Blank Bio

Blank Bio identified a critical bottleneck in mRNA drug development: designing effective mRNA sequences required running thousands of expensive, time-consuming laboratory experiments before identifying viable candidates. Pharmaceutical companies and biotech firms experienced this most acutely—each failed iteration consumed weeks and millions in resources. The problem was measurable: companies could quantify experiment costs, timelines, and success rates across their pipelines. Existing alternatives were limited to traditional trial-and-error screening or basic computational models that lacked accuracy. Blank Bio's RNA foundation models offered a fundamentally different approach by predicting mRNA properties computationally, potentially eliminating redundant wet-lab work. Early validation came quickly: Sanofi and GSK adopted their open-source models, signaling that industry leaders trusted the predictions enough to integrate them into actual R&D workflows. This wasn't theoretical interest—it was immediate, practical adoption by companies with billions at stake, demonstrating the model's credibility and the acute nature of the problem it solved.