JMIR Publications

ABSTRACT

Background:

Chronic multisystem instability remains a central barrier to translating advanced therapeutics, including gene editing, into real-world patient populations. While CRISPR technologies have demonstrated molecular precision in controlled environments, clinical outcomes in immune-volatile and infection-associated chronic conditions (IACCs) remain constrained by biological variability, environmental exposure, and incomplete system-level monitoring. Existing frameworks operate under assumptions of cellular and environmental stability that do not hold in populations affected by myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Long COVID, dysautonomia, and mast cell activation syndrome (MCAS). The scale of these conditions is substantially underestimated: corrected U.S. prevalence modeling indicates 75 to 90 million Americans are living with at least one IACC, with 25 to 35 million experiencing multiple overlapping conditions (Adinig, US-CCUC Framework, 2025).

Objective:

This paper introduces CRISPR²™ (CRISPR Readiness Index, Stabilization, Personalized Recovery), a state-dependent gene editing system architecture designed to address the gap between CRISPR molecular precision and clinical applicability in immune-volatile chronic disease. The framework aims to expand therapeutic reach, improve outcome interpretation, and reduce instability-driven costs in this population.

Methods:

Conceptual framework development was conducted using network medicine principles, integrating established epidemiologic models, systems biology literature, and longitudinal chronic disease research. The framework synthesizes six operational components: Target Readiness Index (TRI), CRISPR Readiness Index (CRI), Stabilization, Tolerance and Immune Readiness (STAIR), VitalGuard environmental modeling, SymCas temporal symptom intelligence, and Stage Zero early detection. Theoretical grounding draws on the Primary Chronic Trigger (PCT) model and Unified Network Collapse Theory (UNCT), both developed within the CYNAERA Institute framework ecosystem. Population estimates derive from the US-CCUC model applying infectionto-chronic conversion rates and diagnostic undercount correction to 2026 parameters (Adinig, USCCUC Framework, 2025).

Results:

CRISPR² identifies three primary failure modes in conventional gene editing deployment: absence of patient-state intelligence, exclusion of environmental exposure as a continuous biological variable, and binary outcome interpretation that misattributes system-driven variability as therapeutic failure. Conventional models reach approximately 20 to 30 percent of the IACCaffected population due to instability-based exclusion. By integrating readiness assessment, stabilization pathways, and environmental and temporal modeling, CRISPR² expands modeled therapeutic reach to 55 to 75 percent, representing a two to threefold increase. Applying a conservative average annual cost of $50,000 per patient and a 20 to 40 percent reduction in instability-driven burden, the framework projects national-scale savings in the hundreds of billions annually under conservative deployment assumptions.

Conclusions:

CRISPR² resolves a structural mismatch between the molecular precision of gene editing technologies and the biological complexity of immune-volatile chronic disease. By treating patient state, environmental context, and temporal dynamics as integral rather than peripheral to intervention design, the framework establishes the conditions under which CRISPR remission becomes feasible at population scale. These findings have implications beyond gene editing for any advanced therapeutic requiring alignment with system state in relapsing, multisystem, and environmentally sensitive conditions.