The Chemo-Transmitter Domino: A Substrate-Layer Audit of Nobel Prizes in Physiology or Medicine as a Predictive Methodology

Existing methods for predicting Nobel Prize winners rely on bibliometric indicators - citation counts, network centrality, h-index - and predict who will win. This paper proposes a categorically different methodology that predicts what domain will win, by auditing the substrate layers of past prizes. The central hypothesis: the majority of Nobel Prizes in Physiology or Medicine awarded since 1945 are sequential discoveries of the same underlying architecture - deterministic chemical cascade transmission - at progressively finer resolution. Each prize identifies one more domino in a chain whose substrate has remained constant. By mapping which chemical and physical layers of biological signal transmission have been awarded and which have not, it becomes possible to identify the unawarded layers as high-probability candidates for future prizes. This substrate-layer audit methodology is independent of bibliometrics, citation networks, and institutional prestige - it operates from the internal logic of the science itself. A worked example using the 2026 prize (optogenetics, Deisseroth) is provided, and candidate unawarded layers are identified.