Biological longevity remains constrained despite continuous molecular repair and adaptive regulation, suggesting the existence of fundamental limits not fully captured by current mechanistic models. This work introduces an information-theoretic framework in which living systems are modeled as error-correcting structures operating under finite energetic and informational resources. We define informational persistence as the capacity of a biological system to maintain functional integrity over time in the presence of stochastic perturbations. By formalizing the balance between error generation, correction efficiency, and resource allocation, we derive quantitative constraints that impose upper bounds on system stability and lifespan. The model predicts that beyond a critical threshold, cumulative informational degradation becomes irreversible, leading to systemic failure irrespective of local repair improvements. This framework provides a unifying quantitative perspective on aging as an emergent consequence of constrained information processing, bridging concepts from biophysics, information theory, and complex systems. The results suggest that longevity is fundamentally limited by scaling relationships between entropy production, correction capacity, and system complexity, with implications for biological aging, synthetic life design, and longevity engineering.
Elias Troche (Tue,) studied this question.
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