Are modality-agnostic platforms the future of drug discovery?

Drug discovery has always been shaped by the tools used to investigate molecules. Over the last decade, therapeutic formats have evolved rapidly, but many of the technologies used to characterize them have not kept pace.

Where discovery pipelines once focused mainly on antibodies and small molecules, they now include a wide range of modalities: targeted protein degraders, bispecific and multispecific antibodies, membrane proteins, fusion constructs, oligonucleotides, RNA–protein complexes, and delivery systems such as AAVs, lipid nanoparticles, and exosomes. These formats often behave unpredictably in standard assays, require special handling, or don’t fit the assumptions built into conventional workflows.

This growing complexity has made one thing clear: platform technologies must become more adaptable. The conventional approach — tailoring a unique assay for each modality — is increasingly impractical. The time, material, and expertise required to adjust for each format slows discovery and limits comparability across programs.

This is where the concept of modality-agnostic tools begins to matter. A modality-agnostic platform doesn’t just tolerate multiple therapeutic formats — it supports them all without requiring format-specific adjustments. It works whether you’re analyzing a small molecule or a large complex. It performs reliably in crude or unpurified samples. It provides consistent, quantitative readouts across formats. And perhaps most importantly, it does so without the need to redesign the workflow each time a new molecular structure enters the pipeline.

In early-stage research, where sample material is often limited and timelines are tight, these characteristics aren’t just helpful, they’re essential. The ability to evaluate binding affinity, kinetics, aggregation, and size directly in solution, in native conditions, removes significant bottlenecks. It makes it possible to answer meaningful questions earlier in the development process, without waiting for purification or optimization. And it improves internal consistency when comparing molecules that fall outside traditional categories.

FIDA is one example of a platform designed with these challenges in mind. It delivers in-solution measurements of hydrodynamic radius, affinity, kinetics, aggregation, and sample loss — all from the same sample, and often in unpurified matrices. It has been used to study protein degraders, bispecifics, membrane proteins, RNA–protein complexes, viral vectors, and other advanced constructs. But more than a list of applications, what defines FIDA is its adaptability. It allows researchers to maintain one workflow across many molecular types, which ultimately leads to better decisions, faster.

As therapeutic development becomes increasingly driven by mechanism rather than format, the technologies that support it will need to do the same. Modality-agnostic platforms won’t replace every specialized tool, but they will form the backbone of a more flexible and efficient discovery environment — one that can keep pace with the diversity of modern drug design.

So yes, modality-agnostic platforms are likely to shape the next era of drug discovery. Not just because of what they measure, but because of how they enable researchers to work: with fewer constraints, earlier insight, and more room to focus on the science.

‍