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Advancing Antibody Innovation Through Discovery, Customization and Sustainability

3D rendering of antibodies with a soft gradient background, highlighting their role in immune response.
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Antibody development plays a pivotal role in advancing research, diagnostics and therapeutics. With their high specificity and affinity, antibodies serve as invaluable tools for detecting and neutralizing biological targets, enabling breakthroughs in diverse scientific fields.


Bio-Rad is at the forefront of antibody development, leveraging cutting-edge technologies and expertise to address critical challenges in the field. Bio-Rad’s antibody services including HuCALTM PLATINUM and the PioneerTM Antibody Discovery Platform exemplify this innovation, with Pioneer offering one of the largest functional phage display libraries for biotherapeutic discovery.


Technology Networks spoke with Dr. Sophie Mayle, technical sales specialist, Dr. Paul Royle, technical sales manager and Dr. John Cardone, marketing manager for Bio-Rad’s custom antibody services, to learn more about recent developments and future directions within the realm of antibody innovation at Bio-Rad.

Karen Steward, PhD (KS):

What recent technological advances at Bio-Rad have impacted antibody quality and reliability?


Paul Royle, PhD (PR):

Bio-Rad has recently developed the Pioneer Antibody Discovery Platform, which is a state-of-the-art phage display, human antibody library for biotherapeutic antibody discovery. The platform, combined with over 20 years of phage display expertise, rapidly generates diverse and high-affinity therapeutic leads with excellent developability profiles. At the heart of the Pioneer Antibody Discovery Platform is the Pioneer Antibody Library — one of the largest functional phage display libraries ever created.


The quality and reliability of antibodies are very much a focal point for the development of this library. For example, the sequences of the antibodies in the library have been very carefully curated to give antibodies that are not only very compatible with the phage display platform but also consider downstream factors, such as ensuring their developability liabilities are removed and the antibody sequences used are limited to the most developable germlines. So, the quality and reliability are something we’ve tried to build in from the start rather than generating an antibody and then having to look at modifying these kinds of characteristics later on.



Sophie Mayle, PhD (SM):

Bio-Rad has also developed SpyTag and SpyCatcher technology, also termed “molecular superglue”, which enables you to format antibodies rapidly at the protein level without the need for subcloning. This new technology has been embraced by the scientific community and Bio-Rad has focused on using it within the antibody field to address the need for different antibody formats depending on users’ applications.   


We add a SpyTag to our recombinant Fab antibodies and have developed a catalog of SpyCatchers that “glue” to the Fab to make multiple antibody formats known as TrailBlazer Antibodies.


The concept is similar to children’s interlocking bricks; you take one brick (or SpyTagged Fab) and glue it to other types of bricks (SpyCatchers) to obtain a different final construct. We've developed a pre-prepared set of SpyCatchers, including a range of labeled formats (e.g. BiSpyCatcher-HRP). The use of SpyCatchers increases the reliability of antibody batches since there is a high degree of batch-to-batch consistency as the label is at site-specific regions in the SpyCatchers and doesn't affect antibody binding as no label is ever introduced to the antigen binding regions.


Coupling an antibody with a SpyTag to different SpyCatcher proteins increases assay design possibilities by allowing the rapid assembly of multiple, stable products, including bivalent Fabs and Ig-like antibodies with different isotypes.



KS:

Could you discuss your custom antibody services and how they cater to specific research needs?


PR:
Bio-Rad has several antibody services to cater for specific research needs. For example, we have an antibody library for generating drug candidates (Pioneer), such as therapeutic antibodies, and another library (HuCAL) that we use for generating tool antibodies, like research antibodies, in vitro diagnostic (IVD) reagents and antibodies that are used in clinical trials. We can make custom antibodies that meet customer requirements by using antibody library screening strategies. We also have classical antibody cell cultures at a site in Oxford, UK. Here we can make very large (i.e., gram) quantities that we sell to IVD manufacturers.


KS:

What are some of the main challenges you see in antibody development and how is Bio-Rad addressing them?


PR:

I believe the quality of the output in antibody generation is highly dependent on the quality of the input, emphasizing the importance of starting with well-designed and robust reagents and processes. For example, if customers want an antibody to “protein X” but protein X isn't correctly folded, the protein will fail to represent its natural conformation in the human body; hence, the resulting antibody for that protein might not necessarily work in the real world.


So, antigen quality is a major issue for us. It’s not that the antigen supplied is of poor quality, but some proteins are very difficult to reproduce with their three-dimensional shape intact. For example, they may normally loop in and out of membranes, but you've removed the membrane. We have various approaches to get around this so we can work with purified protein including more recently working with a company called Salipro, whose technology allows them to reproduce the three-dimensional structure on nanodiscs.


We can also work with whole cells that over-express the protein of interest rather than purified protein. We let the phage bind the cell, we then spin the cells down and wash them, then release the phage.


In summary, we have strategies to solve potential issues that arise with generating purified protein structures for use as targets for the antibody generation campaigns, however, the more challenging the target the more consideration is required, which increases the risk of a project.


The nature of phage display means that we can alternate our planning strategy to try to ensure that we deliver antibodies that work against the best final antigen format.


A lot of our customers come to us after they've failed with an immunization-based technique. Our system is totally animal-free, and because it’s in vitro we can easily manipulate the conditions.


We can screen our library to meet the customers’ needs. For example, if we're making antibodies for a urine assay we can do our experiments in 10% human urine. Multiple factors can interfere with antibody binding in urine such as high salts, low pH and urea (a chaotropic agent), so using 10% urine means all those antibodies that are negatively affected will fall off.



SM:
We can also generate antibodies for more toxic products that cannot be introduced into an animal model, due to the development of necrotic lesions for example. There are obvious ethical reasons for not doing so but you may also not get a good immune response to the target. A lot of people are interested in working with toxic “payloads” such as in the antibody-drug conjugate (ADC) field. Rather than injecting animals with extremely toxic materials, Bio-Rad’s in vitro phage display technology platform can withstand very toxic materials like ADC payloads, venoms and bacterial toxins.


KS:

How is Bio-Rad advancing the design and production of bi- or multi-specific antibodies for complex diseases?


PR:

Bio-Rad is using the SpyTag and SpyCatcher technology I mentioned already, which is a method of covalently linking antibody fragments to other proteins, to aid advances in antibody design. We also have a modified version of SpyCatcher called SpyLock which is the subject of a recent Nature Communications paper.


SpyLock is a SpyCatcher domain that features an engineered cysteine. We used bulky molecules to bind the cysteine in SpyLock to prevent SpyTag binding. Reducing reagents can then be used to remove the bulky molecules to “unlock” the SpyLock allowing it to bind SpyTag. By using a SpyCatcher-Spylock fusion protein (named BiLockCatcher) we can sequentially add the first antibody binding arm, which will bind the SpyCatcher, wash, unlock the SpyLock, then add the second binding arm to get an assembly of 1:1 bispecific heterodimers, as seen in Figure 1.

Figure 1: Diagram illustrating how the SpyLock technology works. Credit: Bio-Rad https://www.bio-rad-antibodies.com/pioneer


This is a rapid reaction with the workflow taking ~90 minutes and is also very inexpensive. You can look at a very large number of combinations and then make a more educated decision about which antibodies you want to take forward in your bispecific antibody projects. 



KS:

How does Bio-Rad address sustainability in manufacturing and sourcing raw materials for its products?


John Cardone, PhD (JC):

Bio-Rad is committed to sustainability, focusing on reducing its environmental impact across manufacturing, R&D, packaging, and operations. The company minimizes its carbon footprint by prioritizing ocean freight over air transportation, installing solar panels at its Hercules, California headquarters, and retrofitting facilities with energy-efficient systems. Since 2016, Bio-Rad has worked with World Land Trust to encourage Bio-Rad customers in Europe to transition to digital ordering. This reduces the use of paper during the ordering process. For each customer who switches to digital communications, Bio-Rad plants a tree in the customer’s honor. The trees help conserve the Atlantic Forest in Brazil. So far, our customers have helped us plant over 3,500 trees, helping to reforest over 4 acres of this important habitat.


The company also prioritizes sustainable packaging by using recyclable materials and reducing waste, such as replacing polystyrene packing with eco-friendly alternatives. In the lab, Bio-Rad provides animal-free solutions and ensures compliance with strict sustainability standards, earning the highest score from My Green Lab. With goals to improve raw material sourcing and reduce CO2 emissions by 2030, Bio-Rad continues to enhance its sustainable practices globally.



KS:

What future trends in antibody technology do you anticipate, and how is Bio-Rad preparing for them?


PR:

I believe antibody research is a very exciting area of science and there’s mileage in antibodies as drugs.


For example, there are many different ways of displaying antibodies – not just phage display but also mammalian display and yeast display. Different ways of maturing or further engineering antibodies, different antibody fragments and ADC payloads as well. There are also different libraries for different purposes such as targeting of ion channels or recessed antigens—antigens that are more like holes rather than topographical features.



SM:

There is a lot of spin on artificial intelligence (AI) design for antibodies but as much as I still think people are interested in that, it’s not the standard technology and people still turn to the more traditional methods.


Interest in AI and work on it is significant but it’s being used to complement pre-existing strategies, rather than replace them. Currently, AI seems to be used more by companies working with immunization. Following immunization, they will take the B cells from an animal, sort them, and use next-generation sequencing. This ends up with an ocean of data of antibody sequences and AI can be used to group and cluster information. They will pick and express a few from a given cluster to see if the antibodies meet the pre-defined requirements of specificity, affinity and functionality. If a candidate antibody looks good, then they might sequence more from that cluster. There are multiple ways you can approach it. For example, we work the other way around, generating a very large number of antibodies as proteins using phage display and characterize them—do they bind what they should, do they not bind what they shouldn’t, do they have good affinities—then we pick and sequence the most interesting ones. This means we only end up with a small number of sequences. There are lots of ways to predict developability, liabilities or immunogenicity, and there's a lot of interest in how best to do it.


We seem to be a long way from having a standalone use for AI within antibody research. I think in some ways, data is lacking from “bad” antibodies. Everybody likes to sequence good antibodies that work, but algorithms often need to exclude the bad binders when trying to interpret data. Nobody spends huge amounts of time sequencing very large numbers of the bad antibodies – but I'm sure it will come.