New Approaches to Antibody Generation

Antibody-based therapeutics are the fastest growing therapeutic class on the market, with over 70 in clinical use today.¹ Nevertheless, monoclonal antibodies remain one of the most costly therapeutics to produce² and continue to suffer from key challenges despite recent advances in design, development, and manufacture. An increasing number of companies are leveraging synthetic biology tools to address these remaining challenges and unleash the full potential of these powerful therapeutics.

A challenging affair

Although the specifics vary, the same general workflow is followed when developing antibodies: identifying and validating targets, creating antibody libraries or leveraging existing ones to pan for hits, expressing and characterizing lead antibodies through affinity and functional testing, and scaling the production process.

Use of hybridomas remains the most common antibody creation method underpinning the production of most antibodies that ultimately end up in the clinic.¹ Yet, it can take up to eight months to develop them, requires humanization of antibodies or the use of transgenic animals, and of course, comes with ethical concerns over the use of animals. Alternative approaches, such as phage display of antibody fragments, which use Chinese hamster ovary (CHO) cells, E. coli, or, in some cases, the yeast Pichia, have been developed to address these drawbacks, but antibodies produced this way are typically less specific, requiring downstream affinity maturation (which requires time and money).

Regardless of the approach used to produce antibodies, time-consuming, often complex protocols that require expensive reagents drive up the cost of their production. Additionally, scale-up of traditional workflows is limited, further increasing production costs and limiting the number of antibodies that can ultimately be delivered to the market.

Advancing antibody production with synthetic biology

Synthetic biology, based on rational design and engineering, is an especially powerful solution to address these challenges. Synthetic biology can help make more effective, versatile antibodies faster and cheaper by enabling researchers to leverage improved antibody libraries and optimized or novel expression systems that are both cheaper and more scalable than traditional methods.

The next generation of antibody libraries

One of the low-hanging fruits for optimizing antibody production with synthetic biology is the antibody libraries themselves. By leveraging semi-synthetic or fully synthetic libraries, we can address the limitations of traditional phage-display antibody libraries, which include the need for PBMCs from immunized or sick animals or humans. Additionally, synthetic libraries provide more precise control over antibody properties and greater flexibility in the effective sequence space.

John Cardone, Marketing Manager, Custom Antibodies, Life Science Group at Bio-Rad, explains that “the experimental approach that can be exploited using synthetic antibody libraries is mainly linked to the ability to control for conditions in a way that immunization simply cannot do. Researchers can control for antibody properties by leveraging screening strategies that implement, for example, unwanted or wanted cross-reactive antigens, different pH and salt concentrations—all of which can be adjusted to influence binding specificity.”

Bio-Rad offers a synthetic library through the Pioneer^TM Discovery Platform, which, Cardone says, offers “the largest fully human, Fab output, synthetic phage display library in existence.” A huge advantage to this library, he adds, is its diversity. Bio-Rad scientists have bio-engineered the Pioneer antibody library “to include >200 billion unique antibodies and reduced sequence motifs that cause developability liabilities in lead candidates.” And results are promising: according to Cardone, the platform has been able to identify leads with picomolar affinities straight out of the library as well as functional performance and biophysical characteristics comparable to therapeutic antibodies currently in clinical trials.

Another company leveraging the power of diverse synthetic phage display libraries is Twist Bioscience, long a key player in the synthetic biology industry. Leveraging its silicon-based DNA synthesis platform, the company is able to synthesize a virtually unlimited number of human antibody libraries using gene sequence information derived from publicly available databases, rather than from PBMCs, completely eliminating the need for complex and costly immunization strategies. They are also automating the process of library production, antibody expression and characterization, and optimization, leveraging computational methods at certain stages to significantly decrease the time from lead discovery to optimized antibody.

Bio-Rad and Twist aren’t the first or only companies to leverage synthetic antibody libraries for antibody development, though: several therapeutic antibodies have been developed using fully or semi-synthetic libraries.³ However, these companies are leading the charge in using synthetic biology to increase the throughput of the production of diverse, highly specific antibodies, including for traditionally difficult-to-target molecules such as GPCRs.⁴

Increasing scale and manufacture capabilities with improved expression systems

Phage display libraries are only one part of a complex process, however, and several companies are working toward optimizing or upgrading the expression systems used for producing antibodies so they can be functionally characterized. One of the biggest issues with current approaches is the fact that most of the time, the same vector design is used for the expression of many different antibodies. This can significantly impact how much antibody is expressed, which is critical for its clinical release, says Jamie Freeman, Senior Director of Business Development and Commercial Strategy at Asimov.

Scientists at Asimov are leveraging a library of different genetic elements that have been experimentally characterized to optimize vectors for each specific antibody that will be expressed. They are also working on ways to optimize antibody secretion by CHO cells using algorithms to test different amino acid sequences and identify structures that require over- or under-expression of individual chains to permit correct folding and secretion.

The final piece of the puzzle is optimizing growth and antibody production of the cells into which the vectors have been placed by predicting optimal feeding regimes, seeding density, media, and other environmental factors. This is critical, says Freeman, because, “protein engineers are coming up with highly efficacious drugs that are not able to be manufactured at scale. Good, effective therapeutics are not making it to patients because of the incapability to make them.”

J. Casey Lippmeier, Senior VP, Innovation at Conagen, echoes Freeman’s concerns over manufacturing challenges. However, his company is approaching the problem differently: instead of optimizing vectors and scaling CHO cell antibody yields, Conagen is turning to microbes, looking to the food industry for inspiration.

“The food industry has a much better idea about how to exploit the economies of scale, and that’s why food ingredients are cheap,” explains Lippmeier. “Biopharmaceuticals made from microbes are an increasing trend. The first one was insulin, which people inject safely every day, and it’s pretty cheap, so we have precedents. We know it’s possible, we just need to extend it to monoclonal antibodies.”

Conagen is working toward just that, using a heterotrophic (i.e., non-photosynthetic) algae, which behaves a lot like a yeast in a fermenter, as an expression system. The organism is easy to manipulate genetically and has the scale-up potential that traditional microbial-based fermentation systems do. The algae also has a favorable glycosylation profile, as it does not produce immunogenic O-linked glycosylations like other microbes. Instead, it produces N-linked glycolsylations that are also found in humans and can be easily genetically manipulated if necessary. While the microbe hasn’t been used to produce any antibodies that have made it to the clinic yet, the groundwork is being laid.

The next frontier for synthetic biology in antibody production

Despite their diverse approaches, many of the companies mentioned in this article (as well as many others not mentioned here) do have one thing in common: the use of computational approaches—some to a larger extent than others—to inform and optimize their technologies. This of course begs the question: what is the potential to use only computational approaches to identify, design, and optimize a therapeutic antibody and then successfully bring that antibody to the clinic?

While we’re not there yet, if there is one thing that Bio-Rad, Twist, Asimov, Conagen, and so many others have taught us, it’s this: the tools are here, and they are making a difference already. With enough dedication and innovation, a new era of therapeutic antibodies built on synthetic biology is on the way.

References

1. Goulet DR and Atkins WM. Considerations for the Design of Antibody-Based Therapeutics. J Pharm Sci 2020;109(1): 74–103.

2. Wellcome. Expanding access to monoclonal antibody-based products Available from: https://wellcome.org/sites/default/files/expanding-access-to-monoclonal-antibody-based-products.pdf. Accessed November 14, 2023.

3. Sato, A. Antibody Development Made Easier with Synthetic Biology. Pharmatech. Available from: https://www.pharmtech.com/view/antibody-development-made-easier-synthetic-biology. Accessed November 20, 2023.

4. Garg P, et al. A High-Throughput Platform to Develop Highly Potent and Functional Antibodies against G-protein Coupled Receptors. Available from: https://www.twistbioscience.com/resources/webinar/platform-develop-highly-potent-and-functional-antibodies-against-g-protein. Accessed November 20, 2023.