Review of the CDATA Digital Twin (v0.1.0)

The Centriolar Damage Accumulation Theory of Aging (CDATA) proposes that the progressive loss of centriolar inducer molecules — driven by reactive oxygen species (ROS) and post-translational modification (PTM) accumulation — constitutes a primary, causally upstream mechanism of organismal aging. To formalize and test this theory, we developed a computational digital twin implemented as a multi-module Entity Component System (ECS) simulation in Rust. The platform integrates eight biological subsystems: centriolar PTM dynamics, cell cycle progression, mitochondrial dysfunction, hematopoietic lineage bias, stem cell hierarchy, asymmetric division, transcriptome-level gene regulation, and full-lifespan human developmental staging across 15 discrete stages from Zygote to Elderly. Five aging tracks (A–E) are explicitly modeled, with inter-track feedback loops connecting mitochondrial ROS production, epigenetic clock acceleration, telomere shortening, spindle fidelity loss, and ciliary dysfunction. The digital twin correctly reproduces the empirical mortality window (~78 years under default calibration), accelerated aging in progeria variants (×5 damage rates), and decelerated aging in longevity variants (×0.6 rates). We describe the architecture and mathematical formulations of each module in detail, and subject the platform to systematic critique: identifying assumptions that are biologically justified, parameters that are poorly constrained, feedback loops that may be structurally incomplete, and components whose absence limits predictive validity. We argue that the digital twin constitutes a valuable theoretical instrument but currently lacks the experimental parameterization, stochastic cell-population dynamics, and spatial niche geometry required to serve as a fully predictive model of human aging.