Plastic pollution is no longer just an environmental load problem. At the nanoscale, plastics cross biological barriers, bind biomolecules, and interfere with regulatory networks in ways that classical toxicology—built around dose and composition—can no longer fully explain.
The Digital Nano Plastic Science (DNPS) initiative proposes a shift in perspective: from viewing nano- and microplastics as passive stressors to understanding them as informational disruptors within living, self-organizing biological systems. In this view, health is not only about molecular damage, but about the integrity of signaling, network coherence, and proteostasis across scales.
The DNPS White Paper integrates proteostasis biology, polybiome systems medicine, nano–biointerface science, and AI-driven modeling into a unified framework for anticipatory risk assessment. A central concept is the Proteostatic Stress Continuum (PSC), which captures how sub-threshold, chronic perturbations can silently accumulate before overt disease emerges—linking environmental exposure to systemic pathologies, including the proposed classification of Type 5 Diabetes Mellitus (T5DM) as a disease of the synthetic age.
By combining multi-omics data, digital twins, and the Systemic Risk Score (SRS), DNPS moves risk assessment from retrospective damage evaluation toward predictive systems stewardship within a One Health framework. The goal is not only to measure harm, but to preserve the informational integrity of biological networks before irreversible breakdown occurs.
The full White Paper presents the conceptual, computational, and governance architecture of this approach and is available on Zenodo with a DOI.
I welcome discussion, critique, and collaboration from colleagues working in environmental health, systems biology, microbiome research, and AI-driven medicine.
REYED M, R. (2026 ). Digital Nano-Plastic Science (DNPS) Paradigm: Computational Intelligence and Proteostasis Disruptions. Zenodo. https://doi.org/10.5281/zenodo.18435353