Finding a high-affinity antibody that binds to your target is only the first step. Not every antibody has what it takes to become a licensed medicine.
Bispecific antibodies are engineered to combine two epitope targeting regions into the same molecule and have long held out promise of expanding the potential of conventional monoclonal antibody therapeutics. Intelligent engineering of these molecules can go even further with the design of molecules with several epitope targeting regions termed multispecifics. In fact, the number of specificities, valency, and structure of these multispecifics can be varied in such a way as to allow an extensive panoply of potential molecular formats, the design of which can be exquisitely bespoke to the intended therapeutic use.
Uses of bi-/multispecifics
The industry pipeline for multispecifics has matured to a point in which many molecules from different multispecific platforms are poised to deliver new therapeutic products. The industry appetite for such molecules is indicative of the predicted therapeutic value of multispecifics, with the promise to propel the field, especially in oncology, to better clinical outcomes. Courtesy of their ability in binding multiple antigens at the same time, this diverse family of molecules can act in a variety of mechanisms by manipulating the spatial and temporal resolution of target molecules and cells.In this way, multispecific antibodies can bridge gaps or act as circuit breaks in signaling cascades, bring receptor molecules together, form multiple blocks on disease-related pathways, coordinate the interface between different cell types, to illustrate a limited few.More specifically, multispecific antibodies have huge promise as cancer therapeutics. Mechanisms of action include selecting for tumor cells via multiple targets to increase specificity and potentially perturb refractory or resistant forms of cancer, bringing together tumour cells and T-cells and/or other effector cells such as NK cells to coordinate multiple complimentary immune mechanisms, the presence of several specificities also allow the increased acuity of targeting a tumour cell alongside the ability to target the tumour microenvironment and limit off-target toxicity.
Difficulties engineering bispecifics
Despite the promise of multispecific antibodies, few have been approved at the present time. As of Q3 2021, only 4 bispecific molecules have been approved in the EU or US with 2 more in regulatory review1. Of these, the blockbuster HEMLIBRA®(emicizumab) for heamophilia has sales of >$500m a year2, illustrating the huge potential value of such molecules. The historical scarcity of multispecifics progressing to regulatory approval is in large part due to the considerable difficulties in producing such highly non-native molecules. The engineering and production process of bi-and multispecific molecules traditionally produces lower yield and purity products, this is mainly due to the problem of incorrect chain assembly plus additional aggregation and stability issues limiting the manufacturability of such therapeutics. However, with recent intelligent engineering advances, there are now several clinically validated multispecific platforms that circumvent some of the issues described. In fact, presently there are over 100 bispecific antibodies in the clinical pipeline ranging from tandem single-chain variable fragments (scFv) to full-length immunoglobulins with dual variable domains. Such molecules are also on an increasing trajectory. As of 2018, bispecific molecules accounted for 25% of the total antibody therapeutics in development, up 150% from the early 2010s1. Many of these therapeutics are poised to gain approval within the next decade as current generation bispecifics have almost identical rates of progress though clinical trials as other monoclonal antibody therapeutics.
Overcoming engineering difficulties at Fusion
At Fusion Antibodies, we have extensive expertise and experience in the use of many established multispecific technologies such as Knobs in Holes platforms (KIH) but can also utilise novel, non-propriety design strategies dependent on a client’s requirements. With a quality by design approach, we employ our in silico and protein engineering expertise to design and optimise an engineering program ideal for an antibody candidate, shaped with the endpoint in mind. This quality first approach leads all the way through to protein production in our transient gene expression (TGE) services where we offer optimisation of bespoke expression and purification strategies, of huge value for such challenging molecules. The complete process of antibody engineering is devised with the end in mind with considerations about scalability and manufacturability. The ultimate aim of these approaches is rooted in increasing the chances of therapeutic success.
Figure 1 – Examples of molecular formats that can be engineered by Fusion Antibodies.
Email info@fusionantibodies.com today to learn how we can help with your multispecific antibody development program.
With their high specificity, efficacy and safety profiles, it’s no wonder that antibodies have become the biggest selling drugs in recent years. Advances in antibody discovery, selection and manufacturing have catapulted therapeutic antibodies to become the primary treatment for several diseases and the market shows no sign of abating, with the industry expected to be worth $300 billion by 2025.
Mammalian antibody libraries are critical tools in the development of novel antibody therapies. By providing the platform for discovery and selection, these libraries help streamline and expedite the identification and pre-clinical optimisation of humanized antibodies. However, with limited numbers of available mammalian cell lines, it is difficult to achieve high diversity and maintain transfection efficiency.
Traditional libraries target complementary determining regions (CDRs) for mutational variation which limits potential diversity. What’s more, although CDRs are important for antigen binding, true specificity is much more complicated. Next-generation, synthetic mammalian libraries are taking a new approach to increase the specificity and affinity of manufactured antibodies. By increasing somatic hypermutation to mimic the natural mutation repertoire, large libraries of complete IgG, fully-human antibodies are being generated with high affinity and low immunogenicity.
Traditional synthetic antibody libraries create diversity by concentrating mutations within the CDRs. Once suitable human germline frameworks are selected, oligo-DNA cassettes are created for the CDRs. Diversity is then introduced through the use of NNK/NNS degenerate codons or error-prone polymerase chain reaction (PCR) techniques that create random amino acid mutations. Although some libraries now have biases towards the creation of certain amino acids within the CDR, the diversity is still only limited to these areas and the stark contrast in diversity between the framework and CDR regions is clear.
While CDRs are undoubtedly important for antigen-binding, framework areas contribute greatly to binding affinity and, using traditional techniques, these areas are largely ignored (see Figure 1). In the IGHV3-23 version antibody, widely used in therapeutics, mutations are almost solely seen in the CDR1, 2 and 3 regions of the variable heavy domain with little to no mutation seen in the framework areas.
Figure 1: Typical mutational pattern in a traditional synthetic mammalian library version of heavy gene IGHV3. Mutations are indicated by the white, green and blue colours and diversity is found only with the CDR regions.
Traditional display platforms are often limited to scFv or Fab fragments rather than full immunoglobulin (IgG) constructs. These fragments need to be converted to full IgG before they can be used as a marketable therapy, a process which is not always straightforward. To create antibodies that fully mimic the effectiveness of the B-lymphocyte’s response to antigens, we must turn to nature and generate libraries and techniques that mirror this response more closely.
Next-generation mammalian libraries are now being designed to align with natural repertoires, with mutations created throughout the heavy chain and, in particular, somatic hypermutations in the framework areas. In patient responses to SARS-CoV-2 spike protein, IGHV3-23 antibodies show mutations throughout the CDR and framework, with significant amounts of mutation in CDR 3 (figure 2). Successful phage displays, using libraries from COVID-19 patients, have already resulted in the creation of neutralising antibodies with promising results of treatment and immunising potential. These experiments demonstrate the inherent diversity needed for effective naïve human library design and their resulting antibody treatments.
Figure 2 Natural repertoire of IGHV3-23 mutations – demonstrating significant mutations throughout the CDRs and framework regions.
Fusion Antibodies has developed an optimised mammalian antibody library yielding complete, fully human antibodies. The library is designed for market optimisation and has been formed by selecting the most commonly used antibodies with the greatest market and downstream manufacturing potential. As well as choosing readily marketable antibodies, heavy chain CDR3 amino acid lengths were selected to mimic the natural response seen in humans. Guided by affinity maturation and humanisation platforms, mutational variation was added to the framework regions, along with the addition of separate CDR cassettes to mimic the natural genetic repertoire. The resulting antibodies show high affinity with low immunogenicity and are free of sequence liabilities.
COVID-19 neutralising antibodies are just tip of the treatment potential offered by fully humanized antibodies, created through this next generation of naïve mammalian libraries.
By screening antibody targets against whole, human antibodies the number of steps needed to discover new antibodies is greatly reduced, eliminating the need for platform switching and the reformatting required by some other approaches. By optimising future marketability at the design phase, antibodies are selected based on their affinity, downstream processing compatibility and market potential.
Next-generation mammalian libraries that maximise diversity, both in the CDRs and through somatic hypermutation in the framework areas, have the potential to increase the effectiveness of antibody treatments. With faster development timeframes and naïve libraries that mimic natural antibody repertoires, we can look forward to a future of treatments and diagnostics with higher affinity, selectivity and stability.
Dr Richard Buick, CTO of Fusion Antibodies explains what he believes to be the top criteria to consider when selecting a humanization outsourcing partner
Here at Fusion Antibodies, we’re celebrating our 200th Antibody Humanisation project, cementing our place as a leading CRO in antibody engineering services.
“This 200th Humanisation milestone is a wonderful achievement and I’m delighted for all of these projects which we have successfully completed,” says Paul Kerr, CEO of Fusion Antibodies.
Many therapeutic antibodies start off as a non-human animal antibody and are “humanised” to avoid generating an immune response. Since the Fusion Antibodies adventure started in 2001, we have expanded the number of antibody engineering services we offer. All of this has grown from our core expertise in antibody humanisation.
In 2012 we crystallised our know-how into our proprietary CDRx™️ platform, combining our laboratory experience with powerful in silico techniques. We graft the residues responsible for affinity from the animal parent antibody onto carefully selected mature human donor frameworks that we know to be stable and express well. We know exactly which residues are key to maintaining structure and function and our in silico phase screens out sequence liabilities that can impact stability, immunogenicity, expression, and manufacturing.
Using our CDRx™️ platform, we provide our clients with a 25-variant panel of humanised antibodies that retain the affinity of the parent antibody and that are development-ready. At least a third of antibodies from our earlier humanisation projects have entered clinical trials and we’re looking forward to following the trajectory of our newer projects.
“I look forward to the next 200 projects and working with drug developers around globe to create better drugs to unmet medical needs,” says Kerr.
We work with a range of customers, from small academic groups to small biotech start-ups, all the way up to big pharmaceutical companies, and many of our customers return for repeat business. Our customers have brought us antibodies from mice, rats, chicken, llamas and birds. They have brought us full antibodies, scFvs and Fabs. And we’re proud to say that every project has finished with a successfully humanised antibody with affinity within a 2-fold difference from the parent antibody. That isn’t our only guarantee. Other CROs offer a “success or your money back” service. We go a step further, and guarantee a successfully humanised antibody, full stop. We keep going until we have a panel of humanised variants with comparable affinity to the parent antibody. We won’t give up after one attempt, like many of our competitors, or offer your money back. We promise to keep going until we have succeeded.
“I feel proud to have developed such a robust antibody humanization platform, that consistently provides highly manufacturable antibodies to our clients. I am confident that some of the antibodies Fusion has designed will soon be marketed worldwide for the benefit of human healthcare.” says Dr Richard Buick, Chief Technical Officer of Fusion Antibodies.
The success of Fusion’s approach is down to a carefully cultivated mix of experience, curiosity and innovation. “Innovation is in our DNA at Fusion Antibodies,” says Kerr, “We will continue to improve our CDRx™️ platform with machine learning and AI.”
The most effective medicines in the world are of limited value if they can’t be produced in bulk, and at a reasonable cost. Therapeutic antibodies take years to develop. Without good oversight, each stage of development risks operating in a vacuum, with teams concentrating solely on their task before passing the candidate antibody onto the next team. An antibody developed with this “pass the parcel” approach may tick all the boxes for moving into clinical trials; it may even ace clinical trials. But if production cannot be scaled up for bulk manufacturing at a reasonable cost, the antibody is simply not commercially viable. Early engagement with manufacturing and commercialization experts and a helicopter view of the whole project from start to finish keeps the focus on developing an antibody that’s fit for purpose.
Scaling up determines cost of goods
Developers should look further than affinity alone when selecting a lead antibody. It would be a cruel twist of irony to develop a safe and effective antibody that cannot be manufactured in sufficient supply to treat all patients. Therapeutic antibodies are administered in high quantities to achieve the therapeutic effect – this can be in the range of milligrams to grams per patient per treatment cycle. For example, patients treated with the therapeutic antibody adalimumab (Humira™) take 80 mg on day one and then 40 mg every other week. The manufacturing process must keep up with the demand created by such dosing requirements.
Production is a key factor determining the ultimate cost of goods. Antibodies are churned out by genetically modified mammalian cells, grown in suspension in bioreactors. The antibody sequence is a critical “part” for the recombinant cell line “machinery”. As any mechanic will tell you, simple robust parts allow the machinery to run smoothly. In this case, well designed antibody sequence “parts” are easier for the cellular “machinery” to churn out in quantity.
Ideally, affinity maturation and sequence optimisation should optimise the antibody for ease of expression by mammalian cells. The yield, or titre, of antibody produced by these cells determines the ease of manufacturing and therefore the cost of goods. A yield of 2 g of antibody per litre of cell suspension is the threshold for a commercially viable antibody (1). Titre up to 4-5 g/L and higher have been reported by some companies.
The titre determines how many cells are needed to harvest enough antibody – this in turn determines the size and number of bioreactors needed and the size of the factory needed to house them. Bioreactors typically range from containing 1,000 litres of cell culture up to 20,000 litres. The cost and time required to purify the antibody out of the cell suspension is another factor in scaling up production, and the ultimate cost of goods.
Production for clinical trials versus the market
Drug development is a race against the clock. Time and investment pressure means that antibodies are first produced in small batches for clinical trials before, or alongside, technology transfer, production scale-up and stability studies. Ideally the small batch production for clinical trials should form the basis for the scaled up bulk manufacturing. For example, changing the cell line to achieve higher titres for bulk production would require validation in additional clinical trials, setting timelines back by years. Similarly, a shelf life of one year may be sufficient for clinical trials, but stability of 3 years is needed for the market. Drug development timelines don’t always allow for a 3-year stability study before clinical trials – but doing things the other way around can lead to a commercially unusable antibody, even if efficacy and safety are good.
Development strategies
One of the main business decisions in antibody development is whether to make or buy, i.e. whether to perform all steps of the process in-house, or outsource certain tasks to specialist providers. A third option is to partner with providers, in a risk-sharing agreement. Whatever route is chosen, teams should start seeking and integrating expert advice about scale-up and commercialisation from the early days of the drug development process.
RAMP™, our rational affinity maturation platform, accelerates and optimizes selection of lead antibody candidates that are “pre-screened” for manufacturing suitability. Our proprietary rational library design introduces mutations in both the CDR and framework regions, inspired by how B cells use somatic hypermutation to generate antibody diversity. In silico modelling then screens out variants with sequence liabilities known to compromise expression and stability.
Contact us to see how RAMPTM can generate lead candidates that are manufacture-ready
References
Phage display has had a good run. After bursting onto the antibody engineering scene in the 1990s, phage display rapidly disrupted the field. The in vitro high throughput screening and selection offered by phage display hit the jackpot in 2002 with the approval of adalimumab (Humira®), which we now know as the world’s best-selling therapeutic antibody.
However phage display’s crown has been slowly slipping. Despite early promise, only 10 of the 100 or so FDA-licensed monoclonal antibodies were developed using phage display (1, 2). So what are the pitfalls of phage?
Antibodies on display in phage
Phage, or bacteriophage to give them their full name, selectively infect bacteria and hitchhike the bacterial machinery to replicate themselves. Biologists in turn have hijacked phage by inserting genetic code into the phage which is then manufactured into a protein by the bacterial hosts’ protein expression system and displayed on the phage outside coat. This link between the genotype (the genetic sequence inserted into the phage) and the phenotype (the antibody manufactured based on the code) is the most important principle of phage display.
Antibody engineers exploit this system for antibody discovery and for affinity maturation of lead antibody candidates. The genetic sequence of the starting antibody is diversified into a library of variants. Each genetic variant is inserted into a phage, in turn inserted into a bacterial factory that pumps out phage replicas bearing the antibody variant in protein format.
In a high-throughput process called biopanning, the antibody target (the epitope) is immobilised and a sample of each variant in the library is washed over the target. Any variants that bind to the target are considered hits.
Phage display libraries – big but have they delivered?
The “display” principle linking genotype and phenotype isn’t limited to phage. Numerous display systems exist, where the antibody of interest is displayed on ribosomes, or on the cell surface of bacteria, yeast or mammalian cells. Each system has its pros and cons, but phage display has several advantages. First the bacterial libraries hosting the phage are relatively fast, cheap and easy to grow up, compared to slower growing yeast and mammalian cells. Phage display has another big advantage – and that is big, big libraries of up to 10^12 variants.
However these large phage libraries come with a price, favouring quantity over quality. While fast, synthetic and semi-synthetic methods of creating library diversity create artificial variants that would never be generated by natural B cell diversification. In addition, synthetic random libraries can be skewed with certain bases showing up too often (or not often enough) at certain positions in the DNA sequence (3). The knock-on effect is the presence of amino acids in “unnatural” spots in the antibody. Such variants may have good enough affinity to register as hits in phage display biopanning, but these “hits” may turn out to have folding or expression problems.
Express yourself
Expression bias and folding errors are two of the biggest drawbacks of phage display. The prokaryote machinery of bacteria is simply not equipped to fold complex human antibodies and cannot make crucial post-translational modifications such as forming disulphide bonds. E.coli, the most popular phage host, can be picky about which antibodies it makes, preferring to express proteins rich in certain amino acids such as methionine and lysine. Phage display handles expression and folding of smaller proteins such as functional snippets of antibodies much better. Single-chain variable fragments (scFv) of antibodies are most suited to phage display, followed by antigen-binding fragments (Fab) (4). However even scFv expression is not without its problems. For example, these antibody snippets are prone to aggregation which can cause false negatives or positives. Another limitation with antibody fragments such as scFv occurs if they need to be reformatted to full length IgG or other formats. After the high-throughput screening phase of phage display, reformatting promising scFv variants can bring an antibody development project skidding back to a crawl. Plus, a promising scFv can turn out to have disappointing affinity once the whole antibody is expressed and folded properly in a mammalian cell.
The eukaryote protein expression and post-translational machinery of yeast display can overcome some of the expression problems of prokaryote phage display. But amongst the trade-offs are smaller library sizes and the larger volumes needed for growing enough yeast cells (5).
Alternatives on display
Some of phage display’s limitations can be overcome by pairing phage display with other technologies. Some groups pair phage display with yeast display (6), or screen phage display hits for functionality with flow cytometry (7) while others batch reformat scFv to IgG before further functionality analysis. But all of these approaches take time, money and resources.
Another option is to bypass phage display altogether. Here at Fusion Antibodies, our rational affinity maturation platform (RAMPTM) sidesteps most of the issues with phage display. Our rationally designed in silico libraries are magnitudes larger than phage libraries, with around 10^25 variants. Diversity is introduced rationally, following the example of somatic hypermutation, which minimises the risk of finding amino acids in unexpected places. Rapid in silico screening of the library yields a micro-library of the strongest candidates which are then expressed directly as full length IgGs in mammalian CHO cells – neatly avoiding expression bias, folding problems and the need to reformat fragments to full IgGs. RAMP™ can also be used in combination with phage display. For example for performing affinity maturation of a phage-derived lead antibody candidate, or for sequence optimisation to improve expression and stability in CHO cells.
Learn how RAMPTM can boost or replace phage display for affinity maturation and sequence optimisation of your antibody
Today, therapeutic antibodies are reaching the clinic in unprecedented numbers. However the path from laboratory to the clinic is far from smooth. Antibodies face a range of obstacles during development, from insufficient efficacy, to manufacturing difficulties to immunogenicity – any of which can spell the costly end of an antibody development program.
Since 2012, Fusion Antibodies has delivered over 160 successful antibody humanization projects to customers worldwide. For many of these projects, we and our customers observed that our humanized antibodies retained and even improved antigen affinity, compared to the parent antibody.
Antibody candidates originate from many sources, using ever-improving discovery technologies. However, achieving a balanced antibody profile can be challenging. Our customers need to identify and eliminate those initially promising antibodies that bind tightly, but later turn out to have problems with manufacturing, stability or immunogenicity. They need to be sure they have the right antibody before establishing a stable cell line, and be confident that their lead candidate can get through CMC testing and make it to clinic.
To help customers face these challenges, we have poured our expertise into creating RAMP™ – our rational affinity maturation platform designed to accelerate and optimize selection of your lead antibody candidate.
RAMP™ combines innovative library design with stringent in silico screening of variants. This sieves out the strongest candidates into a micro-library that can be expressed in mammalian cells for further characterization.
Taking the parent antibody, we create a massive library of around 10^20 variants. Our proprietary rational design approach takes a leaf from nature, inspired by how B cells use somatic hypermutation to generate antibody diversity.
RAMP™ introduces mutations in both the CDR and framework regions to create diversity, allowing only amino acids that can naturally occur at each position in the human antibody sequence. This “natural” approach reduces the likelihood of hydrophobic patches of amino acids and the downstream risks of aggregation and immunogenicity.
At the same time, strict sequence checks are applied to screen out primary sequence liabilities such as deamidation sites, cleavage sites and free cysteines. These checks and balances help create a library of variants that are “pre-screened” for manufacturing and clinical use.
The library is then refined using in silico software that rapidly models variant-antigen binding and predicts affinity and stability. Over the 3-week in silico phase, the initial library is funneled down into a micro-library of the 100 strongest variants. At this stage we either express the micro-library as full length IgGs in CHO mammalian cells or hand the micro-library back to the client for further in-house testing.
RAMP™ for affinity maturation is a fast, reliable method for improving affinity and selecting your lead antibody candidate. In a promising performance test, RAMP™ improved the affinity of the best-selling breast cancer drug trastuzumab in silico and we’re currently validating the best variants experimentally.
RAMP™ can also be applied to “rescue” molecules, with promising functional activity but poor developability profiles, where finessing of the sequence is required. Our novel library design approach can also open up new sequence space to potentially build on your patent family and increase the value of your program.
AI and machine learning
Despite the buzz, the holy grail of true artificial intelligence (AI) – machines that can “think” and reason like humans do – remains elusive. In the meantime, deep machine learning is the established star of the in silico show. Machines are “trained” by feeding them large sets of experimental data and teaching them (via algorithms) how to perform a task. With each repetition of the task, the machine adds the experience to their knowledge bank, improves performance and comes up with results that humans didn’t necessarily expect. So how do in silico techniques, including machine learning, fit in to antibody development?
In silico antibody development
Antibody engineers have a plethora of options in their in silico toolkit for optimising antibodies. These bioinformatics tools include homology modelling to predict antibody structure, molecular docking to identify antibody-antigen interactions and algorithms to calculate energy changes in mutated versions of the antibody. Each of these processes can benefit from machine learning to speed up predictions and improve decision making. Stitching these processes together into an automating streamlined workflow saves even more valuable time.
Focus on libraries and screening
In silico techniques in antibody development have been described as third generation, following second generation in vitro and first generation in vivo methods1. Affinity maturation is a good example of how throughput has soared with in silico methodology. In silico libraries of around 10^25 variants have smashed through the experimental library size ceilings of mammalian display (10^10 variants) and phage display (10^12 variants).
Similarly, the time needed to screen through these libraries for the best sequence has decreased drastically from 3 months with mammalian cells or phage display, down to just 3-4 weeks in silico.
An added bonus is that in silico libraries and screening avoid the potential expression and biophysical issues related with phage display systems, while leaving the door open to promising variants that may not have expressed well in phage.
Challenges remain
The in silico approaches currently used in antibody design remain overwhelmingly knowledge-based. However, machine learning is only as good as the data you train it with. A current challenge is the scarcity of robust experimental open-access datasets, and a lack of widely accepted standards for validating data quality.
Another challenge is the changing skillsets needed by today’s biologists. Data scientists, programmers and technologists are now staple members of biology teams, and everyone needs to learn to speak a common language. Training university students in such interdisciplinary working will ensure the teams of tomorrow are well placed to harness the power of machine learning and in silico techniques.
Future applications
An exciting application of in silico technologies would be to open avenues of investigation previously hampered by experimental roadblocks. For example, G-protein coupled receptors (GPCRs) are a rational antibody target for many disease processes, but are notoriously difficult proteins to isolate out of the cell membrane where they are firmly embedded. In silico modelling could sidestep the difficulty posed by purification and antibody development. This means that proteins that were previously very difficult to raise antibodies against can now be targeted.
RAMP™ – Rational Affinity Maturation Platform
At Fusion Antibodies, we are firm believers in integrating bioinformatics and in silico techniques to accelerate our workflows and therefore your journey to the clinic. That’s why we developed RAMP™ – our rational affinity maturation platform. It takes RAMP™ just 3 weeks to create a massive library of around 10^25 variants of the parent antibody and to select out the best candidates using rapid in silico screening. The result is a micro-library of the 100 best candidates, selected for binding potential and stability.
Harness the power of our in silico RAMP™ technology to optimise your lead antibody faster.
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