Antibody developability checks are moving into discovery instead of waiting for development

Maria Gonzalez-Pajuelo, cofounder and executive vice president of technology and scientific office at FairJourney Bio, says that order is changing. She told Drug Discovery News, in a Sept. 30 piece by Bree Foster, that developability now carries far more weight during discovery itself instead of being saved for later-stage development. Her reasoning is blunt: a functional antibody that can't be manufactured and given to patients doesn't help anyone.

That moves a decision earlier in the program.

Where a strong binder turns into a repair job

A discovery campaign can produce hundreds or thousands of molecules that recognize a target, and teams narrow the pool on affinity, specificity and biological function. Nothing in that funnel guarantees the winner will be easy to develop. A molecule can perform very well in assays and still have poor stability, low expression, aggregation or formulation trouble.

Found late, those problems turn a promising lead into an engineering project: the team modifies the molecule and redoes work before the program can move again. Found early, the same information lets the team switch to a sibling molecule with a cleaner profile, or fix the problem while it's still cheap. Gonzalez-Pajuelo described the goal as discovery handing CMC something it can take forward easily. Skip that step, she said, and developability becomes the bottleneck.

What's changing is when properties such as stability and solubility get checked.

Choosing the discovery method from the end product

The same focus on the finished drug now reaches back to how antibodies are found in the first place. Discovery teams can pick from a broad set of in vivo and in vitro tools: hybridoma technology, transgenic animals, and phage, yeast and mammalian display. Each has different strengths. Gonzalez-Pajuelo's view is that no single strategy fits every case. Having access to all of them matters less than knowing which one suits a given target, and that depends on the target's biology and the target product profile.

The target product profile sets out what the finished therapy needs: how it works, how it will be given and what properties manufacturing will require.

Bigger screening panels made early checks practical

Moving these checks earlier depends on assays that can cope with the volumes seen in discovery. Genetic Engineering and Biotechnology News reported in September 2018 on comments from Jennifer F. Nemeth, director of biophysics, structural characterization at Janssen Research & Development. She said that a decade earlier, many assays had lower throughput and could take only 2, 10 antibodies at a time. Teams were now running multiple panels of tens to hundreds of antibodies through a single assay, she said, and these higher-throughput assays had moved earlier into drug discovery. One example was a high-throughput mass profiling workflow that Janssen R&D was developing with Genedata on Genedata's Biologics Refiner software.

Liusong Yin, director of antibody services at GenScript, said a fast-growing pool of candidates was chasing a slow-growing pool of targets, with most antibody campaigns aimed at existing targets. Citing regulatory trends in the European Union, Nemeth said a molecule that merely matches a product already approved may not necessarily win acceptance from the European Medicines Agency. Yin's broader point was that risk builds up: anything not dealt with at one stage costs more at the next.

When several programs pursue existing targets, the properties that make a molecule easier to manufacture and administer could be where one program pulls ahead of another.

Nemeth also separated the two stages. Discovery, she said, involves examining many different antibodies once or twice each, while development concentrates on several lots of a single antibody. That suggests a discovery-stage developability screen and development work answer different questions. For teams moving checks earlier, the payoff could be fewer surprises in development rather than less development work.

Immunogenicity shows up in patients, and then on the label

Not every property that matters can be ranked in a discovery screen, and some only show up in patients. A 2020 review in Frontiers in Immunology by Anna Vaisman-Mentesh, Yariv Wine and colleagues at Tel Aviv University and the University of Kansas found that some monoclonal antibodies trigger anti-drug antibodies in up to 70% of patients. Those anti-drug antibodies can change a drug's pharmacokinetics and pharmacodynamics, lower its efficacy or neutralize it altogether. They are also hard to detect: because the analyte and the antigen are both antibodies, the authors described most assays as cumbersome, costly, slow and poorly standardized. The review also summarized engineering approaches meant to make antibodies less likely to provoke this response.

Writing in Frontiers in Immunology in 2024, Steven Swanson of Genentech described FDA draft guidance that asks companies to describe clinically significant anti-drug antibodies in product labels, in addition to reporting how often they occur. Clinical significance depends on effects on pharmacokinetics, pharmacodynamics, efficacy or safety, and the guidance also specifies where that information goes in the label.

Swanson also offers the counterweight. In many cases, he notes, the immune response to a protein therapeutic has no clinical significance at all. An anti-drug antibody signal is something to understand and characterize. It is not automatically a reason to drop a program.

AI-designed antibodies face the same question

Those design tools face the same problem Gonzalez-Pajuelo describes. For R&D leaders evaluating these platforms, the thing to watch is whether stability, solubility and expression are scored alongside affinity at the design step, or whether developability is still something someone checks afterward.