“…For effective deployment in real-world settings, lab methods need to be sufficiently cost-effective and robust to empower screening and enable adoption, including in under-resourced areas. Connections between the lab and the clinic also need to be further enhanced, including building more biobank resources with rich metadata, large-scale profiling of samples from clinically annotated and diverse cohorts, and better experimental methods to tap into banked samples, especially formalin-fixed paraffin-embedded issues, which are still incompatible with many single-cell methods 133,134 . Among the key computational challenges are the need for open data that reflect human diversity for training computational models, while appropriately safeguarding patient privacy; methods to decode cellular dynamics from static snapshots; algorithms and platforms for efficient querying for genes, cell states and cell types of interest; and fast iterations between lab and computation to design faithful human-derived organoids and cells for screens and therapies.…”