Parse Biosciences, a Qiagen unit, partnered with bit.bio to build a transcription factor-driven cell identity map intended to support AI-driven therapy design and human cell manufacturing. The collaboration combines bit.bio’s cell programming technology and discovery platform with Parse’s scalable single-cell assay, Evercode, to test thousands of genetic variables against cell behavior. The companies said the resulting datasets and existing bit.bio internal data will help power predictive systems aimed at causal links between genetic inputs and biological outputs—an explicit goal for advancing “predictive medicine” workflows. For biotech R&D teams, the deal underscores a shift toward building shared mechanistic atlases and using them to reduce uncertainty in target selection, biomarker discovery, and cell-based product development.