The molecular phenotyping (transcriptomics, proteomics, metabolomics) of biobanked tissues helps dissect disease traits into underlying biomolecular processes. With high-throughput gene editing of in vitro models, and developments such as spatial and single-cell sequencing, this data-intensive study of molecular traits is increasingly called ‘cellular genomics’. After ten years of modelling molecular traits in the academe and industry, I will reflect on methods I believe are bearing fruit or need attention as genomic big data shapes drug discovery. I will present unexpected developments in collaborative studies of liver ‘rejuvenation’ between my team at the Novo Nordisk Research Centre, the Oxford Centre for Diabetes, Endocrinology, and Metabolism, and the Oxford Transplant Centre. As the metabolic traits studied are typically age-related, one side effect of this work is the illumination of broader pre-clinical ageing processes. I will conclude by sharing my long term vision for big data studies in healthy ageing, because as Stella taught us: age should just be a number