Pioneering generative AI for pharmaceutical and material innovation with extensive wet lab validation.

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10B
Virtual Screening / Day
100+
Drug Design Projects
20+
项PCT专利
1B
Parameter Foundation Model
80%
Cost Reduction
10-60%
Wet Lab Hit Rate

关于我们 Us

Most Validated AI Therapeutic Design Platform

Ainnocence is a 全球 biotech company that leads in generative AI for therapeutic discovery, leveraging industry-grade sequence-based proprietary technology and 训练数据 from over 16 years of expertise.

The Challenge

Costly high-throughput wet lab screening, expensive structure biology, and inaccurate 3D modeling processes.

Our Solution

A radical AI drug discovery system accelerating life-saving therapies with unprecedented speed, deep virtual throughput, and higher success rates.

平台演进

平台血统

从通信动力学理论(2015)到基础模型(2026)

2015
理论基础
通信动力学框架

Communication Dynamics (CD)

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

数学基础

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

关键论文

📄 Paper I: Pan, Güldal, Baugh & Tanik, SDPS 2015
"Communication Theory Based Mathematical Models for Biomolecular Systems"

📄 Paper II: Pan, Skidmore, Güldal & Tanik, JIDPS 2022
"Application to Modelling the Valence Shell Orbitals of Periodic Table Elements"

📄 Paper III: Pan, L., arXiv:2605.08171, 2026
"Communication Dynamics Neural Networks: FFT-Diagonalized Layers for Improved Hessian Conditioning"

维度约简

10,000× 计算效率 相比传统量子力学/分子动力学模型
Polygon DFT evaluation bypasses continuous spatial grids
High-dimensional reality compressed into structure-preserving manifolds

2021
平台开发
基于CD框架构建的10个模态特定模型
📊 图表示
拓扑 • 3D几何 • 交互网络 • 结构感知分子建模
CarbonAI®®
小分子设计
Lead generation, scaffold hopping, PROTAC design. Target selectivity & ADME optimization.
No structure required • Wet-lab validated
太微元素™ (MaterialAI)
新材料设计
High-performance alloys, functional materials, composites, nanomaterials.
Crystal structure prediction • Process optimization
NatmolAI®®
天然分子AI
800K+ natural molecule database screening. Traditional medicine modernization.
Source tracking • ADME enhancement
FormulaAI®™
化学配方设计
Formula performance prediction, process route optimization.
Knowledge graph driven • Cost prediction
CosmeticAI™™
化妆品创新
Small molecule & 肽段 design for functional skincare.
Anti-aging • Hair care • Dermatological treatments
SynMagic™™
逆合成
Multi-step synthesis planning, reaction prediction.
10M+ known 反应 database
🧬 序列表示
线性顺序 • 残基令牌 • Sequence PLM, structure-free 肽段s
SentinusAI®®
蛋白质设计引擎
De novo 蛋白质 design (IgG, Fab, scFv, VHH, 肽段s). Affinity maturation, humanization.
No structure required • Wet-lab validated
CellulaAI™™
细胞编程AI
Intelligent cell engineering, AI-optimized cell line development.
Comprehensive genome screening • Real-time analytics
BioSynthAI™™
合成生物学引擎
Gene design optimization, strain screening & evolution.
Green biopharmaceuticals • Industrial enzymes
SenseAI™™
RNA设计引擎
Therapeutic RNA design & modification. mRNA codon optimization, siRNA design.
mRNA vaccines • siRNA drugs • 蛋白质 replacement
肽段AI®®
肽段设计引擎
Cyclic 肽段s, stapled 肽段s, bioactive 肽段 identification.
Drug development • Cosmetics • Vaccine design
2026
基础模型
统一多模态架构
化学

分子图 • 反应 • Physico化学 space

Unifies: CarbonAI®, 太微元素™ (MaterialAI), NatmolAI®, FormulaAI®, CosmeticAI™, SynMagic™
训练数据
200M 化学s
参数
Up to 1B
架构
图神经网络
DNA/蛋白质

AINN-P1 • 基因组 • 蛋白质 • 肽段 • RNA序列空间

Unifies: SentinusAI®, 肽段AI®, CellulaAI™, BioSynthAI™, SenseAI™
训练数据
53M 序列
参数
Up to 1B
架构
Transformer
⟷
化学 ⟷ DNA/蛋白质
Bidirectional cross-modal generation through shared latent space
Molecule → 蛋白质 interaction | DNA sequence → compound design

Foundation Model 架构

CD-Transformer 架构
  • • Block-circulant CDLinear layers: B× parameter reduction
  • • FFT-diagonalized Hessian: 310× better conditioning
Self-developed LLM Foundation
  • • Mixture-of-Experts (MoE) 架构
  • • Multi-head Latent Attention (MLA)
  • • Multi-Token Prediction (MTP) heads
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研究

科学出版物

Peer-reviewed 研究 spanning AI, drug discovery, and computational biology

Nature Scientific Reports • 2025

AI-designed, mutation resistant broad neutralizing antibodies against multiple SARS-CoV-2 strains

Demonstrating the power of sequence-based AI for therapeutic antibody design with unprecedented speed and accuracy.
SDPS 2015 • JIDPS 2022 • arXiv 2026

Communication Dynamics Theory Series

Three foundational papers spanning biomolecular systems, periodic table orbitals, and neural network 架构

Pan et al. — Mathematical foundation for all Ainnocence 个平台

Multiple Publications

AI Drug Discovery & Virtual Screening

CarbonAI® platform, ParaVS framework, antibody affinity maturation, and more

14+ additional peer-reviewed publications

查看所有17篇出版物

知识产权

专利组合

20+ 项PCT专利 protecting our AI drug discovery methodologies

20+
项PCT专利 Filed
10+
平台技术
全球
覆盖
View 专利组合

联系方式

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