We talk to a lot of teams trying to pick a bispecific platform, and the conversation usually starts in the same place: they have a list of formats, some sense that the options are different, but need some help deciding which differences actually matter for their program.
That’s a fair place to be. Bispecific antibodies have been around for decades, and in that time the field has produced an enormous number of ways to make them. A widely cited review counted well over a hundred distinct formats, and that was in 2017. There’s only been more development since then.
So this is the high-level tour I’d give you if you were investigating your options. What the main methods are, what problem each was built to solve, what trade-offs exist, and where the various platforms sit in that picture.
At Invenra, we help teams use our B-Body® format, so you should read this knowing that. I’ve tried to be straightforward about what the other approaches do well and where they fall short. No format is universally best, so I want to present those nuances objectively.
I only touch on this because the term is broader than some people expect. A bispecific antibody is any molecule that can bind two separate epitopes. It is a broad category that includes molecules with different shapes, sizes, and engineering approaches.
Once antibody engineers started trying to combine two binders into one molecule, they came up with a lot of clever ideas, and most of them work at some level. The differences show up later, when you have to manufacture the molecule and put it in a human being.
Here’s a visual look at the explosion of bispecific formats over time:
Bispecific antibodies offer a wide array of architectures. Reproduced from Brinkmann & Kontermann (2017), mAbs 9:2, 182–212.
Let’s take just a minute to tour this graphic.
The earliest good ideas were the simplest. Antibody engineers took the binding domains and stripped away most of the antibody, and stuck two of them together.
That produces formats built from single-chain pieces, the scFv and VHH shorthand you’ll see on any list. They’re small, easy to design, quick to make, and you can make a lot of them! Plenty of people know how to build them, and there are real drugs in the clinic made this way.
The problem is they don’t always work in the human body. A molecule built this way can look like an invader to the immune system.
Half-life can be short.
The molecule can be immunogenic.
These molecules often don’t have the inherent stability that a natural antibody has.
So, this route gives you something that binds great, but can also be an engineering nightmare.
There’s a “middle” group worth considering, and it's usually written on format lists as something like scFv-Fc or VHH-Fc. The name tells you exactly what it is: a fragment-based binder on one end and a full antibody Fc on the other. Some people call them hybrids here because that's what they are: part engineered fragment, part natural antibody.
The idea is to keep what's easy about the fragments while borrowing back what makes an antibody behave like one. You can take those fragment-based binders and attach them to an Fc, the vertical stem of the Y. The Fc matters because it’s how the molecule interacts with the immune system, and it embodies a lot of what makes an antibody behave like an antibody.
So these hybrids look more like the real thing. This architecture eliminates some challenges, but the binding ends are still assembled rather than natural, so they carry some of the same baggage.
The other approach is to keep the natural antibody shape and solve the assembly problem.
The payoff is predictability. In the body, an IgG-like bispecific behaves much more like a normal antibody. There’s a lower immunogenicity risk. These antibodies deliver a half-life of roughly a week for a human IgG, which tells you something about dosing before you run a single study. You likely get better stability on the shelf and in the vial.
To get there, you have to manage how an antibody is built from its four chains: two heavy and two light. Of course, in a normal monoclonal, the two halves are identical, so the chains only have one correct way to come together. In a bispecific, they’re different, and now four chains are looking for partners.
This presents two engineering challenges. The graphic below shows Challenge 1 (heavy chain pairing) and Challenge 2 (light chain mispairing), with the various attempted solutions: knobs-into-holes, common light chain, and combined approaches.
Combinatorial diversity of bispecific IgGs. Overview of possible combinations to arrange heavy and light chains from two different antibodies, including strategies to overcome incorrect heavy-light chain pairing.
I’ll briefly unpack each problem here.
You need the two different heavy chains to pair with each other rather than with themselves. This one is largely solved using the knobs-into-holes design.
You engineer a bump on one heavy chain and a matching groove on the other, so they fit together preferentially.
It was originally developed at one of the large biotechs; it’s been used everywhere for years, and it works well. The B-Body platform uses this approach. It’s a conventional technique that most IgG-like platforms build on. It solves one of the two problems because the format is virtually error-proof.
This is where platforms actually differ.
In nature, each light chain binds with the heavy chain it’s supposed to, because they evolved together. In a bispecific antibody, the two light chains are different, and the left one has to find the left arm while the right one finds the right arm.
When that goes wrong, you get mispaired molecules, impurities, and poor yield. At the kilogram scale in a steel tank, that’s expensive.
Three approaches are used to address light chain mispairing.
The simplest fix is to remove the problem. Use the same light chain on both arms. If there’s only one light chain, it can’t pair incorrectly.
It works, and molecules built this way are considerably easier to manufacture. The cost is your design space. You wanted the left arm to bind epitope A and the right arm to bind epitope B, and now both arms have to share a light chain that works well enough with both. You’re no longer choosing the best binder for each target. You’re choosing the best binder that happens to tolerate a shared partner.
For some programs, it’s a perfectly reasonable trade. If the binders you get are good enough, you have an easier molecule to make. The trade-off is you gave up options to get there, and you gave them up before you knew what you’d find.
Another approach keeps two different light chains and engineers electrostatic charges into the interfaces, adding or removing positive and negative charge so each light chain is pushed toward the correct heavy chain and away from the wrong one.
These are viable. There are drugs in the clinic built this way. But it’s worth seeing them for what they are: a set of mutations designed to work around a problem on the underlying architecture.
You’re steering chains that would otherwise pair incorrectly, rather than making it structurally hard for them to fail.
Another approach changes the architecture. Instead of nudging the chains, you swap out one of the domains that drives pairing so the two arms are no longer alike, making them unlikely to pair incorrectly.
This is the closest approach to what we do at Invenra, and generally the strongest of the three. As you assess the options, from fragments, to common light chain, to charge steering, to domain switching, the molecules get more IgG-like and the platforms improve.
B-Body sits at the far end of that progression, so let’s dig deeper.
The B-Body platform uses a domain switch technique. The specific swap we made is what gives the platform its properties.
Here’s a look at the B-Body design:
The B-Body architecture features knobs-into-holes Fc for heavy chain pairing, proprietary CH3 domain pairs substituting for CH1/CL in one Fab arm, and the plug-and-play variable domains.
In one Fab arm, we remove the native CH1 and CL domains and replace them with a proprietary CH3 pair, along with some internal mutations. The result is two arms that no longer resemble each other at the pairing interface.
The light chains won’t go to the wrong side because the surfaces they need to bind with aren’t similar enough to be confused. On the other arm, the natural CH1 and CL still zip together the way they always have, with multiple contact points holding it stable.
This elegant design has two advantages, and this is what I stress the most when describing the format:
You keep your preferred binders. Because the engineering happens in the constant domains and not the variable ones, you aren’t constrained in which antibodies you can use. Any well-behaved mAb will work well. No common light chain, no sequence compromise, no giving up your best binder because it doesn’t tolerate a shared partner.
One arm carries a single CH1, and that turns out to be worth a lot. Because only one arm has a CH1 domain, we use it as a purification handle. An anti-CH1 resin grabs only chains carrying that domain. We deliberately express the other chains in excess, so when we purify, what comes off is overwhelmingly the correctly assembled molecule.
That matters twice!
In screening, it means a one-step, plate-based purification of hundreds of molecules at a time. We can build a large panel in the real final format, purify it quickly, and test what actually works.
Then in manufacturing, the same molecule switches to conventional purification: standard Protein A on the Fc, then ion exchange polishing. No custom process, no special resin required downstream. Most platforms optimize for one of them. B-Body serves both.
Here’s the thing that gets overlooked when people compare platforms on binding data alone:
Nature never had to solve the problems we have. An antibody made in your body doesn’t need to sit in liquid on a shelf for six months, or survive being made by the kilogram in a steel tank, or hold up through freeze-thaw. It gets made, and it gets used. When we make an antibody as a drug, we’re of course asking to survive a complex manufacturing and supply chain on top of binding well.
When you evaluate a platform, binding is the entry ticket, not the answer.
The questions that decide whether your molecule becomes a drug are about everything else: yield, purity, stability, viscosity, immunogenicity, and whether what you saw in screening delivers at scale. That’s the standard I’d hold any platform to, including ours.
Here’s where the B-Body platform stands out:
To date, we’ve made more than a thousand different B-Body bispecifics using variable domains from many sources.
Across that set, over 95% of 1×1 molecules hit their purity target without any optimization. That’s the number I’d point to first, because one clean molecule proves nothing about a platform. A thousand starts to tell you something about how the platform behaves on your molecules
The purity distribution figure from transient CHO expression. Grey shows the main peak purity after anti-CH1 capture. Green shows the same after polishing. Here, we’re illustrating consistency across diverse variable domain sources.
With the B-Body platform, stable CHO clones run 6 to 11 g/L. For context, a typical bispecific results in 2 to 4 g/L. That difference shows up directly in manufacturing costs.
The part we find more useful, though, is the predictability. Expression tracks sensibly from transient to pool to clone, and early product quality is a good indicator of what you’ll see later. Late-stage manufacturing surprises are among the most expensive things that can happen to a program, and a platform where early data translates into manufacturability lowers that risk.
The progression figure shows expression yields of 0.1–1.0 g/L transient, 3–5 g/L pool, and 6–11 g/L stable clone, demonstrating that early product quality predicts manufacturing outcomes.
Not every program team wants the same bispecific shape.
A 1×1 binds each target once and suits most therapeutic applications, including tumor targeting and immune cell redirection.
A 2×1 gives you avidity on one side, which helps when one antigen is highly expressed and the other isn’t.
A 2×2 is bivalent on both and fits blocking or bridging work, including bi-paratopic designs.
With the B-Body platform, all three use the same discovery and manufacturing setup, so you can choose a format based on your biology rather than because it is what your platform can handle. (The more complex formats do give up some titer and purity relative to a 1×1, which is what you’d expect.)
Here’s a family portrait of the B-Body molecules:
The Invenra B-Body family. The B-Body platform supports three bispecific formats—1x1, 2x1, and 2x2—all with the same high expression and manufacturability. Most therapeutic programs start with 1x1 format for simplicity. If you need avidity or bi-paratopic binding, we can rapidly prototype 2x1 or 2x2 versions.
Titer and purity numbers for all three B-Body formats maintain excellent manufacturability with just one-step purification. Even our most complex 2x2 format achieves a transient titer of 170 mg/L and 85% purity without optimization (performance that typically requires extensive optimization on other platforms). Choose the format based on your biology and mechanism, not manufacturing constraints.
A molecule that can’t be concentrated can’t be given as a subcutaneous injection, which limits how patients receive it.
B-Body bispecifics have reached up to 200 mg/mL while staying under the viscosity limit for subcutaneous delivery, and they hold up through the stress of UF/DF processing.
On the safety side, B-Body molecules show cytokine release profiles and T-cell proliferation comparable to an approved clinical antibody control, and pharmacokinetics in non-human primates that look like a normal human IgG.
Viscosity vs. concentration of BsAb A in excipient-free formulations showing the concentration reached while staying under the 15 cP subcutaneous injection limit. Most bispecific platforms struggle with aggregation above 100 mg/mL, limiting dosing options. B-Body's high solubility gives you strategic flexibility: Sub-Q delivery, smaller volumes, less frequent dosing.
The B-Body approach is strongest when what you want is a human IgG-like bispecific antibody that binds two different epitopes. That’s what it was built for, and that’s where it’s superior to other formats.
But there are good ideas that don’t require two epitopes. Say you want one Fab arm to find a tumor, and then you want to position a cytokine off the bottom of the molecule. Or you want one side to be an antibody arm and the other side to be a ligand that binds a receptor. Those are legitimate multispecific drugs, and people are building them.
At some point, though, the molecule stops being an antibody, and once you’re there, our platform isn’t adding much. Fragment-based and appended formats may serve you better.
If what you really want to make is a bispecific antibody, the B-Body platform has been the logical fit for most of the teams we talk to. If you’re building something that stopped being an antibody a while ago, pick a format accordingly.
If you only take one thing from this guide, take the questions below. Use them when you are evaluating the B-Body platform or another approach.
| Ask this | Because |
| Does this bispecific format stay IgG-like? | It sets your half-life, your immunogenicity risk, and how easy your antibody transfers to manufacturing. |
| Can I use my binders? | Some platforms require a shared light chain, which narrows what you’re allowed to pick before you’ve seen the data. |
| Do I screen the real molecule? | If you screen a simplified version and reformat later, behavior can change, and you find out late. |
| What happens at the CDMO? | A platform that needs a custom purification process moves cost and risk downstream. |
| Can you show me more than one molecule? | Anyone can show a good result once. Ask what the distribution looks like across many. |
| Can it be dosed the way I need? | Concentration and viscosity decide whether subcutaneous delivery is even on the table. |
Most platforms answer two or three of these well. The reason we built the B-Body platform the way we did was to answer all of them, and the reason we put the comparison in writing is that the data is there to back it up.
Talk to us
Tell us what you’re building and what the molecule has to do. We’re happy to give you a straight read on whether the B-Body platform fits or when it doesn’t, and to evaluate your needs against our approach and other specific platform providers.
Contact us »
Or start with the data: The B-Body platform brochure has the yield, purity, formulation, and matrix screening data referenced above, in one file you can forward to a colleague. Download our B-Body data sheet »