Current economic models rely on behavioral primitives (rational agents, constant discount rates) that neuroscience has shown to be biologically implausible. We propose nanoeconomics: a second-order epistemological framework integrated with neurobiology that updates existing economic theories by incorporating measurable neurophysiological primitives. As both a proof of concept for the generative power of nanoeconomics and a standalone theoretical development, we derive the Internal Intertemporal Inconsistency Coefficient (IIIC), which links dopaminergic states to time preferences, and demonstrate its applicability by updating (1) Modigliani’s Life-Cycle Hypothesis, (2) the Dornbusch overshooting model, and (3) the Keynesian marginal propensity to consume. Empirical evidence shows that people with opioid addiction exhibit time horizons of 9 days compared to 4.7 years in controls (≈190×), undermining assumptions of stable planning. Recent work links the opioid crisis to a reduction of up to 2 million people in the U.S. labor force (Krueger, 2017; Case & Deaton, 2017) via incapacitation and lower participation, with consequences for human capital. During that period, DSGE models failed to anticipate this shock, illustrating how neurobiological disturbances can evade conventional frameworks. Our approach provides falsifiable tools for incorporating neurobiological heterogeneity into existing economic models, enabling immediate, incremental improvements while paving the way for discrete advances in realism, predictive power, and epistemological rigor. By grounding economics in measurable neurobiological primitives, nanoeconomics articulates a clear and promising path toward hard-science standards.