Platform Lineage

From Communication Dynamics Theory (2015) to Foundation Models (2026)

2015
THEORETICAL FOUNDATION
Communication Dynamics Framework

Communication Dynamics (CD)

Reality as Information — Physical & biological systems modeled as Shannon communication channels

Mathematical Basis

Polygon error-control / DFT spectral basis
Block-circulant operators
Noise constant κ₀ = CD = 0.0118

Key Publications

Pan, Güldal, Baugh & Tanik, SDPS 2015
"Communication Theory Based Mathematical Models for Biomolecular Systems"
Pan, Skidmore, Güldal & Tanik, JIDPS 2022
"Application to Modelling the Valence Shell Orbitals of Periodic Table Elements"
Pan, L., arXiv:2605.08171, 2026
"Communication Dynamics Neural Networks: FFT-Diagonalized Layers for Improved Hessian Conditioning"

Dimensional Reduction

High-dimensional reality compressed into structure-preserving manifolds
~10× compute reduction in downstream models

2021
PLATFORM DEVELOPMENT
9 Modality-Specific Models Built on CD Framework
📊 GRAPH REPRESENTATION
Topology • 3D geometry • Interaction networks • Structure-aware molecular modeling
CarbonAI®
Small Molecule Design
Lead generation, scaffold hopping, PROTAC design. Target selectivity & ADME optimization.
No structure required • Wet-lab validated
MaterialAI™
New Material Design
High-performance alloys, functional materials, composites, nanomaterials. Material performance prediction & structure optimization.
Crystal structure prediction • Process optimization
NatmolAI®
Natural Molecule AI
800K+ natural molecule database screening. Traditional medicine modernization & green drug discovery.
Source tracking • ADME enhancement
FormulaAI™
Chemical Formula Design
Formula performance prediction, process route optimization. Safety control & intelligent manufacturing integration.
Knowledge graph driven • Cost prediction
CosmeticAI™
Cosmetic Innovation
Small molecule & peptide design for functional skincare. De novo actives, safety assurance, skin permeability.
Anti-aging • Hair care • Dermatological treatments
SynMagic
Retrosynthesis
Multi-step synthesis planning, reaction prediction. Route optimization & yield estimation.
10M+ known reactions database
🧬 SEQUENCE REPRESENTATION
Linear order • Residue tokens • Sequence PLM, structure-free peptides
SentinusAI®
Protein Design Engine
De novo protein design (IgG, Fab, scFv, VHH, peptides). Affinity maturation, humanization, ADC/PDC design.
No structure required • Wet-lab validated
CellulaAI™
Cell Programming AI
Intelligent cell engineering, AI-optimized cell line development. Precision manufacturing & multi-omics integration.
Comprehensive genome screening • Real-time analytics
BioSynthAI™
Synthetic Biology Engine
Gene design optimization, strain screening & evolution. Bioprocess control & intelligent production integration.
Green biopharmaceuticals • Industrial enzymes
SenseAI™
RNA Design Engine
Therapeutic RNA design & modification. mRNA codon optimization, siRNA design, UTR engineering.
mRNA vaccines • siRNA drugs • Protein replacement
PeptideAI®
Peptide Design Engine
Cyclic peptides, stapled peptides, bioactive peptide identification. Stability enhancement, cell penetration, proteolytic resistance.
Drug development • Cosmetics • Vaccine design
2026
FOUNDATION MODELS
Unified Multi-Modal Architecture

CHEMICAL

Molecular graphs • Reactions • Physicochemical space

Unifies: CarbonAI, MaterialAI, NatmolAI, FormulaAI, CosmeticAI, SynMagic
Training Data
200M chemicals
Parameters
Up to 1B
Architecture
Graph Neural Net

DNA / PROTEIN

AINN-P1 • Genomic • Protein • Peptide • RNA sequence space

Unifies: SentinusAI, PeptideAI, CellulaAI, BioSynthAI, SenseAI
Training Data
53M sequences
Parameters
Up to 1B
Architecture
Transformer
⟷
CHEMICAL ⟷ DNA/PROTEIN
Bidirectional cross-modal generation through shared latent space
Molecule → protein interaction | DNA sequence → compound design