๐Ÿ‡ณ๐Ÿ‡ฑ Hoofddorp, Netherlands โ€ข KvK: 42019613

Generative Molecular Intelligence for De Novo Cancer Therapeutics

Accelerating small molecule drug discovery from 5 years down to 3 weeks using deep neural graph architectures targeting previously "undruggable" oncogenic proteins.

๐Ÿงช Small Molecule De Novo ๐ŸŽฏ KRAS / TP53 / EGFR โšก 3D Binding Affinity
TARGET: KRAS G12D
FPS: 60 AFFINITY: -11.4 kcal/mol
๐Ÿ–ฑ๏ธ Move or drag mouse to rotate 3D molecular structure
0
Molecules Screened
De Novo In Silico Library
99.2%
Binding Precision
Verified in 3D Simulations
4x
Lead Optimization Speed
From Years to Weeks
3
Lead Compounds
Preclinical Validation
INTERACTIVE DEMO

AI Molecule Generator Sandbox

Experience our generative AI neural model in action. Select an oncogenic target mutation, initiate de novo molecular generation, and observe live 3D structure morphing and parameter calculations in real time.

๐Ÿงฌ Live 3D Molecular Morphing Engine
READY FOR DE NOVO SYNTHESIS

Predicted Molecular Parameters

3D Binding Energy -11.4 kcal/mol
ADMET Toxicity Risk 0.02 (Very Low)
Molecular Weight 384.4 g/mol
Drug-likeness (QED) 0.91 / 1.0
OncoHelix Tensor Terminal v3.8 โ€ข Live Feed

> System Initialized. AI Model: OncoHelix-GraphNet-v3

> Location: Hoofddorp Neural Compute Node [NL-AMS-01]

> Selected Target: KRAS G12D (Oncogenic Pocket)

> Press "Run De Novo AI Discovery" to simulate generation...

OUR PLATFORM

The De Novo AI Engine Architecture

Combining 3D graph convolutional neural networks, quantum binding simulations, and automated ADMET filtering to design non-obvious, highly specific cancer drug candidates.

3D Pocket Discovery

Scans target protein surfaces to identify cryptic binding pockets on previously "undruggable" oncogenic mutants.

Generative Graph Net

Synthesizes novel small molecules atom-by-atom with precise stereochemistry to fit specified protein pockets.

Quantum Energy Scoring

Simulates molecular dynamics & free energy perturbation (FEP) to predict binding affinity with sub-nanomolar accuracy.

In Silico ADMET

Filters out toxic, unstable, or non-synthesizable candidates before entering wet-lab synthesis, cutting costs by 80%.

DRUG DISCOVERY PIPELINE

Our Proprietary Oncology Pipeline

OncoHelix AI is advancing a portfolio of targeted small-molecule therapeutics toward preclinical and clinical trials.

Compound ID Oncology Target Primary Indication Discovery Lead Opt. Preclinical Phase I Ready
OH-101 Lead Candidate KRAS G12D Pancreatic & Colorectal Cancer
Preclinical In Vivo Validation
OH-204 Optimization TP53 Y220C Ovarian & Breast Cancer
Lead Optimization & ADMET
OH-309 Discovery EGFR L858R Non-Small Cell Lung Cancer (NSCLC)
Target Pocket Mapping
๐Ÿ‡ณ๐Ÿ‡ฑ DUTCH BIOTECH ECOSYSTEM

Headquartered in Hoofddorp, Netherlands

Strategically located in the Greater Amsterdam biotech corridor in Hoofddorp, OncoHelix AI operates under strict Netherlands Chamber of Commerce (KvK) regulations and European Medicines Agency (EMA) standards.

KvK Registration Number: 42019613
Registered Jurisdiction: Hoofddorp, North Holland, NL
Regulatory Alignment: EMA & GDPR Compliant
Hoofddorp HQ (KvK 42019613)
Amsterdam AI Hub
Leiden Bio Science Park

Accelerate Your Oncology Drug Discovery Pipeline

We partner with pharmaceutical companies, biotech ventures, and research institutions to license lead compounds or co-develop de novo targets.