While most often associated with the field of pharmacology, the concept of dose is fundamental to every domain of physiology.All biological systems transduce inputs into outputs through quantitative relationships that are inherently nonlinear, dynamic, and individualized.Mechanical forces, chemical concentrations, electrical signals, temporal patterns, and genetic variations each have normal dose regimes that shape physiological state and determine downstream outcomes.Diseases emerge when dose is perturbed, sensitivities are altered, or the underlying dose-response architecture becomes pathologically reconfigured.Advances in sensing, computation, and multimodal data integration now make it possible to quantify dose with precision across molecular, cellular, tissue, and whole-organism scales.Identifying the normal dosing ranges across multimodal physiological processes provides a quantitative baseline for defining the boundaries of stable physiological control and sensitivities that govern transitions between states.There may be an important future to characterize individualized dose envelopes to identify where and how deviations arise.Identification of individually tailored dosing ranges will allow for personalized therapeutic strategies that adjust inputs with precision to recalibrate system behavior.Individualized digital twins through modeling and simulation may be a viable path for personalized prediction of normal homeostasis and disease ranges.In this review, we argue that dose functions as a unifying principle across physiology, examine its implications for mechanistic understanding, and describe how a dose-centered framework can catalyze the next generation of precision medicine. Key concepts Dose is a multidimensional input signal defined by magnitude, timing, pattern, localization and context Physiology is governed by nonlinear dose-responses with thresholds and stability boundaries Disease reflects reconfiguration of the mapping between dose and response Early disease detection may emerge from longitudinal shifts in sensitivity, threshold, capacity, and reserve Translation requires clinician-oriented dose maps, prospective trials, and equity aware infrastructure
Giordani et al. (Wed,) studied this question.