Antibody discovery – past, present, and future

Three of our antibody experts discuss how developments in antibody discovery platforms are contributing to personalized medicine, and take a look to the future of antibody discovery.

Antibody discovery platforms have come a long way since initial steps towards understanding what antibodies do and how to harness them. The first monoclonal antibody was developed using a hybridoma technique, in which a single cell line is immortalized and produces the same antibody.1 Since then, monoclonal antibodies have moved from lab to clinic, with the first approved antibody-based therapy used to prevent kidney transplant rejection.2 Advances in technology and science mean that antibodies in the form of immunotherapy look set to combat some of the most significant diseases or our time, from neurodegeneration to cancer.

Although antibody discovery has progressed significantly, many still use these fundamental concepts. Whether one antibody discovery platform or another is better depends on the needs of the researcher and the intended use of the antibody. Here we bring together three experts in antibody development platforms from Abcam: Dr Joyce Young, VP of Custom Solutions, Dr Jamie Campbell, Head of Custom Solutions UK, and Dr Valeria Busygina, Head of Custom Solutions US. These scientists work to develop and implement our antibody platforms and have a keen interest in the future of antibody discovery. 

From left to right: Joyce Young, Valeria Busygina and Jamie Campbell.

Immunotherapies and stratification

Personalized medicine is unfolding and represents a new era for healthcare, where we use diagnostic tools to stratify patients into groups depending on whether they will respond to a particular therapy.3 These stratifying biomarkers typically require antibodies to bind a biomarker of treatment response.4 Antibodies are also essential therapeutics themselves, as biologics that bind, block or stimulate disease targets or overcome regulation to unlock the patient’s immune response to tumor assault.5 Antibody development tools have been updated to meet these demands, and in turn, these new tools open new areas of research and business.

Dr Campbell explains why antibody discovery platforms are increasingly important, and in demand, “In oncology, they’re seeing antibodies starting to become the mainstay of therapy. That means people moving away from the other types of therapies like small molecules, which although relatively cheap are not as specific as antibodies.”

Antibodies are not only able to bind the same targets that chemical drugs can, but also treat disease in novel ways. Dr Young expands, “The therapies coming out of antibody discovery are transformational; there are now so many different targets, and combinations of those targets, to go after. Antibodies are moving into very specific patient stratification to do that.”

How antibodies do this depends on the particular medicine, Dr Young explains, “Bi-specifics are big at the moment, joining different specificities of antibody together. The industry is even using antibodies to target and reprogram T cells. Antibodies continue to be the biggest growing drug market, and you have oncology therapies coming off the back of the immuno-regulatory space where the antibodies, instead of targeting the tumor, are targeting mis-regulation of the immune system.”

This focus on antibodies as therapies means the tools to study them are advancing, which is fundamentally changing the way science uses antibodies. Dr Campbell continues, “Antibodies are the main focus of many therapies, so the types of tools you need to support them are also developing. Originally, researchers would screen large compound libraries. Now, they’re doing antibody discovery, which is more efficient. Antibodies and antibody libraries are designed and targeted so rather than fishing in a large pool and seeing what sticks; you’re stacking the cards in your favor and biasing that pool.”

Antibody discovery: phage display

The first use of phage display, when developed back in 1985, was as a method of getting a bacteriophage to display a protein of interest by incorporating the gene for that protein into its genome. The phage then displays the protein on its coat. Phage display became incredibly interesting for antibody discovery as the protein displayed can be a binding fragment of an antibody,6,7 opening up the possibility of making antibodies against intractable targets (like toxins). Although phage display has been available for around 30 years until recently it has been expensive, difficult to do, and time-consuming.8

New platforms, such as the AxioMx platform used at Abcam, have sped this process up. We can now develop antibodies with the benefit of binder enrichment from diverse libraries within days to weeks rather than months or years.

Dr Busygina, explains, “Phage display allows us to target those molecules that are difficult with other methods, like targets that are toxic or not immunogenic. It also allows for more intelligent design of antibodies by predicting the sequence that would bind to a certain molecule, and by modifying the antibodies in vitro to procure the properties we want. Unlike immunization approaches, we control the input and outcome of every phage display-based antibody discovery. It is also much quicker, so we can achieve our goals faster.”

AxioMx is a high-throughput phage display antibody-discovery platform, using high-diversity libraries of antibody single-chain variable fragments (scFvs) fused to the P3 coat protein of an M13 bacteriophage. Our libraries are designed to allow rapid cloning to give a full IgG recombinant antibody, all created using animal-free technology. This type of antibody discovery is fast, cost-effective, and has benefits across a wide array of applications.

Antibody discovery: next-generation sequencing

Another approach to antibody discovery is next-generation sequencing (NGS). The NGS method enables the discovery of many more unique clones than traditional methods such as hybridoma generation, resulting in a pool of rationally-selected antibodies. This approach gives researchers access to a comprehensive database of antigen-specific binders, helping to increase the chances of identifying the best antibody for the task at hand.9

“It took us six-to-eight years to develop our NGS platform,” says Dr Young, “Much of that was around getting the bioinformatics together and applying the NGS to the rabbit immune response. The rabbit immune system brings many advantages, with diversity generated by gene conversion in addition to somatic hypermutation. It was rather a complex beast to tackle with NGS, but it’s now a robust platform that can go out to customers.”

NGS uses a large pool of potential candidates which naturally means a greater chance of discovering an antibody that best binds the target. Dr Busygina expands, “The NGS approach allows us to have an in-depth look into the whole immune response. Not only at a few clones, but what does the whole immune response look like. Then, using a bioinformatics approach to select a set of binders that will be the most beneficial to our application.”

Dr Young adds, “What NGS gives us is a blueprint of the immune response. We see laid out in front of us, like a galaxy of stars, all options that have been targeted by an immune response against a particular target. So that gives you huge scope in terms of hitting the exact properties you need for a given antibody, whether that be for diagnostic or therapeutic purposes.”

Ultimately, NGS is a way of narrowing the playing field to give a greater chance of hitting the target. “NGS and our immunization approaches are ways of biasing the pool of antibodies against the target, and then fishing from that smaller enriched pool. In the antibody discovery space, innovation is being driven by finding ways to make the pool more targeted, so that more things you screen and express will bind your target in the first place,” says Dr Campbell.

Dr Young also notes that NGS represents a great platform for business development, because an NGS screen will result in thousands of unique antibody sequences. These sequences can support an intellectual property filing to protect the resulting antibody discovery for a given target.

Unlike previous antibody discovery platforms that used Sanger sequencing where the data could be understood manually, NGS is as much a computational problem as a technical one.10 Dr Young expands, “Within the NGS space a huge component is dealing with the data. Data are no good unless you know how to interpret and use them. We’ve been careful to build suitable bioinformatics tools as we’ve developed our NGS platform, so we can put those thousands of sequences into arrangements and alignments that allow you to view the data from a rational perspective.”

Having partners with the expertise in both wet-lab technique and data management is vital for customers outsourcing antibody discovery. Dr Young says, “When we’re working with our partners, we don’t just throw them a whole load of sequences we’ve found, we guide them where to start. They’re essentially looking for a needle in a haystack, but we have the tools to let them know where to start, and we can then help develop those antibodies.”

Dr Young, “We don’t just say, ‘It binds to your target, figure out the rest,’ we work with the customer to ensure we know what they’re trying to do and that informs the assay cascades we put in to deliver against the profile.”

This kind of teamwork is key to the work that we do. “We’ve been very fortunate to have some customers who have come to us with real problems they’re having, and we’ve worked together as a joint team to solve them,” says Dr Young, “We’ve hit problems as we’ve gone along and resolved them using our shared expertise. Every antibody project we do is with the customer – they vary in how much they want us to be their expert partner or have us as part of an extended project team. But we can provide that bridge from a customer who is brand new to antibodies, through to pharmaceutical companies who have antibodies as a core part of their technology.” 

Partnering for success

Being specialists at producing antibodies is one aspect of what we do, but we also work to meet clients’ needs. “Previously Abcam has been known as having this great catalog of antibodies, now we’re able to support our customers from bench to bedside,” explains Dr Young, “We’re able to take clients from wondering if what they have is a target or not, to providing them with reagents that are produced under regulated manufacturing processes  and can be used to support diagnostics and patient stratification.”

Working with clients is key says Dr Young, “Abcam develops some of these therapeutics, and we help define which patients would benefit from them, we also bring the reagents which can allow us to do the patient stratification and then allow us to progress these drugs through clinical trials and pharmacokinetic analysis. Abcam supports from beginning to end, validating the target, deriving the antibody against it, deriving support reagents to that and supporting antibody drugs through development.”

The future of antibody discovery

Antibody discovery technology keeps moving and with progress comes new research and business opportunities. Dr Young says, “When it comes to antibody discovery platforms, we never stop. It’s not like we can get to one place and say, this is our platform, and this is what it does. The field is always moving, and we keep moving with it.” When it comes to the future of antibody discovery, Dr Young continues, “Things happening faster and more efficiently is a given. Even with our previous technology, in the past, it wouldn’t be uncommon to take a year to develop an antibody that’s a binder, and now we’re taking weeks to go from fusion to having a hit.”

Artificial intelligence (AI) is advancing all areas of science and technology, and antibody discovery is no different.11 Dr Campbell predicts AI will be essential in the future of antibody discovery, “With computational tools and bioinformatics advancing at such a rapid rate, not just in science but in all technology, I see these tools being used in the form of AI and these big data sets we now have from things like NGS.” He continues, “I think a lot of the initial analysis from an NGS library will be done using these AI tools, and that will essentially be the screening component. I can only see the NGS approach improving as our tools get better at predicting and understanding which clones we should make and select first. This means we’ll be able to screen less, provide antibodies to the customer more rapidly, and provide them with the right tool from the start.”

Dr Busygina is working directly with these tools in the laboratory and believes AI will ensure the discovery of new antibody platforms. “AI will allow us to do things faster, but it will also change how things are done. Initially, DNA sequencing was a tremendous effort, but now it is cheap and easy and fast. We want to move the antibody field to a similar paradigm, where we can achieve greater success in developing specific properties in each antibody we develop.” She continues, “We can now generate a lot of data regarding the immune response to a particular antigen, and regarding the evolution of antibodies in vitro. I can imagine that in the future we’ll combine those two approaches to allow in silico antibody prediction – we’ll be able to predict the properties of certain antibodies or predict the sequences we’ll need to put in the complementarity determining region to develop antibodies bioinformatically.”

Combining approaches and working out where the center of the Venn diagram of knowledge and technical ability sits is likely to hold the next fundamental shifts in antibody discovery. Dr Young concludes, “Going forward, I see us being able to really harness our knowledge of the immune system. Phage display is the way the AxioMx platform has harnessed the affinity maturation stage – a really clever molecular biology tool to give rapid affinity maturation – more rapid than any other phage display out there. That has meant applying knowledge of molecular biology to technology in a very clever way. There’s no reason we can’t continue to do that. Synergy between different technologies is often where you get the ‘aha’ moment and advance things, so we’re lucky to have three tremendous platforms: NGS, phage display, and RabMAb®.”



1) Köhler G, Milstein C. (1975) Continuous cultures of fused cells secreting antibody of predefined specificity. Nature. 256(5517):495–497.

2) Leavy O. (2010) Therapeutic antibodies: past, present and future. Nat Rev Immunol. 10(5):297. 

3) Maughan T. (2017) The Promise and Hype of ‘Personalized Medicine’. The New Bioethics. 23(1):13–20.

4) Kraeber-Bodere F, Bailly C, Cherel M, Chatal J-F. (2016) ImmunoPET to help stratify patients for targeted therapies and to improve drug development. Eur J Nucl Med Mol Imaging. 43(12):2166–2168.

5) Oo C, Kalbag S. (2016) Leveraging the attributes of biologics and small molecules, and releasing the bottlenecks: a new wave of revolution in drug development. Expert Review of Clinical Pharmacology. 6:747–749.

6) Smith G. (1985) Filamentous fusion phage: novel expression vectors that display cloned antigens on the virion surface. Science. 228(4705):1315-7.

7) Hammers C, Stanley J. (2014) Antibody Phage Display: Technique and Applications. J Invest Dermatol. 134(2):e17.

8) Hentrich C, Ylera F, Frisch C, Ten Haaf A, Knappik A. (2018) Chapter 3 – Monoclonal Antibody Generation by Phage Display: History, State-of-the-Art, and Future. Handbook of Immunoassay Technologies. p47-80.

9) Hardiman (2012) Next-generation antibody discovery platforms. Proc Natl Acad Sci U S A. 109(45):18245-18246.

10) Magi A, Benelli M, Gozzini A, Girolami F, Torricelli F, Brandi M. (2010) Bioinformatics for Next Generation Sequencing Data. Genes (Basel). 1(2):294-307.

11) David M, Concepcion G, Padlan E. (2010) Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies. BMC Bioinformatics. 11:79.