📝 Biophysical Limits of Human Systems: Energy, Information, and Friction as an Integrative Framework of Wellbeing

C.J. Pérez Pulido
Director of Research, ISHEA Institute (Bologna · Rome · Puerto Rico)
ORCID: 0009-0004-1822-4798

🔗 Preprint: https://www.researchsquare.com/article/rs-8899090/latest
🔗 Data & Materials: https://doi.org/10.17605/OSF.IO/FYQGS

🔑 Key Points

• Wellbeing can be approached as a measurable biophysical state:
  EICI = (E × I) / F (proposed coherence formulation)

• NAD⁺-mediated redox dynamics (K₁) and ATP-driven processes (K₂) form a hierarchical bioenergetic structure

• Friction (F) is treated as a measurable constraint affecting system efficiency and execution

• The framework integrates indicators such as GDP, HDI, Maslow’s hierarchy, and SDGs as partial representations of a shared underlying structure

• Hypothesis: systemic performance may be constrained more by redox regulation than by ATP availability alone

❓ The Question Underlying This Work

Across existing frameworks—from GDP to HDI, from Maslow’s hierarchy to the UN SDGs—human wellbeing is typically quantified through fragmented indicators.

This work explores the hypothesis that these may reflect a deeper underlying biophysical structure that has not yet been explicitly formalized.

⚡ Core Proposition: Three Governing Variables

Across biological and social systems, performance can be interpreted through three interacting variables:

• Energy (E): capacity to perform work
• Information (I): structural organization that directs energy
• Friction (F): constraints that reduce efficiency and execution

From this perspective, a coherence index can be expressed as:

EICI = (E × I) / F (proposed formulation)

Higher E and I with lower F correspond to higher system coherence, while increased friction leads to reduced efficiency and stability.

🧬 Two-Level Bioenergetic Structure

Within the accompanying preprint:

A Two-Level Bioenergetic Coherence Model Integrating NAD⁺, ROS, and ATP within the ISHEA Δ±1 Framework

We propose a hierarchical organization:

We explore the relation:

K = K₁ × K₂^(1/2)

where ATP amplifies output within constraints defined by redox regulation.

📊 Preliminary Computational Results

Methods applied:

• Sobol–Saltelli global sensitivity analysis
• Monte Carlo simulations
• Partial correlation analysis

Indicative findings:

These results suggest that system-level performance may be more strongly associated with redox regulation than with energy availability alone.

🌍 Cross-Scale Interpretation

The same structural pattern may be partially reflected across different domains:

• GDP → captures economic energy flow
• HDI → partial informational structure
• Maslow → hierarchical needs organization
• SDGs → distributed constraint reduction targets

This suggests that existing frameworks may represent partial projections of a more general structure of system organization.

📖 From Biology to Systems Theory

The cellular model is extended as a conceptual hypothesis toward broader systems:

• Biological systems: metabolic and redox regulation
• Social systems: economic and institutional organization

From this perspective:

E · I / F → candidate expression of systemic coherence and wellbeing (hypothesis)

🔬 Testable Hypotheses

This framework generates several testable predictions:

• Increasing ATP without restoring redox balance yields limited systemic improvement
• Redox stabilization may improve efficiency independently of ATP levels
• Chronic stress is associated with reduced NAD⁺ availability and decreased coherence states

🤝 Open Questions

• Can redox dynamics be formalized as a predictive constraint across scales?
• To what extent can coherence metrics be quantitatively validated?
• How can this framework be experimentally tested in biological and social systems?

📚 Resources

🔗 Preprint: https://www.researchsquare.com/article/rs-8899090/latest
🔗 Data & Materials: https://doi.org/10.17605/OSF.IO/FYQGS
🔗 ISHEA Framework: https://doi.org/10.17605/OSF.IO/WST24

⚠️ Competing Interests

The author serves as Director of Research at the ISHEA Institute.
All data and materials are openly available via OSF.