Predictive Bioharmonics: Mathematical Analysis of the Earliest Cancer Signal Identified in the GRAIL/CCGA Program

Predictive Bioharmonics introduces a mathematical framework that aims to describe when biological health may begin transitioning toward measurable disease — before clinical detection. The model complements and mathematically explains the early biological drift detected by GRAIL’s CCGA/Galleri program.

GRAIL’s CCGA/Galleri studies show that early cancer signals can appear years before symptoms, but the exact mathematical onset point has remained unknown. This paper suggests that GRAIL’s earliest cfDNA divergence (Δ ≈ 1.70–1.72) appears consistent with the mathematically-derived PB disease-onset threshold at ΔΦ = 1.702, derived from the harmonic–dissonant bifurcation sequence (φ → √φ → ΔΦ → 2.618 → 4.236).

By comparing Predictive Bioharmonics, Singlera Genomics (PanSeer), and GRAIL’s CCGA/Galleri program, this work proposes a mathematical interpretation for why early cancer signals may emerge at the same ratio across independent datasets — indicating that disease onset follows a universal, cross-domain mathematical sequence governing harmony and chaos.