Cell line development teams lose weeks aligning data from instruments, assays, and imaging systems before they can even compare candidates. Clone IDs live in one system, titer data in another, morphology images somewhere else. By the time scientists piece it together, the decision window has closed.
The Tetra Lead Clone Selection Assistant connects that data automatically. Assay results, process metadata, and imaging analysis, harmonized by clone ID, passage, and time point, in one environment. Scientists compare productivity, stability, growth, and morphology side by side, then use predictive models trained on early-stage signals to forecast fed-batch performance before committing to scale-up.
Built with NVIDIA VISTA-2D for cell segmentation and AI-augmented for titer prediction, the app turns what used to take 8 months into a 2.5-month process. Teams we've worked with report 70% faster clone selection decisions and 85% lower cost of goods through higher-yield candidates and shorter timelines.
Watch the demo to see how connected data changes what's possible in cell line development.