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Panel discussion: ADC bioanalytics
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Panel discussion: ADC bioanalytics
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Language: EN.
Segment:0 .
Fantastic so Hello and welcome to our panel discussion on ADC bioanalytics as part of our spotlight in partnership with ICON. So before I introduce you to our speakers, I'd quickly like to cover a few housekeeping items for our audience. So you'll have the opportunity to submit written questions to today's panelists by typing your questions into the Q&A tab at the side of your window.
You may send in your questions at any time during the presentation, and we'll collect these and our speakers will address them at the end of the presentation. And then the last thing to note, please do let us know your thoughts on today's webinar by tweeting us at bioanalysis zone using the hashtag #BZ webinars.
So we're absolutely delighted to have some fantastic speakers joining us for today's discussion. So I'm going to let each of our speakers introduce themselves. And we'll start with you, Ashley. Hi, my name is Ashley Brandt. I'm the vice president for bioanalytical services at ICON, and I've been doing bioanalysis as my kids like to say since the 1900s. Hey good afternoon.
My name is Benno Engels. I'm currently heading the Department of bioanalytics and DMPK at Byondis. This is a Dutch biotech company involved in oncology. We have a strong focus on ADCs, and my department basically covers all the biomedical aspects of ADCs. So LCMS, LDA, immunogenicity in all phases of drug development. Yeah so I've worked at ADC therapeutics for just about 11 years now focusing on bioanalysis of antibody drug conjugates and obviously ADC therapeutics.
Our focus is antibody drug conjugates. So looking forward to the discussion today. Hi, I'm Rachel. I'm a senior scientist within Discovery science. Bioanalysis based in AstraZeneca. So we're within the clinical safety pharmacology department. So we handle the bioanalysis of all of the ADC therapeutics that come through the pipeline there.
Hi, I'm Violet. I'm a senior principal scientist within the biomedical sciences department at Genentech. And our group supports all the bioanalysis of ADCs and complex biotherapeutics. Perfect thank you to all five of our panelists for joining us today.
So I'm going to briefly go through the agenda before we jump into today's discussion. So over the course of this spotlight, we've looked into the key trends relating to ADCs, including the primary endpoints being monitored by our audience, the techniques currently in use, the Pa and ADA assays most commonly used, and some of the bioanalytical challenges associated with ADCs. Our audience communicated some of the strategies they believe will address some of the most significant challenges, as well as the ways in which ADC bioanalysis might evolve in the next five years.
All of the data presented today has been taken from our audience survey, which took place from January to March of 2025, and you can access a downloadable infographic that summarizes this data from our spotlight main page. So if you'd like to have a little look and deep dive in, dive deeper into that data. You're more than welcome to do so there. So in today's session, we're going to dissect some of that data we've collected and answer some of your live questions submitted by our audience.
So let's get into the data. So we asked our audience about the primary endpoints that they usually monitor. And they reported monitoring the conjugated ADC and the payload much more frequently than they monitored total antibody. Violet, let's come to you first. What endpoints do you measure in your work and what do you see as the benefits of doing so.
Yeah so this definitely highlights some of the complexities with ADCs where you've got the antibody portion, but then also the various drug to antibody conjugated moieties as well as the payloads that might become conjugated. And so actually outlined pretty succinctly and really nicely in some previous publications by Cardinale and Horvitz and all back in 2013, they actually outlined really well.
Some of the key analytes for PCA analysis and considerations, and the major ones consists of total antibody conjugated ADC or antibody conjugated drug. So it's really measuring either from the and how much payload is still remaining intact with the ADC. But then also there's the unconjugated drug or what comes off. Now one thing that I will say is it's also depending on the payload and what the potential metabolites could be, you may want to consider also monitoring those as well, especially if they are known to be active or have some potency that remains.
So that would be something that you would want to potentially track in terms of actually seeing the percentages being higher for what's called the conjugate ADC or what we also consider antibody conjugated drug and also the payload. I can see where that makes sense because these are the moieties that actually contain the active active pieces. And and also this somewhat hinges on whether your molecule is stable or not.
I think if your molecule actually has staple linkers, then you could actually see where only measuring two out of these three would actually give you the information that you would need for having an understanding of the pKa of the molecule. So in that sense, when you have a very stable ADC, your total antibody and your conjugate would end up mirroring each other pretty well, versus if you actually have a linker that would conjugate easily, then you would actually see a difference in the pq between the total antibody and the AC drug.
And then Additionally, I would say also as part of the analysis, we also look at the ADA. And in the clinic, we would actually do it in a tiered fashion where we actually look at screening first. And if it's positive, we would confirm titer and then characterize to better understand the domain specificity of the ADA as well. Fantastic thank you.
Violet and Charlie, let's come to you next. Going back to this data that we can see on the screen. Why, in your opinion, do you think that total antibody measurement is being monitored less frequently as the primary endpoint, or do you think. Yeah, it's a good question. I think as violet sort of alluded to, I mean, I think the conjugate assays, the one that shows you the most interesting data from a pharmacology perspective.
I mean, if you want to do modeling for your PK profile and things like that or activity, then that's the one that is of most use to clinical pharmacologist payload. I think that's probably more likely to be linked with a tox readout. So the total antibodies on its own is not really telling you a lot. You need to combine that with either the conjugate result or the free payload result to see if its conjugate.
And I think that's the main reason that's been used. And once you've determined that in later phases of development, it's probably not as useful to gain that information from every single trial. So that's probably why I would imagine that it's less commonly wanted. Great both. So we're now going to take a look at some of the techniques currently being used by our audience.
So here the data is split to show the techniques being used to assess the conjugated ADC versus total antibody. So conjugated in blue, total antibody in green. And the ligand binding ligand binding assays like Eliza and MSD were kind of the most used by our audience, and they were used equally as much for total antibody as well as conjugated ADC measurements. LCMS was also very commonly used, and 62% of our audience used it for that conjugated ADC quantification, but only 37 using it to assess total antibody.
So Ashley will come to you for this question. Why do you think lbas are potentially the preferred technique with our audience. And do you think this split is reflective of what you're seeing in the industry in general. Yeah so we are seeing a similar split, though we're seeing a little bit more popularity with quantitative LCMS.
And I think that a big part of that is probably some historical basis of looking at large molecules with LDA. But also by looking at them, because therefore you're seeing it typically for at least the antibody portion, you're seeing it based on its activity, which is considered to be more of the clinically relevant piece of that information or of that puzzle. And then Additionally, I think trying to come out with appropriate reagents, whether or not that stable label and the additional work that goes into identifying whether it's your peptide fingerprinting profile and then also getting a matched peptide internal standard, if you're going to do things by LCMS, it adds essentially an extra burden in order to do that, where typically for specificity and sensitivity, you'll still end up looking in an anti ID for either that antibody and/or the antibody conjugate.
Great thank you very much, Ashley. So 61% of our respondents are reporting seeing a shift in the use of lba to lc-ms Ms. technology for total antibody assessment. Benno why do you think. Why do you think this is. Why why are we seeing this shift potentially. Yeah I think it's also like what Ashley said in the, in the, in the past like maybe a decade ago.
So almost no one was using LC MS for, for proteins. So that's a general shift right, in protein analysis from lba moving a little bit more towards LCMS. In addition. But I think people even in the recent past or maybe even now, people would be a little bit reluctant to use LCMS more in the regulatory studies, like being afraid what type of guidelines to use. Maybe we get to talk about that a little bit later on as well.
So for that reason, it would be safe to stick with lba. But if you look at more agency specific reasons to go for LCMS, it's again, also what Ashley was referring to, like looking at quantification of total antibody and the conjugated antibody with lba. It's also in our experience total antibody assay can be sometimes like sensitive. So meaning that the response can be dependent on to antibody ratio.
And that's of course not desired. Right you want that total antibody assay to be not sensitive. So in that case, the LCMS can be a better choice. And of course, you want to have a sensitive assay for the mass spec. Sorry for the conjugated antibody assay for the conjugated payload assay. So for that, I guess in most cases, you end up having to use a mass spec assay.
We also do have some working assays, but it's always difficult to get these to be antibody rich. So sensitive. When you use a liquid binding assay. And then I think another advantage of using LC MS, and I think quite a lot of labs are doing so is you can go for multiplexing. So setting up assays to measure the total and the conjugated antibody in a single run.
And that's just making your data more robust and more efficient of course. And these are also the exact things that came up in the recent questionnaire from the European bioanalysis forum, for example, like looking at multiplexing and also the discussion on the categoryreagents. So I think that gives you a good summary.
You're on mute. Thank you. Ben Rachel, have you got anything to that you'd like to add. Yeah, I was going to echo some of those comments, especially the final one about being able to combine the antibody and ADC analysis from a single run, essentially. So that is a huge improvement in sample volume sustainability and sort of reducing the amount of analysis required.
If you're able to take a single aliquot forward. And then split it to get the different endpoints from a single sample. And I also think as ADCs are moving through generations and getting more complex, I think antibodies are as well. So even some protein therapeutics or just antibody based drugs are including sort of hybrids or chimeric forms, which may be too complex for some of the lba sort of capture and detection based assays available.
Whereas with LCMS, you can focus in on multiple peptides from various regions of the antibody. So heavy chain and light chain peptides and really gives you a more broader understanding of the antibody stability and sort of reduction or fallout of light chain and heavy chain fragments. Brilliant thank you Rachel. Thank you Benno.
So we'll move to our next topic. So often. Multiple pKa and ADA assays are requested by project teams or sponsors and pKa pKa assays to assess the free payload. Total antibody and conjugated antibody was the most frequently requested, at around 77% of our audience, requesting that immunogenicity assays against the ADC are also really frequently requested by our audience, at 71% So Ashley will come to you again for this one.
Can you talk us through some of these results and maybe comment on why some assays are being requested potentially more or less frequently, and maybe which of these assays, in your opinion, is are maybe the most important to be requesting. Absolutely so we see a similar within our shop of what's being requested. And I think it comes down to finding the most clinically relevant for especially late phase that drives these percentages.
But we are seeing more requests, especially in the early phase. Work to look at your drug antibody ratio. And metabolites, in particular with that of the linker, and making sure that we're understanding how stable that is and therefore what we'll be able to essentially model and expect into those late phase studies. So I think that each of those, especially as we go forward with more complex moieties and look at things with more complex analysis, such as high resolution mass spectrometry, I think it becomes more popular and more doable to look at some of those different determinations, and then they become more of a menu item and then therefore may end up becoming more popular in late phase again, as some of those payloads become more complex and some of those antibonding interactions and linkers become more complex.
Great thank you, Ashley and Rachel. What about, in your opinion, which would you say are some of the most important or do you agree, do you think maybe that potentially a combination is the best approach. Yeah, I tend to agree with Ashley. I think you have to really understand the impact of the data you're going to generate from each of the different approaches, and then where that impact of data is going to lead into understanding the study.
So I'm sort of broadening it out from PK studies. But there's also other sort of efficacy studies, PD studies or sort of more in vitro based modeling studies that could benefit from having some of the other endpoints than just a standard pKa sort of concentration. So I agree, I think if you've got complex ADCs and you want to understand stability, EBITDA is also important. And I think, Yeah, metabolites.
And specifically if you've got some sort of non-cleavable ADCs or some with more complex linkers, sometimes they're worth monitoring alongside your payload in the free fraction, just in case you've got some sort of incomplete deconjugation or a slower release of payload, that sort of would typically be ignored if it wasn't being monitored. Fantastic Thank you both.
So we'll now move on to looking at some of the challenges associated with ADC bioanalysis that were reported by our audience. And I'll give you a couple of minutes just to or a couple of seconds just to kind of have a little look at this, but you can see that ADC, ADC stability and sensitivity and detection limits were among the most suggested challenges by our audience. So violet, let's come to you first and then maybe Charlie can add afterwards.
But what do you kind of make of this list. And do you think there are any challenges that are missing. Yeah so actually seeing this list, some of these challenges actually resonates with our experiences. And I would say actually some of these challenges kind of go hand in hand. So if you take, for example, the need to drive sensitivity. So trying to hit lower limits of quantitation this often can be linked with the availability of your critical reagents.
So again, depending on the assay right. So you know you can go with a more generic assay. But then in that situation you might not be able to have the sensitivity that you might need for a specific ADC. And that's where having a critical reagent or a reagent that's actually intentionally developed for your molecule can actually help with that sensitivity any aspect.
And then along the lines of that, I would say, you know, the lack of standardization of methods, while I think generally what I've been seeing happening more is that there's generalization in the assay formats. So like for example, like with the total antibody, you'll see that there's actually many publications out now that talk about generic assays. And some of that can actually be, you know, helped to streamline a lot of the bioanalysis.
But ultimately, that will be molecule specific. And and really, I think the ability to adopt a standardized method is also somewhat going to be limited by the requirements to support your molecule, your study and what your clinical expected dosing regimens is and what your expected concentrations are going to be. And so that's actually going to help dictate your sensitivity.
For example. Yeah useful. Particularly if your ADC is quite stable. Because if you're not releasing much free warheads, it's not going to be a lot there to detect. So you need a very, very sensitive assay. Whereas if you have a very for conjugate for example, conjugate ADC, if you have a low potency warhead and a high dose, then you probably don't need a lot of sensitivity.
So it's much easier to hit that. So it knows exactly what you're trying to look for. Stability is quite an interesting topic, I think, for ADCs. I mean, it depends a lot on how you conjugate, of course, and the methodology and chemistry used there. But I mean, there are some schools of thought that suggest that a little bit of instability may not be a bad thing, that maybe a slow release of the drug may aid the efficacy.
I'm not saying that's necessarily a scientifically fully explored theory, but it's definitely one that is discussed. Yeah so there's definitely some interesting things about the stability. But I mean also you can get species specific instabilities. There are particular linkers in particular free warheads that are unstable, for example. So you always have that to consider.
And then if it's stable in the human then maybe that's not too much of a problem. It's just a developmental issue or hurdle you have to get over or consider. But I think. In terms of I did see a batch to batch variability in the ADCs, I presume. Again, this is probably something that's more likely to be seen in the early phases, very early phases, presumably for perhaps some of the more novel constructs, whereas the standard ADC perhaps sees that a little bit less.
But people are trying to go for more, you know, innovative techniques to make an ADC that's perhaps harder to reproduce, particularly in the early phases. Presumably once that's in the clinic, that's not really an issue anymore. But I think this is a reasonably good summary of the main challenges of ADCs, for sure. Great thank you Charlie. That was really, really informative.
We just missed the very first point that you said, if you just wouldn't mind repeating it, the rest was perfect. I have no idea what I said. I think it probably depends in part. What did I say. I think it depends in part on the methodology you use. So we tend to find Italy is quite sensitive method more so than Elisa, and we tend to have better access to that than LCMS as well.
But if you're looking for free warhead analysis, that obviously needs to be LCMS, and if you have a very stable ADC, then getting you need a very, very, very sensitive free warhead assay to detect anything at all. Otherwise, everything is just below the lower limit. That was exactly it. Thank you Charlie. Perfect fab. And then Rachel will come to you for this next one.
So we've talked a little bit there around sensitivity and detection limits being the most common challenge reported by our audience. Do you have any advice from your own experiences on overcoming that. Yeah, unfortunately, we were able to improve our sensitivity by moving to a newer mass spec system. So there is that the platforms are continuously being developed and improved on, which is helping with sensitivity and selectivity.
And I also think in my personal experience, I had to work around a lot of matrix effects, which were significantly impacting my peak analyte response. So by just sort of rather than doing one generic payload assay over and over again, we were able to improve on and make it more highly selective just by switching from a protein precipitation extraction to a solid phase extraction.
So by using a more selective method, we're able to reduce our lacz and therefore be able to report more applicable payload data from some complex samples. And I also to add to some of the stability points, I agree with Charlie. It's very complicated. I think the main issue is not stability in the samples. I think if you're using ADC reference materials for your sort of calibrator, calibrator and QC stocks, you want to be careful that they're stable upon storage and over analysis because you may lose or you may get various responses as you go over a study.
So it's the stability of the reference materials I think is as important as the samples. But Yeah, sort of just Yeah. By new mass spec and you'll get 10% more sensitivity. Thank you Rachel. Violet, do you have anything to add just before we go to ashley? Yeah, no, as we've been talking about some of the challenges associated.
One other thing that I was thinking about is, we see on here there's the challenges with heterogeneity. And again, depending on the assay and also the format that you use. And again, this is where it becomes linked also with the critical reagents. But you also have to think about whether there's a bias in for different ADCs moieties or the species. Right so like if you're actually doing a capture step like an immunoaffinity capture, you want to make sure that you're not preferentially capturing a DEA1 versus a, a fully loaded ADC as well, because then that can end up skewing your PK analysis as well.
So again, kind of piggybacking off of, you know, also the stability comment both Rachel and Charlie have mentioned because we know in vivo you know, we're trying to design ADCs that are stable. But in a, you know, at the same time, we know that they are de conjugating. And so we know that all these different moieties are present in vivo.
Thank you for that. And I have to really add in is some information that I found interesting, not only in our own hands, but also that was presented to me this year. And that was kind of the emphasis on going back to the basics. I think sometimes, especially when we're looking at some of these complex molecules and we're looking at more complex linkers, more complex payload, we tend to overlook some of the more basic chemistry, the pH of all of your reagents, the pH of your different buffers, making sure that you're monitoring some of those more simple yet can be very impactful aspects of your assay, as well as what you're storing in what you are bringing up samples in.
You know, we tend to overlook those as we think, Oh, well, we're just looking at things essentially like as it goes into the body, and we're getting this instantaneous snapshot when we pull it out of a patient. But unfortunately, that's really not the case. And we do a lot of manipulation outside xvivo that we have to really monitor and understand. So I think it really takes still time to, to really look at each of these molecules as, as the item that it is.
And then evaluate what and not overlook some of those more basic principles of what we do from a biochemistry or a straight chemistry aspect. Brilliant thank you to all of our panelists for chipping in to that question. So we'll now move on to our next slide, which is around some of the strategies to or technologies potentially, that our audience thought would help them overcome some of those other challenges within ADC bioanalysis.
So we've got a nice long list here. The numbers next to the first few relate to how many times our audience suggested that individually. So those improved detection methods, standardized standardized protocols, more robust linkers were being suggested very, very frequently. So firstly, let's come to you. How do you see some of these improvements taking shape potentially specifically on maybe some of those standardized protocols that have been mentioned.
Yeah so I guess to me standardized protocols would mean, I guess the generic methods that you would use for the determination of the total and, and can you get the antibody mainly in early phases of drug development. So in the preclinical space, I guess in most labs in preclinical space will use either ligand binding or an MS method focusing on under the humanized part of the tail of the antibody for the total antibody assay at least.
Right and these assays, they work really, really well. And of course, like I said before. Right a lot of people said before as well, the LDA assay in that sense can suffer from this sensitivity. So in that sense sometimes it cannot be a good assay. And the assay miss. So targeting this human tryptic peptide could be a better choice although being less sensitive.
But that sensitivity is often not a big issue in those early preclinical studies. And then I guess if you work with the same payload. So again, in early programs using the same payloads on different antibodies, for example, then it could be worthwhile to, to set up to generate an antibody against that payload. Or maybe one if you're lucky, right.
So with that payload antibody, you can also set up sort of generic methods to support that platform for that specific payload. We also use and I'm sure many labs use enzymatic assays to cleave off the payload like papain for example. This could also work fairly well in my view at least, where to set up generic methods for the conjugated antibody assay.
And then again, of course, the ligand binding assay for to setting up an anti payload antibody for using with that antiplatelet antibody. I'm sorry that's a little bit more difficult to develop, especially to make it in a sensitive way. But of course, it's more sensitive again. So it's always a trade off right. The outcomes may be more easy to set up the assay.
Say if you're looking for the. The reagents and but but LDA being more sensitive than the LCMS. Yeah brilliant. Thank you Ben and Ashley. Maybe looking at more of the improved kind of high Res mass spec instruments, where do you see some of that taking shape in future.
Yeah, I think currently we're using more high resolution mass spectrometry in order to do characterization and other steps. I think it would be fantastic if those platforms could be more holistically moved towards a regulatory space. That means that we can use them in later phase and to find, I guess, the ideal platform, which, each of them provides slightly different aspects, right?
If you're looking at a molecule using a linear ion trap, you're going to get different answers than you will if you're looking at it on a, for instance. So I think it's important to identify each of the advantages. But it would be great that each of those platforms also transition with us into the regulated bioanalytical space, which I think hasn't really occurred yet. We tend to still focus on the quantitative, triple quadrupole LCMS that we have right now.
So I think future state would be fantastic if we can start moving in that direction. Great thank you very much. So we're going to move on to our final slide, which is around the kind of emerging and future trends. So our audience reported a number of techniques or technologies that they'd be interested in exploring for ADCs bioanalysis. Ashley, we'll come to you again.
And then, Rachel, perhaps you can follow on. Why do you think again, following on from that high resolution mass spec, why do you think this was the most popular suggestion. And where are those benefits. What are some of those benefits that high resolution mass spec provides over other techniques. Yeah, I think the power is really in the amount of information that you can glean from high resolution mass specs.
So when you're looking at these large molecules, you can better understand what parts of the molecule you have that are still together, essentially like where the weakest link is, but also understanding where even the three dimensional folding and interaction may be and how that could be shifting in accordance to how it's being dosed. So there's so many different aspects of those questions that can be answered with high Res mass spec.
But I think we really just haven't figured out what that data and how we're reporting it and the bioanalytical space what that looks like for a submission. Right so if we're creating all of this data, what is an endpoint that's really clinically relevant that we want to prove. That either shows the safety or efficacy shifts that we're trying to prove.
So I think as we start to incorporate that and look at things in a more holistic fashion, I think that could shift both the need for that platform, but also the type of data that we're providing for a submission. Yeah, I agree, Ashley, and as I'm more in a discovery setting rather than further down the line like the rest of you, I'm definitely applying high Res mass spec methods more recently to some of the more complex ADCs.
So we're having some intact ADCs where we need to use high Res. And Additionally we've also got some interesting ADCs where we're not fully sure of what we're going to see in tissue and in tumor, just based on the ratio of linker cleavage or the time points required for that. So by doing high Res mass spec, we can see intact, partially cleaved and some of the cleaved antibodies.
So I think as Ashley was saying, you get so much more information. And I think kind of applying a proteomics approach, but specifically on your ADC target, will just give you better endpoints to then move on to a high throughput system. So you can take your Ms. through back to the triple quad to then do the targeted quantitation. So Yeah, I think high Res is you can get so much information from it, which can be overwhelming.
But if you know what you need and the impact, you can apply to some of these more complex ADCs, then, Yeah, it's sort of a beneficial piece that everyone can start to consider. Fantastic thank you Rachel. So moving on to the right hand side data. So when asked about how they anticipate ADC bioanalysis evolving in the next five years, the majority of our respondents, around 72% found or felt that improved standardization and regulatory alignment was very likely to occur, amongst a few other things.
Charlie will come to you for this one. 38% of our respondents suggested this kind of broader adoption of AI and machine learning for data interpretation. Can you provide maybe a little bit more insight on how AI or machine learning can be leveraged to facilitate the ADC development. Sure I think I mean, it's probably worth mentioning to begin with the FDA announcement last week of moving away from tox studies.
Animal based studies to AI and machine learning models, which is quite a shift from their usual their previous stance. But it's really nice to see. And I think I mean that kind of AI and machine learning modeling, it can go much further than just the pre-clinical modeling, modeling, the pKa and immunogenicity and things like that. The FDA referenced, I mean, I'm thinking more towards the project, project Optimus, where you have to look at multiple dosages in the clinic to really optimize the efficacy and the dosing in your clinical trials to make sure you're getting the appropriate dose for your product.
And I'm sure that there's the opportunity to use AI models to make that much more efficient, particularly with, I think, pricing pressures from various governments and everyone, you know, money's not limitless. So you don't want to spend more money than you need to develop a drug, which then makes you want to charge more later on. You know, more efficient.
You can be earlier on getting the data that you need to develop a drug that works well. I think anything that aids that would be advantageous and I is, is kind of prime for that really, I think probably a bit more smaller scale. I mean, anything, you know, that makes things more efficient in lab. So, you know, training your results or, you know, informing. Let's say.
Well, hang on, let me start that again. So informing the design of future molecules, for example on based on your current data. So looking at, you have one molecule that works very well in the pka is very good maybe. And then another which is not so good. You build that data set and that kind of can build an age your future molecules as well. And again, I mean, a lot of people reference things like method development and troubleshooting as well for AI models.
But also things like sustainability and efficiency. I mean, presumably I could aid there too in helping anything to do with, reducing wastage or removing steps or, you know, suggesting ways that we could be more sustainable in, in what we do in the lab. Yeah is that I think that's.
That's great. Charlie, thank you very much. So thank you to each of our speakers for helping us to dissect some of that data. Like I mentioned before, you're able to see that full data set in our spotlight main page. If you want to take another look at that. But we'll now begin the question and answer portion of today's session where our panelists will answer your questions.
So as a reminder, you're able to submit your questions using the question and answer tab at the side of your window. You're also able to direct your questions to a specific speaker or ask the whole panel, so feel free to do that. As you wish. Any questions that we don't have time for today. We will be addressing offline. So not to worry. If we do run out of time, then we're going to come to you for the very first question.
And this is around how we can deal with the guidelines for bioanalytical method development. So for lba we have different guidelines compared to LCMS. So our audience is kind of asking, do we use other validation criteria depending on the technology that we use, even if it's the same molecule. I wonder if you have an opinion on this. Yeah, sure.
Thanks this is always an interesting question. It's been a long discussion in the biomedical community in the last decade or so. It's like you said, it's kind of silly if you like, measure protein and normally you use an assay, you're allow to use it for 620 rule. And then you you're going to set up a PCA for that very same protein. And then you use LCMS, and all of a sudden you have to use for 615.
So that kind of doesn't make sense. Again, it's quite some discussion about that. I think most people would agree that also when you apply and maybe to add to that by the way. So of course for the ADCs using mass spec assays are more in scope, as we discussed in the past 45 minutes. So it becomes more of an issue. So what I was going to say, I think most people would agree to use for 620, just looking at that specific rule, about 15 versus 20 for 620 for the LCMS assays and for what I've heard also in our community.
There's been no regulatory pushback when using the 420 in a mass spec assay. So I would say that it should not be afraid to go for the 420. And of course, there are other considerations between the guidelines for lba versus LCMS. So related to the number of runs so three versus six or parallelism, the selectivity et cetera. So I would say and these come especially into play when you look at hybrid assays.
And many people use of course, these hybrid assays to do immune capture followed by LCMS. So is this an assay using mass spec detection or is it assay using capture method sample pretreatment. Again, there are no fixed guidelines for these type of assays. Which which is good right. So you can kind of make up your own essay using your, your scientific you're using your mind.
And I think if you use scientific arguments to set up a proper validation plan, you will get away with it by determining the proper guidelines there. And maybe that's a good kick off the discussion. Yeah, absolutely. We also do have another question for you bhanu. So when using LC MS, is it OK to use multiple minims to quantify the antibody or the ADC. And can you elaborate on potential rules when using multiple Mims.
Yeah, that's also an interesting question. The and I would be happy to hear other feedback on that subject as well from others. The but I would say certainly for the regulator studies, it would be safe to stick to a single MRM. Otherwise I think you'll get it into trouble. Double, but so people would certainly use and we had the arguments with in like 50 minutes ago like went to us.
So you can use HMMS and multiple moms or PRM. Right parallel reaction monitoring the orbitrap in your earlier studies. And for example you can use skyline. There's this, these algorithms like this p to look at different. Charges to determine the probability of you're actually looking at the right p curves or the right peptides.
So these type of algorithms when looking at multiple signals for single peptide I think can be very useful, but especially in earlier studies and not so much in the regulated studies. Great thank you very much, Ben. Ashley, we're going to come to you for this next question. So the question is around in free payload assays, should we be testing the feet so frozen for short term or LTS long term stability test.
So do we test at both ADC low and ADC high concentration for frozen for short term and long term stability tests. What's your opinions on that. I would argue that, yes, it's a best practice to do it both low and high. Again, when we're looking at large molecule analysis. I think you can see different behavior. And especially when you think about how you're analyzing those samples and whether or not you can end up with different aspects of folding or interaction, as well as, again, when you're in buffer versus in a, in a live sample, what can happen and how you are treating that.
So I think it's imperative to look at different concentrations and minimally at low and high when you're validating those assays, just because it really helps you to evaluate those different levels of interaction in real sample. And then as we mimic that to make sure that what we're seeing when we look at samples, that we're seeing something that's real and something that's as accurate as possible.
Fantastic thank you. Ashley and Charlie, do you have anything to add to this question. I am unable to hear Ashley at all, so I have no idea what she said, I'm afraid. But so can you repeat the question and I'll. Absolutely sure, if you want. No, the question was around in three payload assays. Should we be testing both ADC low and ADC high concentration for or Fleet Street and LTE stability test.
So that frozen thaw, short term and long term stability tests what your opinion would be on that. So I mean this is stability of the or interference from the ADC in the three wide assays. The way I interpret this question. So I would say if it doesn't interfere with the cmax concentration of the ADC, then there's no need to test anything else. If you start to get interference, you could probably determine at what level of your ADC concentration you do start to get interference in your free, but I wouldn't normally do it from the off from the start unless I felt there was a need.
Is that in any way similar to what actually. I know, I think that's good. Ashley, do you want to follow up with anything. No, I, I agree. I mean it's two it's different aspects of a similar question. We tend to be, I think, a little bit more conservative in wanting to look at things at both a low and high, given that at low concentrations, we can sometimes still see different interactions that we weren't expecting.
Thank you both. Rachel, we're going to come to you for this next question. So the question is around in what situation would naked antibody interference need to be evaluated for ADCs, and total antibody assays. Yeah, I think it does depend on your assay. But from personal experience. I have not seen interferences with in vivo plasma based matrices.
But when I've been analyzing some in vitro models. So again, the whole sustainability drive away from animals, there is now a bigger application for in vitro cell based or organoid. So sort of mini organ models to test your disease on before you move forward with the selection. But in these specific models there are additives and derivatives such as cytokines or some other proteins which we have seen cause an interference with our assay.
So we've seen it interfere with the capture antibody and therefore be carried forward as an interfering peak specifically for our antibody method. But because our assay you use the single sample to then do antibody and ADC measurement, and because the interference is missing from the ADC portion and because the interference is below 20% of our expected lock, it was deemed acceptable. But I think although the hybrid capture based ADC and antibody assays are being rolled out and are being well used.
I think it is worth considering that always there is that possible matrix effect, and that cross interference with the capture antibody from any other sort of proteins or peptides in the sample, while rare. We are starting to see more of it now that we're moving more into in vitro models where the sort of cytokines and other immunoglobulin proteins are being added to maintain the cells. So I have seen it.
Yeah but it's you're able to overcome it. Yeah fantastic. Thank you Rachel. Violet will come to you for this next one. So the question is to what extent is it better to evaluate in vivo da ratio apart from da established during CMC phase. Yeah so I would say where in our experience, we do a lot more of in vivo da analysis would be more earlier on.
So in more of the clinical studies where we're actually getting a better understanding of the molecules stability, while sometimes we will look, it is possible to still look at it in the clinical species. But if it really depends on what the question is that you're asking. And so we would look at it if, for example, you know, if there's potentially, you know, an efficacy question, like if you're not actually seeing that efficacy in the clinic, you may there could be some transformations that are occurring.
And when we say biotransformation, that could be quite broad, it could actually be that you're losing your payload. So due to instability you can actually have biotransformations occurring on the payload itself, which then renders it inactive potentially. But by and large. I would say when we're looking at in vivo da of actual study samples, that tends to be more in the non-clinical space.
And then Additionally, if you're actually trying to assess that stability piece, another way that you could also look at it is, in essence, a back of the envelope type of calculation. Because if you've actually got your total antibody pKa and also your conjugate measurement, you can do that calculation to get a sense of your stability. But we've also looked at da analysis, but more broadly, the biotransformation in clinical samples to have in some situations to actually have a better understanding about that.
Translatability going from a non-clinical to clinical phase as well. Thank you. So I'm afraid that's all we have time for. For today's live audience. So we'll address all of our other questions offline. So if you do still have any more questions for our panelists, then please do continue to submit them into that question and answer tab.
And we'll keep this open for a further few minutes just to allow everyone to submit them. So thank you very much to Ashley, Rachel, Charlie, Violet, and Benno for joining us for today's session and to everyone who watched and followed along in the audience. So you'll receive an email with how to watch this webinar on demand shortly if you want to come back and watch it. So do look out for that as well.
Don't forget to visit us at bioanalysiszone.com for more webinars. Thank you again for attending and we'll see you soon.
Segment:0 .
Fantastic so Hello and welcome to our panel discussion on ADC bioanalytics as part of our spotlight in partnership with ICON. So before I introduce you to our speakers, I'd quickly like to cover a few housekeeping items for our audience. So you'll have the opportunity to submit written questions to today's panelists by typing your questions into the Q&A tab at the side of your window.
You may send in your questions at any time during the presentation, and we'll collect these and our speakers will address them at the end of the presentation. And then the last thing to note, please do let us know your thoughts on today's webinar by tweeting us at bioanalysis zone using the hashtag #BZ webinars.
So we're absolutely delighted to have some fantastic speakers joining us for today's discussion. So I'm going to let each of our speakers introduce themselves. And we'll start with you, Ashley. Hi, my name is Ashley Brandt. I'm the vice president for bioanalytical services at ICON, and I've been doing bioanalysis as my kids like to say since the 1900s. Hey good afternoon.
My name is Benno Engels. I'm currently heading the Department of bioanalytics and DMPK at Byondis. This is a Dutch biotech company involved in oncology. We have a strong focus on ADCs, and my department basically covers all the biomedical aspects of ADCs. So LCMS, LDA, immunogenicity in all phases of drug development. Yeah so I've worked at ADC therapeutics for just about 11 years now focusing on bioanalysis of antibody drug conjugates and obviously ADC therapeutics.
Our focus is antibody drug conjugates. So looking forward to the discussion today. Hi, I'm Rachel. I'm a senior scientist within Discovery science. Bioanalysis based in AstraZeneca. So we're within the clinical safety pharmacology department. So we handle the bioanalysis of all of the ADC therapeutics that come through the pipeline there.
Hi, I'm Violet. I'm a senior principal scientist within the biomedical sciences department at Genentech. And our group supports all the bioanalysis of ADCs and complex biotherapeutics. Perfect thank you to all five of our panelists for joining us today.
So I'm going to briefly go through the agenda before we jump into today's discussion. So over the course of this spotlight, we've looked into the key trends relating to ADCs, including the primary endpoints being monitored by our audience, the techniques currently in use, the Pa and ADA assays most commonly used, and some of the bioanalytical challenges associated with ADCs. Our audience communicated some of the strategies they believe will address some of the most significant challenges, as well as the ways in which ADC bioanalysis might evolve in the next five years.
All of the data presented today has been taken from our audience survey, which took place from January to March of 2025, and you can access a downloadable infographic that summarizes this data from our spotlight main page. So if you'd like to have a little look and deep dive in, dive deeper into that data. You're more than welcome to do so there. So in today's session, we're going to dissect some of that data we've collected and answer some of your live questions submitted by our audience.
So let's get into the data. So we asked our audience about the primary endpoints that they usually monitor. And they reported monitoring the conjugated ADC and the payload much more frequently than they monitored total antibody. Violet, let's come to you first. What endpoints do you measure in your work and what do you see as the benefits of doing so.
Yeah so this definitely highlights some of the complexities with ADCs where you've got the antibody portion, but then also the various drug to antibody conjugated moieties as well as the payloads that might become conjugated. And so actually outlined pretty succinctly and really nicely in some previous publications by Cardinale and Horvitz and all back in 2013, they actually outlined really well.
Some of the key analytes for PCA analysis and considerations, and the major ones consists of total antibody conjugated ADC or antibody conjugated drug. So it's really measuring either from the and how much payload is still remaining intact with the ADC. But then also there's the unconjugated drug or what comes off. Now one thing that I will say is it's also depending on the payload and what the potential metabolites could be, you may want to consider also monitoring those as well, especially if they are known to be active or have some potency that remains.
So that would be something that you would want to potentially track in terms of actually seeing the percentages being higher for what's called the conjugate ADC or what we also consider antibody conjugated drug and also the payload. I can see where that makes sense because these are the moieties that actually contain the active active pieces. And and also this somewhat hinges on whether your molecule is stable or not.
I think if your molecule actually has staple linkers, then you could actually see where only measuring two out of these three would actually give you the information that you would need for having an understanding of the pKa of the molecule. So in that sense, when you have a very stable ADC, your total antibody and your conjugate would end up mirroring each other pretty well, versus if you actually have a linker that would conjugate easily, then you would actually see a difference in the pq between the total antibody and the AC drug.
And then Additionally, I would say also as part of the analysis, we also look at the ADA. And in the clinic, we would actually do it in a tiered fashion where we actually look at screening first. And if it's positive, we would confirm titer and then characterize to better understand the domain specificity of the ADA as well. Fantastic thank you.
Violet and Charlie, let's come to you next. Going back to this data that we can see on the screen. Why, in your opinion, do you think that total antibody measurement is being monitored less frequently as the primary endpoint, or do you think. Yeah, it's a good question. I think as violet sort of alluded to, I mean, I think the conjugate assays, the one that shows you the most interesting data from a pharmacology perspective.
I mean, if you want to do modeling for your PK profile and things like that or activity, then that's the one that is of most use to clinical pharmacologist payload. I think that's probably more likely to be linked with a tox readout. So the total antibodies on its own is not really telling you a lot. You need to combine that with either the conjugate result or the free payload result to see if its conjugate.
And I think that's the main reason that's been used. And once you've determined that in later phases of development, it's probably not as useful to gain that information from every single trial. So that's probably why I would imagine that it's less commonly wanted. Great both. So we're now going to take a look at some of the techniques currently being used by our audience.
So here the data is split to show the techniques being used to assess the conjugated ADC versus total antibody. So conjugated in blue, total antibody in green. And the ligand binding ligand binding assays like Eliza and MSD were kind of the most used by our audience, and they were used equally as much for total antibody as well as conjugated ADC measurements. LCMS was also very commonly used, and 62% of our audience used it for that conjugated ADC quantification, but only 37 using it to assess total antibody.
So Ashley will come to you for this question. Why do you think lbas are potentially the preferred technique with our audience. And do you think this split is reflective of what you're seeing in the industry in general. Yeah so we are seeing a similar split, though we're seeing a little bit more popularity with quantitative LCMS.
And I think that a big part of that is probably some historical basis of looking at large molecules with LDA. But also by looking at them, because therefore you're seeing it typically for at least the antibody portion, you're seeing it based on its activity, which is considered to be more of the clinically relevant piece of that information or of that puzzle. And then Additionally, I think trying to come out with appropriate reagents, whether or not that stable label and the additional work that goes into identifying whether it's your peptide fingerprinting profile and then also getting a matched peptide internal standard, if you're going to do things by LCMS, it adds essentially an extra burden in order to do that, where typically for specificity and sensitivity, you'll still end up looking in an anti ID for either that antibody and/or the antibody conjugate.
Great thank you very much, Ashley. So 61% of our respondents are reporting seeing a shift in the use of lba to lc-ms Ms. technology for total antibody assessment. Benno why do you think. Why do you think this is. Why why are we seeing this shift potentially. Yeah I think it's also like what Ashley said in the, in the, in the past like maybe a decade ago.
So almost no one was using LC MS for, for proteins. So that's a general shift right, in protein analysis from lba moving a little bit more towards LCMS. In addition. But I think people even in the recent past or maybe even now, people would be a little bit reluctant to use LCMS more in the regulatory studies, like being afraid what type of guidelines to use. Maybe we get to talk about that a little bit later on as well.
So for that reason, it would be safe to stick with lba. But if you look at more agency specific reasons to go for LCMS, it's again, also what Ashley was referring to, like looking at quantification of total antibody and the conjugated antibody with lba. It's also in our experience total antibody assay can be sometimes like sensitive. So meaning that the response can be dependent on to antibody ratio.
And that's of course not desired. Right you want that total antibody assay to be not sensitive. So in that case, the LCMS can be a better choice. And of course, you want to have a sensitive assay for the mass spec. Sorry for the conjugated antibody assay for the conjugated payload assay. So for that, I guess in most cases, you end up having to use a mass spec assay.
We also do have some working assays, but it's always difficult to get these to be antibody rich. So sensitive. When you use a liquid binding assay. And then I think another advantage of using LC MS, and I think quite a lot of labs are doing so is you can go for multiplexing. So setting up assays to measure the total and the conjugated antibody in a single run.
And that's just making your data more robust and more efficient of course. And these are also the exact things that came up in the recent questionnaire from the European bioanalysis forum, for example, like looking at multiplexing and also the discussion on the categoryreagents. So I think that gives you a good summary.
You're on mute. Thank you. Ben Rachel, have you got anything to that you'd like to add. Yeah, I was going to echo some of those comments, especially the final one about being able to combine the antibody and ADC analysis from a single run, essentially. So that is a huge improvement in sample volume sustainability and sort of reducing the amount of analysis required.
If you're able to take a single aliquot forward. And then split it to get the different endpoints from a single sample. And I also think as ADCs are moving through generations and getting more complex, I think antibodies are as well. So even some protein therapeutics or just antibody based drugs are including sort of hybrids or chimeric forms, which may be too complex for some of the lba sort of capture and detection based assays available.
Whereas with LCMS, you can focus in on multiple peptides from various regions of the antibody. So heavy chain and light chain peptides and really gives you a more broader understanding of the antibody stability and sort of reduction or fallout of light chain and heavy chain fragments. Brilliant thank you Rachel. Thank you Benno.
So we'll move to our next topic. So often. Multiple pKa and ADA assays are requested by project teams or sponsors and pKa pKa assays to assess the free payload. Total antibody and conjugated antibody was the most frequently requested, at around 77% of our audience, requesting that immunogenicity assays against the ADC are also really frequently requested by our audience, at 71% So Ashley will come to you again for this one.
Can you talk us through some of these results and maybe comment on why some assays are being requested potentially more or less frequently, and maybe which of these assays, in your opinion, is are maybe the most important to be requesting. Absolutely so we see a similar within our shop of what's being requested. And I think it comes down to finding the most clinically relevant for especially late phase that drives these percentages.
But we are seeing more requests, especially in the early phase. Work to look at your drug antibody ratio. And metabolites, in particular with that of the linker, and making sure that we're understanding how stable that is and therefore what we'll be able to essentially model and expect into those late phase studies. So I think that each of those, especially as we go forward with more complex moieties and look at things with more complex analysis, such as high resolution mass spectrometry, I think it becomes more popular and more doable to look at some of those different determinations, and then they become more of a menu item and then therefore may end up becoming more popular in late phase again, as some of those payloads become more complex and some of those antibonding interactions and linkers become more complex.
Great thank you, Ashley and Rachel. What about, in your opinion, which would you say are some of the most important or do you agree, do you think maybe that potentially a combination is the best approach. Yeah, I tend to agree with Ashley. I think you have to really understand the impact of the data you're going to generate from each of the different approaches, and then where that impact of data is going to lead into understanding the study.
So I'm sort of broadening it out from PK studies. But there's also other sort of efficacy studies, PD studies or sort of more in vitro based modeling studies that could benefit from having some of the other endpoints than just a standard pKa sort of concentration. So I agree, I think if you've got complex ADCs and you want to understand stability, EBITDA is also important. And I think, Yeah, metabolites.
And specifically if you've got some sort of non-cleavable ADCs or some with more complex linkers, sometimes they're worth monitoring alongside your payload in the free fraction, just in case you've got some sort of incomplete deconjugation or a slower release of payload, that sort of would typically be ignored if it wasn't being monitored. Fantastic Thank you both.
So we'll now move on to looking at some of the challenges associated with ADC bioanalysis that were reported by our audience. And I'll give you a couple of minutes just to or a couple of seconds just to kind of have a little look at this, but you can see that ADC, ADC stability and sensitivity and detection limits were among the most suggested challenges by our audience. So violet, let's come to you first and then maybe Charlie can add afterwards.
But what do you kind of make of this list. And do you think there are any challenges that are missing. Yeah so actually seeing this list, some of these challenges actually resonates with our experiences. And I would say actually some of these challenges kind of go hand in hand. So if you take, for example, the need to drive sensitivity. So trying to hit lower limits of quantitation this often can be linked with the availability of your critical reagents.
So again, depending on the assay right. So you know you can go with a more generic assay. But then in that situation you might not be able to have the sensitivity that you might need for a specific ADC. And that's where having a critical reagent or a reagent that's actually intentionally developed for your molecule can actually help with that sensitivity any aspect.
And then along the lines of that, I would say, you know, the lack of standardization of methods, while I think generally what I've been seeing happening more is that there's generalization in the assay formats. So like for example, like with the total antibody, you'll see that there's actually many publications out now that talk about generic assays. And some of that can actually be, you know, helped to streamline a lot of the bioanalysis.
But ultimately, that will be molecule specific. And and really, I think the ability to adopt a standardized method is also somewhat going to be limited by the requirements to support your molecule, your study and what your clinical expected dosing regimens is and what your expected concentrations are going to be. And so that's actually going to help dictate your sensitivity.
For example. Yeah useful. Particularly if your ADC is quite stable. Because if you're not releasing much free warheads, it's not going to be a lot there to detect. So you need a very, very sensitive assay. Whereas if you have a very for conjugate for example, conjugate ADC, if you have a low potency warhead and a high dose, then you probably don't need a lot of sensitivity.
So it's much easier to hit that. So it knows exactly what you're trying to look for. Stability is quite an interesting topic, I think, for ADCs. I mean, it depends a lot on how you conjugate, of course, and the methodology and chemistry used there. But I mean, there are some schools of thought that suggest that a little bit of instability may not be a bad thing, that maybe a slow release of the drug may aid the efficacy.
I'm not saying that's necessarily a scientifically fully explored theory, but it's definitely one that is discussed. Yeah so there's definitely some interesting things about the stability. But I mean also you can get species specific instabilities. There are particular linkers in particular free warheads that are unstable, for example. So you always have that to consider.
And then if it's stable in the human then maybe that's not too much of a problem. It's just a developmental issue or hurdle you have to get over or consider. But I think. In terms of I did see a batch to batch variability in the ADCs, I presume. Again, this is probably something that's more likely to be seen in the early phases, very early phases, presumably for perhaps some of the more novel constructs, whereas the standard ADC perhaps sees that a little bit less.
But people are trying to go for more, you know, innovative techniques to make an ADC that's perhaps harder to reproduce, particularly in the early phases. Presumably once that's in the clinic, that's not really an issue anymore. But I think this is a reasonably good summary of the main challenges of ADCs, for sure. Great thank you Charlie. That was really, really informative.
We just missed the very first point that you said, if you just wouldn't mind repeating it, the rest was perfect. I have no idea what I said. I think it probably depends in part. What did I say. I think it depends in part on the methodology you use. So we tend to find Italy is quite sensitive method more so than Elisa, and we tend to have better access to that than LCMS as well.
But if you're looking for free warhead analysis, that obviously needs to be LCMS, and if you have a very stable ADC, then getting you need a very, very, very sensitive free warhead assay to detect anything at all. Otherwise, everything is just below the lower limit. That was exactly it. Thank you Charlie. Perfect fab. And then Rachel will come to you for this next one.
So we've talked a little bit there around sensitivity and detection limits being the most common challenge reported by our audience. Do you have any advice from your own experiences on overcoming that. Yeah, unfortunately, we were able to improve our sensitivity by moving to a newer mass spec system. So there is that the platforms are continuously being developed and improved on, which is helping with sensitivity and selectivity.
And I also think in my personal experience, I had to work around a lot of matrix effects, which were significantly impacting my peak analyte response. So by just sort of rather than doing one generic payload assay over and over again, we were able to improve on and make it more highly selective just by switching from a protein precipitation extraction to a solid phase extraction.
So by using a more selective method, we're able to reduce our lacz and therefore be able to report more applicable payload data from some complex samples. And I also to add to some of the stability points, I agree with Charlie. It's very complicated. I think the main issue is not stability in the samples. I think if you're using ADC reference materials for your sort of calibrator, calibrator and QC stocks, you want to be careful that they're stable upon storage and over analysis because you may lose or you may get various responses as you go over a study.
So it's the stability of the reference materials I think is as important as the samples. But Yeah, sort of just Yeah. By new mass spec and you'll get 10% more sensitivity. Thank you Rachel. Violet, do you have anything to add just before we go to ashley? Yeah, no, as we've been talking about some of the challenges associated.
One other thing that I was thinking about is, we see on here there's the challenges with heterogeneity. And again, depending on the assay and also the format that you use. And again, this is where it becomes linked also with the critical reagents. But you also have to think about whether there's a bias in for different ADCs moieties or the species. Right so like if you're actually doing a capture step like an immunoaffinity capture, you want to make sure that you're not preferentially capturing a DEA1 versus a, a fully loaded ADC as well, because then that can end up skewing your PK analysis as well.
So again, kind of piggybacking off of, you know, also the stability comment both Rachel and Charlie have mentioned because we know in vivo you know, we're trying to design ADCs that are stable. But in a, you know, at the same time, we know that they are de conjugating. And so we know that all these different moieties are present in vivo.
Thank you for that. And I have to really add in is some information that I found interesting, not only in our own hands, but also that was presented to me this year. And that was kind of the emphasis on going back to the basics. I think sometimes, especially when we're looking at some of these complex molecules and we're looking at more complex linkers, more complex payload, we tend to overlook some of the more basic chemistry, the pH of all of your reagents, the pH of your different buffers, making sure that you're monitoring some of those more simple yet can be very impactful aspects of your assay, as well as what you're storing in what you are bringing up samples in.
You know, we tend to overlook those as we think, Oh, well, we're just looking at things essentially like as it goes into the body, and we're getting this instantaneous snapshot when we pull it out of a patient. But unfortunately, that's really not the case. And we do a lot of manipulation outside xvivo that we have to really monitor and understand. So I think it really takes still time to, to really look at each of these molecules as, as the item that it is.
And then evaluate what and not overlook some of those more basic principles of what we do from a biochemistry or a straight chemistry aspect. Brilliant thank you to all of our panelists for chipping in to that question. So we'll now move on to our next slide, which is around some of the strategies to or technologies potentially, that our audience thought would help them overcome some of those other challenges within ADC bioanalysis.
So we've got a nice long list here. The numbers next to the first few relate to how many times our audience suggested that individually. So those improved detection methods, standardized standardized protocols, more robust linkers were being suggested very, very frequently. So firstly, let's come to you. How do you see some of these improvements taking shape potentially specifically on maybe some of those standardized protocols that have been mentioned.
Yeah so I guess to me standardized protocols would mean, I guess the generic methods that you would use for the determination of the total and, and can you get the antibody mainly in early phases of drug development. So in the preclinical space, I guess in most labs in preclinical space will use either ligand binding or an MS method focusing on under the humanized part of the tail of the antibody for the total antibody assay at least.
Right and these assays, they work really, really well. And of course, like I said before. Right a lot of people said before as well, the LDA assay in that sense can suffer from this sensitivity. So in that sense sometimes it cannot be a good assay. And the assay miss. So targeting this human tryptic peptide could be a better choice although being less sensitive.
But that sensitivity is often not a big issue in those early preclinical studies. And then I guess if you work with the same payload. So again, in early programs using the same payloads on different antibodies, for example, then it could be worthwhile to, to set up to generate an antibody against that payload. Or maybe one if you're lucky, right.
So with that payload antibody, you can also set up sort of generic methods to support that platform for that specific payload. We also use and I'm sure many labs use enzymatic assays to cleave off the payload like papain for example. This could also work fairly well in my view at least, where to set up generic methods for the conjugated antibody assay.
And then again, of course, the ligand binding assay for to setting up an anti payload antibody for using with that antiplatelet antibody. I'm sorry that's a little bit more difficult to develop, especially to make it in a sensitive way. But of course, it's more sensitive again. So it's always a trade off right. The outcomes may be more easy to set up the assay.
Say if you're looking for the. The reagents and but but LDA being more sensitive than the LCMS. Yeah brilliant. Thank you Ben and Ashley. Maybe looking at more of the improved kind of high Res mass spec instruments, where do you see some of that taking shape in future.
Yeah, I think currently we're using more high resolution mass spectrometry in order to do characterization and other steps. I think it would be fantastic if those platforms could be more holistically moved towards a regulatory space. That means that we can use them in later phase and to find, I guess, the ideal platform, which, each of them provides slightly different aspects, right?
If you're looking at a molecule using a linear ion trap, you're going to get different answers than you will if you're looking at it on a, for instance. So I think it's important to identify each of the advantages. But it would be great that each of those platforms also transition with us into the regulated bioanalytical space, which I think hasn't really occurred yet. We tend to still focus on the quantitative, triple quadrupole LCMS that we have right now.
So I think future state would be fantastic if we can start moving in that direction. Great thank you very much. So we're going to move on to our final slide, which is around the kind of emerging and future trends. So our audience reported a number of techniques or technologies that they'd be interested in exploring for ADCs bioanalysis. Ashley, we'll come to you again.
And then, Rachel, perhaps you can follow on. Why do you think again, following on from that high resolution mass spec, why do you think this was the most popular suggestion. And where are those benefits. What are some of those benefits that high resolution mass spec provides over other techniques. Yeah, I think the power is really in the amount of information that you can glean from high resolution mass specs.
So when you're looking at these large molecules, you can better understand what parts of the molecule you have that are still together, essentially like where the weakest link is, but also understanding where even the three dimensional folding and interaction may be and how that could be shifting in accordance to how it's being dosed. So there's so many different aspects of those questions that can be answered with high Res mass spec.
But I think we really just haven't figured out what that data and how we're reporting it and the bioanalytical space what that looks like for a submission. Right so if we're creating all of this data, what is an endpoint that's really clinically relevant that we want to prove. That either shows the safety or efficacy shifts that we're trying to prove.
So I think as we start to incorporate that and look at things in a more holistic fashion, I think that could shift both the need for that platform, but also the type of data that we're providing for a submission. Yeah, I agree, Ashley, and as I'm more in a discovery setting rather than further down the line like the rest of you, I'm definitely applying high Res mass spec methods more recently to some of the more complex ADCs.
So we're having some intact ADCs where we need to use high Res. And Additionally we've also got some interesting ADCs where we're not fully sure of what we're going to see in tissue and in tumor, just based on the ratio of linker cleavage or the time points required for that. So by doing high Res mass spec, we can see intact, partially cleaved and some of the cleaved antibodies.
So I think as Ashley was saying, you get so much more information. And I think kind of applying a proteomics approach, but specifically on your ADC target, will just give you better endpoints to then move on to a high throughput system. So you can take your Ms. through back to the triple quad to then do the targeted quantitation. So Yeah, I think high Res is you can get so much information from it, which can be overwhelming.
But if you know what you need and the impact, you can apply to some of these more complex ADCs, then, Yeah, it's sort of a beneficial piece that everyone can start to consider. Fantastic thank you Rachel. So moving on to the right hand side data. So when asked about how they anticipate ADC bioanalysis evolving in the next five years, the majority of our respondents, around 72% found or felt that improved standardization and regulatory alignment was very likely to occur, amongst a few other things.
Charlie will come to you for this one. 38% of our respondents suggested this kind of broader adoption of AI and machine learning for data interpretation. Can you provide maybe a little bit more insight on how AI or machine learning can be leveraged to facilitate the ADC development. Sure I think I mean, it's probably worth mentioning to begin with the FDA announcement last week of moving away from tox studies.
Animal based studies to AI and machine learning models, which is quite a shift from their usual their previous stance. But it's really nice to see. And I think I mean that kind of AI and machine learning modeling, it can go much further than just the pre-clinical modeling, modeling, the pKa and immunogenicity and things like that. The FDA referenced, I mean, I'm thinking more towards the project, project Optimus, where you have to look at multiple dosages in the clinic to really optimize the efficacy and the dosing in your clinical trials to make sure you're getting the appropriate dose for your product.
And I'm sure that there's the opportunity to use AI models to make that much more efficient, particularly with, I think, pricing pressures from various governments and everyone, you know, money's not limitless. So you don't want to spend more money than you need to develop a drug, which then makes you want to charge more later on. You know, more efficient.
You can be earlier on getting the data that you need to develop a drug that works well. I think anything that aids that would be advantageous and I is, is kind of prime for that really, I think probably a bit more smaller scale. I mean, anything, you know, that makes things more efficient in lab. So, you know, training your results or, you know, informing. Let's say.
Well, hang on, let me start that again. So informing the design of future molecules, for example on based on your current data. So looking at, you have one molecule that works very well in the pka is very good maybe. And then another which is not so good. You build that data set and that kind of can build an age your future molecules as well. And again, I mean, a lot of people reference things like method development and troubleshooting as well for AI models.
But also things like sustainability and efficiency. I mean, presumably I could aid there too in helping anything to do with, reducing wastage or removing steps or, you know, suggesting ways that we could be more sustainable in, in what we do in the lab. Yeah is that I think that's.
That's great. Charlie, thank you very much. So thank you to each of our speakers for helping us to dissect some of that data. Like I mentioned before, you're able to see that full data set in our spotlight main page. If you want to take another look at that. But we'll now begin the question and answer portion of today's session where our panelists will answer your questions.
So as a reminder, you're able to submit your questions using the question and answer tab at the side of your window. You're also able to direct your questions to a specific speaker or ask the whole panel, so feel free to do that. As you wish. Any questions that we don't have time for today. We will be addressing offline. So not to worry. If we do run out of time, then we're going to come to you for the very first question.
And this is around how we can deal with the guidelines for bioanalytical method development. So for lba we have different guidelines compared to LCMS. So our audience is kind of asking, do we use other validation criteria depending on the technology that we use, even if it's the same molecule. I wonder if you have an opinion on this. Yeah, sure.
Thanks this is always an interesting question. It's been a long discussion in the biomedical community in the last decade or so. It's like you said, it's kind of silly if you like, measure protein and normally you use an assay, you're allow to use it for 620 rule. And then you you're going to set up a PCA for that very same protein. And then you use LCMS, and all of a sudden you have to use for 615.
So that kind of doesn't make sense. Again, it's quite some discussion about that. I think most people would agree that also when you apply and maybe to add to that by the way. So of course for the ADCs using mass spec assays are more in scope, as we discussed in the past 45 minutes. So it becomes more of an issue. So what I was going to say, I think most people would agree to use for 620, just looking at that specific rule, about 15 versus 20 for 620 for the LCMS assays and for what I've heard also in our community.
There's been no regulatory pushback when using the 420 in a mass spec assay. So I would say that it should not be afraid to go for the 420. And of course, there are other considerations between the guidelines for lba versus LCMS. So related to the number of runs so three versus six or parallelism, the selectivity et cetera. So I would say and these come especially into play when you look at hybrid assays.
And many people use of course, these hybrid assays to do immune capture followed by LCMS. So is this an assay using mass spec detection or is it assay using capture method sample pretreatment. Again, there are no fixed guidelines for these type of assays. Which which is good right. So you can kind of make up your own essay using your, your scientific you're using your mind.
And I think if you use scientific arguments to set up a proper validation plan, you will get away with it by determining the proper guidelines there. And maybe that's a good kick off the discussion. Yeah, absolutely. We also do have another question for you bhanu. So when using LC MS, is it OK to use multiple minims to quantify the antibody or the ADC. And can you elaborate on potential rules when using multiple Mims.
Yeah, that's also an interesting question. The and I would be happy to hear other feedback on that subject as well from others. The but I would say certainly for the regulator studies, it would be safe to stick to a single MRM. Otherwise I think you'll get it into trouble. Double, but so people would certainly use and we had the arguments with in like 50 minutes ago like went to us.
So you can use HMMS and multiple moms or PRM. Right parallel reaction monitoring the orbitrap in your earlier studies. And for example you can use skyline. There's this, these algorithms like this p to look at different. Charges to determine the probability of you're actually looking at the right p curves or the right peptides.
So these type of algorithms when looking at multiple signals for single peptide I think can be very useful, but especially in earlier studies and not so much in the regulated studies. Great thank you very much, Ben. Ashley, we're going to come to you for this next question. So the question is around in free payload assays, should we be testing the feet so frozen for short term or LTS long term stability test.
So do we test at both ADC low and ADC high concentration for frozen for short term and long term stability tests. What's your opinions on that. I would argue that, yes, it's a best practice to do it both low and high. Again, when we're looking at large molecule analysis. I think you can see different behavior. And especially when you think about how you're analyzing those samples and whether or not you can end up with different aspects of folding or interaction, as well as, again, when you're in buffer versus in a, in a live sample, what can happen and how you are treating that.
So I think it's imperative to look at different concentrations and minimally at low and high when you're validating those assays, just because it really helps you to evaluate those different levels of interaction in real sample. And then as we mimic that to make sure that what we're seeing when we look at samples, that we're seeing something that's real and something that's as accurate as possible.
Fantastic thank you. Ashley and Charlie, do you have anything to add to this question. I am unable to hear Ashley at all, so I have no idea what she said, I'm afraid. But so can you repeat the question and I'll. Absolutely sure, if you want. No, the question was around in three payload assays. Should we be testing both ADC low and ADC high concentration for or Fleet Street and LTE stability test.
So that frozen thaw, short term and long term stability tests what your opinion would be on that. So I mean this is stability of the or interference from the ADC in the three wide assays. The way I interpret this question. So I would say if it doesn't interfere with the cmax concentration of the ADC, then there's no need to test anything else. If you start to get interference, you could probably determine at what level of your ADC concentration you do start to get interference in your free, but I wouldn't normally do it from the off from the start unless I felt there was a need.
Is that in any way similar to what actually. I know, I think that's good. Ashley, do you want to follow up with anything. No, I, I agree. I mean it's two it's different aspects of a similar question. We tend to be, I think, a little bit more conservative in wanting to look at things at both a low and high, given that at low concentrations, we can sometimes still see different interactions that we weren't expecting.
Thank you both. Rachel, we're going to come to you for this next question. So the question is around in what situation would naked antibody interference need to be evaluated for ADCs, and total antibody assays. Yeah, I think it does depend on your assay. But from personal experience. I have not seen interferences with in vivo plasma based matrices.
But when I've been analyzing some in vitro models. So again, the whole sustainability drive away from animals, there is now a bigger application for in vitro cell based or organoid. So sort of mini organ models to test your disease on before you move forward with the selection. But in these specific models there are additives and derivatives such as cytokines or some other proteins which we have seen cause an interference with our assay.
So we've seen it interfere with the capture antibody and therefore be carried forward as an interfering peak specifically for our antibody method. But because our assay you use the single sample to then do antibody and ADC measurement, and because the interference is missing from the ADC portion and because the interference is below 20% of our expected lock, it was deemed acceptable. But I think although the hybrid capture based ADC and antibody assays are being rolled out and are being well used.
I think it is worth considering that always there is that possible matrix effect, and that cross interference with the capture antibody from any other sort of proteins or peptides in the sample, while rare. We are starting to see more of it now that we're moving more into in vitro models where the sort of cytokines and other immunoglobulin proteins are being added to maintain the cells. So I have seen it.
Yeah but it's you're able to overcome it. Yeah fantastic. Thank you Rachel. Violet will come to you for this next one. So the question is to what extent is it better to evaluate in vivo da ratio apart from da established during CMC phase. Yeah so I would say where in our experience, we do a lot more of in vivo da analysis would be more earlier on.
So in more of the clinical studies where we're actually getting a better understanding of the molecules stability, while sometimes we will look, it is possible to still look at it in the clinical species. But if it really depends on what the question is that you're asking. And so we would look at it if, for example, you know, if there's potentially, you know, an efficacy question, like if you're not actually seeing that efficacy in the clinic, you may there could be some transformations that are occurring.
And when we say biotransformation, that could be quite broad, it could actually be that you're losing your payload. So due to instability you can actually have biotransformations occurring on the payload itself, which then renders it inactive potentially. But by and large. I would say when we're looking at in vivo da of actual study samples, that tends to be more in the non-clinical space.
And then Additionally, if you're actually trying to assess that stability piece, another way that you could also look at it is, in essence, a back of the envelope type of calculation. Because if you've actually got your total antibody pKa and also your conjugate measurement, you can do that calculation to get a sense of your stability. But we've also looked at da analysis, but more broadly, the biotransformation in clinical samples to have in some situations to actually have a better understanding about that.
Translatability going from a non-clinical to clinical phase as well. Thank you. So I'm afraid that's all we have time for. For today's live audience. So we'll address all of our other questions offline. So if you do still have any more questions for our panelists, then please do continue to submit them into that question and answer tab.
And we'll keep this open for a further few minutes just to allow everyone to submit them. So thank you very much to Ashley, Rachel, Charlie, Violet, and Benno for joining us for today's session and to everyone who watched and followed along in the audience. So you'll receive an email with how to watch this webinar on demand shortly if you want to come back and watch it. So do look out for that as well.
Don't forget to visit us at bioanalysiszone.com for more webinars. Thank you again for attending and we'll see you soon.
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