In 2023, Formula-Y set out to answer a deceptively simple question: could therapeutic antibodies be designed computationally, with AI, before any wet-lab work, and could that be turned into a real service? With support from SNN (Samenwerkingsverband Noord-Nederland) under the MIT Haalbaarheid (feasibility) scheme, we ran a structured technical and economic feasibility study to find out.
Why it needed proving
Antibodies are one of the most important classes of modern medicine, used against cancers, autoimmune disorders and infectious diseases. But discovering them is complex, costly and slow, and still largely driven by laboratory trial-and-error. Before investing in building a platform, we wanted evidence that an in-silico-first approach was genuinely realistic, both technically and commercially.
What we examined
On the technical side, we assessed whether the raw material for AI-driven design exists in sufficient quality, which methods suit the task, and what it would take to build and run such a platform. On the commercial side, we mapped where the market potential is strongest across oncology, autoimmune, inflammatory and infectious disease, examined how to protect the resulting intellectual property, and identified a suitable service-based revenue model. Encouragingly, we also found biopharmaceutical parties open to collaborating once a proof of concept was in hand.
What came next
The feasibility study gave Formula-Y the confidence, and the roadmap, to move from idea to execution. It set the direction for everything that followed, from studying AI-driven target identification to the current proof-of-concept project.