The latest DDW Sitting Down With podcast features Bryan Jones, Senior Research Fellow, BioTechnology Discovery Research, Eli Lilly and Co and Dan Bedinger, Application Science Team Lead, Carterra.
Bamlanivimab was the first neutralizing monoclonal antibody to receive emergency use authorization from the FDA as a treatment for mild to moderate COVID-19 on 9 November 2020, 94 days after the monoclonal antibody discovery workflow began for the molecule. This achievement, says Eli Lilly, represents the shortest timeline from discovery to public usage for a monoclonal antibody to date. In February 2021, bamlanivimab administered with etesevimab received emergency use authorization for treatment of recently diagnosed, mild to moderate COVID-19 in patients who are high risk for progression to severe COVID-19.
Jones and Bedinger talk us through the Bamlanivimab story.
Tune in to find out how Eli Lilly strategized and built multiple collaborations enabling this COVID-19 therapeutic to reach patients in just over eight months, plus details of Carterra’s involvement in the process.
0:00:05.1 Speaker 1: Hello, and welcome to the DDW Podcast. This is the Sitting Down With Series, where we examine the people, the breakthroughs, and the innovation driving the drug discovery and development sector. I'm Lu Rahman, Editor In Chief, Drug Discovery World.
0:00:20.1 Speaker 1: Drug Discovery World is a multi-platform global voice for drug discovery and development community, from research stage to clinical trials, the brand covers the latest innovation and expertise in the sector. Above all, DDW readers learn how to turn science into business. Today's guests are Bryan Jones, Senior Research Fellow, Biotechnology Discovery Research, Eli Lilly and Co, and Dan Bedinger, Application Science Team Lead, Carterra. We'll be discussing the Bamlanivimab story, how one technology enabled this therapeutic to reach clinic in eight months during the pandemic. First, a little bit about Bryan and Dan.
0:00:55.8 S1: Bryan received his BS in Chemistry from the California State University and Doctorate in Chemistry from Pennsylvania State University in 1994. After post-doctoral fellowship at the University of Washington, he joined Eli Lilly and Co as a Senior Scientist in 1997. Bryan is currently a Senior Research Fellow at Lilly and the group leader for the Protein Biosciences Group located at the Lilly Biotechnology Center in San Diego.
0:01:22.3 S1: Dan started his career making and characterizing therapeutic monoclonal antibodies more than 20 years ago at Abgenix. Since then, he's continued to pursue the screening and characterization of monoclonal antibodies at a number of biotechnology companies and using a broad range of approaches, from biophysical binding using many platforms to cell-based functional assays and in vivo characterization. Dan earned a PhD from UC Davis in Cellular, Molecular, and Integrative Physiology while studying biological function of allosteric modulating antibodies to the insulin receptor. Thanks for joining us today, Dan and Bryan.
0:01:58.4 Speaker 2: Thanks for the invite.
0:02:00.7 S1: You're welcome. So I think if we just start with some background to this story. Bamlanivimab was the first neutralizing monoclonal antibody to receive emergency use authorization from the FDA as a treatment for mild to moderate COVID-19 on November the 9th, 2020, which was just 94 days after the monoclonal antibody discovery workflow began for the molecule. This achievement represents the shortest timeline from discovery to public usage for monoclonal antibody to date. And in February 2021, Bamlanivimab administered with Etesevimab received emergency use authorization for the treatment of recently diagnosed mild to moderate COVID-19 in patients who are high risk for progression to severe COVID-19. So Bryan, we'll start with you then. As the pandemic was unfolding in 2020, can you walk us through how Lilly started to strategize and build collaborations enabling this COVID-19 therapeutic to reach patients in just over eight months?
0:02:57.9 Speaker 2: Yeah, I can certainly try to explain. It was a complicated story. It had, actually, an unexpected beginning. We didn't expect to be involved. It wasn't certainly on our radar here. We had already been in discussions and plans with AbCellera, a collaborator in the discovery of Bamlanivimab, from an antibody discovery perspective. And I guess those discussions and the agreement that was put in place for that led AbCellera to ask us to partner with them on the development of an antibody. So that happened in early March. I think we met with them in person the very first time because some of the key individuals from AbCellera happened to be in San Diego. We actually met with them early March while they were in the process of screening the PBMC sample that they received from the Vaccine Research Center, which was is part of the NIAID, NIH here in the United States.
0:03:53.3 S2: That sort of kicked off the whole discovery and development process. You mentioned collaborations, obviously that was the first of the collaborations amongst many that enabled all of this to happen in such a short time frame. Interestingly enough, because we aren't an anti-viral company, we haven't done antiviral research in decades, we certainly didn't have the capabilities or facilities to really pursue this. So for instance, BSL-3 labs that deal with live virus neutralization, is a prime example. So that actually necessitated Lilly reaching out to a large number of academic institutions, labs, and contract research organizations to enable some of that characterization to make sure we could show them the antibody had a legitimate, whatever antibodies we happened to discover with the collaboration with AbCellera would in fact work.
0:04:45.3 S2: And so it was an amazing, I would say even within the company, a huge collaborative effort, right? Everybody was all hands on deck, everybody was singularly focused on making this happen and making it happen fast. And that was everywhere from the science side to the manufacturing side, to enabling these external agreements to work with collaborators. And if you look at the science translation on that paper, you can see the collaborations we had with Ralph Baric's lab at North Carolina, John Mulligan at NYU, across Geisbert labs at UTMB, for not only live virus characterization, but then some of the structural work that was enabled by Jason McLellan and UT Austin, and of course the collaborations with AbCellera and the Vaccine Research Center to make all this happen. So it was a huge collaborative effort, surprisingly, to make all of this happen so quickly.
0:05:38.3 S1: Okay. Thanks, Bryan. That is an impressive back story. Thank you for that. And can you provide some more detail on how large the original antibody panel was and what new technologies were utilized to validate, characterize, and pick the best neutralizing antibody candidates against COVID-19?
0:05:54.0 S2: Yeah, sure. So the original sample that came from a convalescent patient via the Vaccine Research Lab that AbCellera did a discovery on, they screened, I forget how many, I wanna say around three million cells from that PBMC sample. And their screening process is a fascinating story in and of itself to identify B cells that make antibodies that bind to a particular target. And through that screening process they identified roughly 2000 antibodies that were sequenced. And so that was the starting pool of antibodies from this one patient. Those antibodies were then subsequently narrowed down relatively quickly just based on sequence information and a number of computational assessments, both AbCellera's own computational tools as well as computational tools we use here at Lilly, to a more manageable number that we could actually make and characterize. So the initial pool was around 2000, we narrowed it to around 200, so 296 well placed worth of antibodies that we would actually clone and express.
0:06:57.6 S2: Both Lily and AbCellera clone and expressed these antibodies, and those antibodies got sent to different purposes. And that led us to take advantage of the Carterra LSA to help us really understand what the diversity of these antibodies looked like from an epitope space perspective, and also get an idea of how well they bind the target that we were interested in, in this case the spike protein of the SARS-CoV-2 virus, as well as more functional aspects such as Ace2 blocking. So understanding which antibodies potentially neutralize the interaction between the virus and the human receptor for the cell. And so that data led us to ultimately select 24, and through more of a standard biochemical screening and characterization those 24 were sent all over the country to the various labs we were collaborating with to be tested for their neutralization activity. We looked at a lot of properties here at Lilly that we typically do for all of our antibody discovery efforts to make sure that the antibodies that we would want to develop have the appropriate properties for development, so no issues that might be associated with poor pharmacokinetics or manufacturability issues. So all that kinda happened all in the span of a few weeks, but that was the number, give you a rough idea of the number that led ultimately to the selection of what was called antibody 555, which became Bamlanivimab.
0:08:17.8 S1: Okay, thanks, Bryan. So just coming to you now, Dan. Can you explain to the audience how epitope binning analysis speeds up drug discovery?
0:08:25.6 Speaker 3: Sure. So the LSA enables scientists to set up a parallelized competition assay for up to hundreds of clones using just a couple of micro-plates and small amounts of antibody, about 15 micrograms or less of each, and a modest amount of antigen. And then they can automate the testing of many thousands of parallelized competition interactions, and this allows them to get a really high-resolution competition-based epitope-binning profile on a whole panel of antibodies. In this type of analysis, you can include up to about 384 clones off of a single array, a single analysis, and generate a matrix up to 147,000 parallelized interaction analysis. And even a more modest set, which is probably more typically run, would be like a 96 by 96 sample matrix, and that will generate over 9000 parallelized interactions. So this scale is not really readily achievable on other platforms and can really provide a very rich picture of the complex competition profiles created by diverse antibody panels.
0:09:37.6 Speaker 3: So when you apply epitope binning at this scale, this approach can really reveal small differences in contacts between antibodies and antigens representing as few, just a couple of amino acids shift in the binding domain. So it's usually important that new monoclonal antibody discovery efforts begin with a diverse array of candidates and the goal was typically to include a diverse set of sequences and mechanism of actions for evaluation in key downstream assays like virulant activation studies in this case. So, since sequence diversity alone doesn't really necessarily guarantee epitopic or functional diversity, the ability to perform high through epitope binning early in the screening process, can really provide a verification that there is both broad epitopic and functional diversity within a panel of maps.
0:10:30.7 S3: So when you perform high resolution epitopic binning, you can get enough detail to allow the scientists involved to select clones or group clones into functional classes and really guide the selection to ensure that they carry a lot of diversity forward into the funnel. So a low resolution epitope binning assay would really not allow for this type of detailed and nuanced epitope clustering, and therefore really has minimal impact on discovery funnel and was really applied as a late stage characterization. So if a binning experiment is socially detailed, you can really have confidence that clones are behaving the same way and that they should share other properties, or at least that the clones that you're carrying forward into your funnel are clearly differentiated from each other.
0:11:23.2 S3: So this can be particularly relevant in the development of antibody cocktails, where binning data will clearly demonstrate which clones can co-occupy the target protein and have a high probability of synergy and competition. So as Denisa Foster presented in the recent webinar with Nature, Lilly was able to run kinetics and binning assays and Base 2 competition profiles for all two plates of 187 clones, I think they reported, antibodies in just a few days. So this data was then transferred to AbCellera's bioinformatics platform along with various other factors that they knew about the antibodies at the time, and allowed them to select that smaller subset to bring forward in the funnel.
0:12:10.3 S1: Okay, yeah, thank you for the insight Dan, that was really interesting. So Bryan, just coming back to you then, Lilly is continuing to play a leading role in discovery and development as the pandemic continues around the world and as many more COVID-19 variants emerge, can you discuss any new developments in therapies.
0:12:26.7 S2: Sure, so after we were able to clinically study and then also ultimately achieve emergency use for both Bamlanivimab and then the antibody we partnered with, Jhansi at a seven mob, we really didn't stop. We continued to pursue antibody discovery, and the reason is we knew variants would arise, this is a virus and this is what viruses do, so we continued to partner with AbCellera on further discovery efforts. And so this took on a number of activities, the first of which was just continuing to screen additional patient samples for antibodies, the idea was to look for unique antibodies with respect to say, epitope diversity, unique function, etcetera. So for instance, we altered the screening paradigm for which we use to look for antibodies, so for instance, trying to find more cross-reactive antibodies, we look for more finer resolution epitope mappings as Dan just described because right now, and by the middle of last year, even there were a number of clearly defined antibodies available.
0:13:29.4 S2: If you look at the antibodies that were available from Vir, from Regeneron, you could use the Carterra technology to further help us identify antibodies to unique epitopes that haven't been screened before, and then in addition, we started to also explore alternate mechanisms beyond just the receptor-binding domain antibodies that block the spike protein from interacting with ACE2, and so all that work continued and the idea that we took was that we knew that there was a susceptibility that our antibodies that we had authorization for might become resistant or might no longer work against variants that are resistant to this particular treatment. So we wanted to have other antibodies sort of in the stable ready to develop or explore clinically should variants pose a continued threat to the existing antibody therapies and ultimately that led us at the beginning of the year to select another antibody called 1404 that came also from a patient and pursue the manufacturing and develop an event that current antibody is known as 1404.
0:14:30.4 S2: There's a bio-archive pre-print available, also now has the generic name Bebtelovimab, is in clinical studies and we hope that, we're kind of weighing now to see how the clinical data look and ultimately decide what we're gonna do to this antibody, but it's an example of having essentially a backup antibody waiting and this particular antibody we know is unaffected by all of the known variants currently circulating worldwide so it provides another weapon in the arsenal to fight this particular disease.
0:15:00.2 S1: That's great Bryan. It's really good to get an understanding of further developments and what we can look forward to. So just coming back to you now Dan, we learned about your work analyzing more than 350 neutralizing antibodies against COVID-19 developed by Biopharma-Academia and research centers around the world and presented it at the NIH summit on anti-SARS-CoV-2 antibodies with attendance by Dr. Francis Collins and Anthony Fauci. Can you discuss this Gates Foundation supported initiative which was led by the Ollmann Saphire lab at La Jolla Institute of Immunology and the type of analysis you provided in understanding how we might develop cocktails to conquer potential escape mutants?
0:15:39.1 S3: Sure, thank you. So the Coronavirus Immunotherapy Consortium or CoVIC was established as you mentioned by Eric Ollmann Saphire at LJI and was funded by the Gates Foundation, Wellcome and Mastercard per this operation Warp Speed Coronavirus initiatives. So, the consortium sought and compiled a set of over 300 anti-SARS-CoV-2 antibodies from many different collaborators and have the goal of figuring out which ones would be the best? What makes them the best? And which one could likely be combined? And how they will perform in response to various viral mutations. So this effort is ongoing as well as new variants emerge and as the trickle of antibody still comes into the program. So Carterra performed epitope binning on the panel of antibodies, and we found that the panel of antibodies provided to the consortium, which as we mentioned, came from really broad variety of sources and different antibody discovery platforms, really demonstrated a very impressive amount of epitope diversity.
0:16:47.1 S3: This was really good news, given that the vast majority of the clones were receptor-binding domain or RBD binders, and they blocked the ACE2. So in a more traditional receptor competition assay or epitope binning the level of diversity would really not have been apparent given the fact that there's a really high level of cross-competition among the clones, and like I said, they're broadly receptor-neutralizing, so therefore the inclusion of that type of characterization process wouldn't have been a suitable technique to assess the diversity and adjust what goes into the funnel moving forward. So the CoVIC process was interesting and a bit unique in that all of the clones were evaluated in many of the assays, I think the only assay that all of the clones weren't evaluated in was the cryo-EM stage 'cause it's just too time-intensive, but that generated a really rich data set, but most drug discovery screening processes really applied much more of a narrowing funnel approach, and so being able to generate all of the diversity of bio-functional and viral neutralization assays for everything is not really practical.
0:17:55.8 S3: So the CoVIC panel was found to cluster into a series of hierarchal epitope groupings of the RBD binders, there appeared to be, at least, 20 unique epitope behaviors, and it seemed to represent nearly the entire surface of the RBD, but many clones shared significant aspects of their profiles and we were able to classify them into about seven larger RBD community clusters. And the cryo-EM data generated for various representatives of these clusters really demonstrated that the larger communities were descriptive of the region or the face of the molecule over these clones bound and it described that general interaction surface. So the sensitivity of the binding of the clones to various spike mutants was really well-correlated to the presence of the mutations in that interface, with a few exceptions that appeared to be conformational.
0:18:48.7 S3: So this analysis really allowed for the selection of a combination of clones which can co-occupy the receptor, so even among clones with which both compete for receptor binding, there was sufficient shifting of the epitope location to create opportunities for two blocking antibodies to bind. Also given the conformational flexibility of the spike protein, the epitope community to which an antibody belongs was also predictive of whether or not the antibody could bind to the epitope in the RB up-down or both positions and confirmation states. So these experiments in the pairing with cryo-EM data for a number of clones have gone a long way to demonstrate just how descriptive and nuanced a high throughput binning experiment can be, and we believe that as the industry develops more experience with the technique, the level of sophistication in the application of this information to the screening funnel and the antibody selection process will continue to evolve and grow.
0:19:50.6 S1: Okay, that was a great response. Thank you Dan. Finally, Bryan, what considerations is really made for the neutralizing antibody program in regards to the expanded prevalence of the variants of concern?
0:20:01.4 S2: Well, I think first and foremost, the development of an antibody that seems to be... Today is completely active against all of the known variants and having that antibody potentially ready for use clinically is probably the primary approach that we're taking in addition to some other activities. We're still continuing to collaborate with AbCellera in this case, now that we have a receptor binding domain bodies, including Bebtelovimab which are good against variants now trying to look for maybe the needle in a haystack kind of approach. So for instance, looking for Pan-SARs antibodies, neutralizing antibodies such as Vir. It would be nice that we had... If you think about it, a future pandemic that's coronavirus based, it would be nice if we already had an antibody that was broadly cross-reactive, and then beyond that, I think it's something that everybody is concerned about and everybody is doing, especially at the companies that have antibodies approved or clinically being used clinically, is continuing to survey the viral landscape.
0:21:04.9 S2: Looking at variants through public databases, sequencing and making sure that we understand which antibodies are effective against which variants so the use of these antibodies can be tailored to where they're most likely to be effective, and that's primarily what we're doing at this point, I think hopefully the virus will eventually subsides, the vaccines take over and we no longer need these antibodies, but it's nice to have them obviously, it helps, they certainly all helped a lot of people, keeping them out of the hospital.
0:21:32.1 S1: Thank you. Thanks Bryan, and thank you Dan. That was a fascinating snapshot into the way that you've been involved in this as well as a really great taste of what the drug discovery set has to look forward to. So thank you both for your time today.
0:21:45.4 S2: Thank you.
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