the increased shrinking and loss of fluorescence of the spheroid. And you'll note as well that we've got the 3D site titer glow endpoint assessment here again, just illustrating the the capacity to be able to Multiplex this this assay. So to summarize, looking at these assays, overall Conceder looks like it should be the most effective therapy from the the in vitro data that we present here. But we do know that clinically in her two is the most effective treatment. So why is this? And ultimately it's due to the complexity of cancer. So yes, and this really is a challenge for us to produce in vitro assays that really reflect the complexity of cancer. So monocultures give us this good idea of how potent the ADC is in targeting the positive cell lines. However, the overall efficacy of the therapy is not just dictated by how effective it is at killing these target positive cell lines, but also the cells within these heterogeneous tumors that could potentially be causing extra harm during this disease. For example, the cancer stem cells really are, are a key cell population that we'll want to kill within a tumor to stop the kind of re re kind of growth of these tumors. So a clinically effective ATC that needs to kill both the target positive cells, but also the the potentially target negative cancer cells within the facility of of the target positive cells. And this is where we want to really assess this, which is the bystander effect. So bystander killing occurs when the drug from an ADC is released either from the target cell following internalisation and degradation of the ADC or release of the drug within the extracellular space. So the challenge really is how to replicate this effect in vitro. So we have the two methods here described that are commonly used, which is the supernatant transfer method from 1 monoculture to another. However, that doesn't really capture those like localized effects that could happen where the as the site is toxic drug becomes diluted within the supernatant. So where 2 cells together where one is dying and it's releasing that cytotoxic drug, it's very concentrated then to the cells surrounding it. And then also the flow cytometry method is another method that's used to assess the bystander effect. These are good endpoint assays, but they are very labour intensive and they are difficult to use to capture dynamics because you have to do multiple set time points. So our solution really is using the live cell imaging of cultures and this is the workflow that we use. So we we actually transduce the target positive and the target negative cells with fluorescent protein expression and they use lantivirus reagents to do this. Then we seed the cells together, we add the compounds Co incubation and then read out over time. So the bystander assays just to reiterate and not really Co culture, for example, the supernatural transfer or their endpoint like this atomic target negative cell line. But with our bystander assay, it's a real code culture, it's real time and it monitors the target positive and the target negative cell lines. So here is the the data that we are the qualitative microscopy data that we're able to obtain using this. So as I click through, you should be able to see the videos as they come up. So on the left hand side we have the, we have the, we have the untreated cells which are proliferating together. Then we have the trituzumab which just slightly prevents the the growth of the target positive cell line. So the red cell line is just the growth is slightly prevented with those while the green proliferates is normal, which is the target negative cell line. But with Kadcyla, you can hopefully see that you end up with the the red cells dying very quickly and then the green cells proliferate in fact, to take up that space while in her two is killing both the target positive cells and the target negative cells. And then this is the the graphical data that we can produce using this microscopy based assay where we can see the her 2 positive cells that they're dying. And in her two and CAD silo are quite similar, but CAD silo is the more effective as Grant showed in fact earlier. But in these her two negative cells, you can see really see that the in her two is killing those cells. But the CAD siler is has just allowed that space for the the target negative cells to proliferate. So we can conclude from this essay that in the two is producing a bystander effect in CAD, Siler is not. So even though Katzila appears to be most potent using the monoculture methods, NA2 is more effective at inducing this bystander effect. This is suggested in the literature why NA 2 is more effective at tackling cancer. And then by using in future assays, we do gain this clinically relevant mode of action data, which really helps in the early development program. And and this ultimately as we're trying to do with all these in vitro assays is reduce the need for as many animals as possible for preclinical testing. And then it's also, you know, cost wise as well, we want to reduce the amount of money is required to make a new therapy. So in vitro assays are both cheaper and quicker than in vivo. So the future of in vitro testing, so monoculture as I reiterate that the plate based assays are actually essential really in determining the in vitro potency of an ADC. They're still very much key testing in the early stage and for the late stage comparability studies and they are still the only acceptable way of testing in a good manufacturing practice environment. So when we do these batch to batch variation and monitor that when we produce these ADC's at scale as I say is still the only appropriate way of doing this. However, we need to understand an ADC. More complex approaches are required, the live cell time lapse experiments to understand the kinetics of the ADC including you know the pro meter assay that we saw earlier and the imaging assays as well. And they come together to abuse very good data on this and into two or more types together, including the immune cells in for example, in the 2D format. For example, this is this image on the right hand side here is ADCC of cancer cells by amine cells. So you can hopefully see the amine cells come in and killing the the target positive cells which are are in red. The 3D spheroid assays the ground showed in here now can be done routinely at scale. And these are getting closer especially to the solid tumor, what we'd expect to see a solid tumor to be like. And also then the next generation of these will be the Organon chip organoid tumoroid models, which will get us even closer to the in vivo. So currently, life cell imaging does provide the best way of understanding these complex and localized events. And this can be multiplexed with for example, the Prometer kits that we saw earlier. And actually it's kind of a further challenge is really trying to capture the complexity with with the multiple different cell types within a tumor. And then finally, I want to reiterate that really does offer these bioassay solutions for all of these. And we do like to work with organisations and companies developing these ADC's so that we can get them closer to the clinic. OK, thank you very much and thank you very much for listening to our talk today. So like to acknowledge these particular team members, but also the whole of the Bioassa team within Absina, Cambridge and the further support teams and the further other scientific teams as well. So yeah, let's move medicines forward together. Thank you very much for listening. Thank you for your time everyone and apologies for the technical issues earlier, but I hope you're able to get some use of information from the the presentation today. Brilliant. Thank you very much. I've seen that was a lovely presentation. We've got some questions from the audience. The first one was came in early in Darren's talk and it was where in the lucid phrase? Where is the lucid phrase in the Mt essay? Is it in the cell or is it in the media? Thanks. So with the Mt cell viability assay, actually I'm just going to go to this slide now, which we should be able to see. So with this with this assay, I'll skip on. So you have the so you have your cells, you have the nano luciferase pro substrate which is selling permeable. So both of these reagents sit in the media. So the pro substrate is cell permeable where nano luciferase isn't. So once once that pro substrate is diffused into the cell, reduced down for a redox reaction and diffuses out from the cell into the media, it then binds to that nano luciferase to generate luminescent signals so that reaction happens in the media. So I hope that answers your question. Thank you, Darren. Our next question is also for Darren. How do we know that the essay that's used for detecting cell viability is sufficient for picking up the viability signals of the cells that are located? They've said in the deeper side that I'm guessing you mean in the centre of the sphere of the sales for the 3D cell. Culture, OK, so with this assay, yes, it originally it was optimized for 2D, but then we've optimized it for 3D and we've looked at various sizes up to you know fairly fairly sizeable spheroids and we can see that yes, absolutely is getting into central S penetrating that and you're getting a a signal that is proportionately out above or so. So we've optimized that for fairly large steroids. Thank you. Questions for Abzena, in your 3D cell cultures, have you ever compared the real time aluminescent readout from Amiga with other assays? And how did you get on with time scales and sensitivities? So we've the, the, the main one that we have tested with Prometer in 3D is the 3D cell to anticlow. And we've found that it's been a very good benchmark. I say when we've been developing and optimizing the spheroid asteroids that you that we presented here. But we, we do, we, we, we strive for continuous improvement as well. And we're we're looking to adapt further assay such as the real time blow and then next in five assay into a 3D format as well. Brilliant. Thank you. We have another question. The assays for ADC sound wonderful. Do you have any specific or favorite method for the investigation of internalisation in order to choose the best antibody candidate to transform into ADC? Yeah. Sure. So yes Sir, we do have a very good assay that we do that we use for screening ADC's to make sure that they are getting into this lysosome, which is that that target organelle that that we need that the ADC must reach to then release the drug. And and we do that through the using APH sensitive dye and the and the flat 4 system from Sartorius. So yeah, for us that provides us the most sensitive way of doing these internalisation assays. OK. And one more question, I think another one for Abzina. Do you have 3D assays set up in your lab for batch release testing? And if so, do you do this and 2D or just do you do the 3D? Yeah, we. Currently we just do it at the the in the 2D format at the moment of a batch release. Yeah, yeah. So, so as I explained actually at the on that concluding slide in the 2D format that in the the monoculture 2D format is only really the acceptable way for GMP testing at the moment because it gives that consistent and reproducibility. So yeah, at the moment we would like to of course look towards 3D to to get closer to to say to the in vivo kind of environment. But yeah, for the moment, 2D only. And another question for Absina, how would you suggest measuring the rate of antibody internalisation? The rate of internalisation. So, so, yeah, we did, we do in fact take a look at the the internalization rate by analyzing the the kinetic curves of the data. And then that way then that can produce something that's kind of closer to the pharmacological kind of relevance that you would find say potentially in vivo. So we did, yeah. So say we analyzed really the kinetic curves. That we do get from our live cell imaging assets. Brilliant. Thank you. I don't think we've had any other questions come in. I'd like to apologize for the problems we've had with IT during some of this webinar, but thank you for bearing with us. If you do have any other questions, please pop them in and we can get back to you later. 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