We aim to redefine cellular classification by prioritizing molecular activity over molecular abundance, positing that chemical activity serves as a unique fingerprint of cellular identity. This new approach overcomes the limitations of traditional transcriptomic and proteomic methods that cannot differentiate between active and inactive molecular states. We plan to develop a scalable DNA-encoded chemistry platform for sensitive, multiplexed detection of chemical activity at the single-cell level. Our initial focus will be on protease activity—key in cancer and other diseases. Our method uses DNA-barcoded peptides as substrates; upon cleavage by proteases, the released DNA barcodes are detected via next-generation sequencing as markers of activity. This technique promises to enhance our understanding of cellular heterogeneity and disease progression, potentially transforming diagnostics and treatments by identifying new cellular types and subtypes not detectable with existing methods.