Multi-Scale Nanomedicine Simulation Made Simple

Open-source platform bridging macro, meso, and micro scales for drug delivery research

OpenFOAM GROMACS AutoDock Vina
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Industry-standard drug discovery

Macro

Transport

μm-mm
→

Micro

Docking First

Å-nm
→

Meso

MD Validation

nm-μm

Fast docking screens thousands → MD validates top candidates

Nanoparticle delivery & membrane targeting

Macro

Transport

→

Meso

Membrane MD

→

Micro

Docking

→

Meso

Validation

MD explores membrane interactions → Docking targets receptors

The Challenge

Nanomedicine researchers currently face fragmented workflows across multiple scales

⚠️

Manual Data Transfer

Researchers spend weeks manually converting data between incompatible simulation tools

📈

Steep Learning Curves

Each software requires months of training across CFD, MD, and quantum chemistry

💰

High Costs

Commercial licenses cost $10,000+ annually, limiting accessibility for researchers

🔧

No Standard Workflow

Every lab builds custom scripts, leading to poor reproducibility

Our Solution

A unified, open-source platform that automates multi-scale simulation workflows

🔄

Adaptive Workflows

First platform with bidirectional scale bridging - automatically selects optimal workflow based on your use case

Our Competitive Edge
🔗

Unified Interface

Single interface to configure and execute simulations across all three scales

🤖

Intelligent Routing

Smart workflow selection based on target type, compound library size, and computational budget

🌍

Open Source

Free for research and education, with transparent, community-driven development

Understanding Multi-Scale Simulation

NanoSim bridges three distinct simulation scales to provide comprehensive drug delivery insights

Comparison of macro, meso, and micro simulation scales in NanoSim
Macro scale icon

Macro Scale (μm-mm)

Blood flow, tissue transport, nanoparticle circulation using CFD (OpenFOAM)

Meso scale icon

Meso Scale (nm-μm)

Cell membrane interactions, protein dynamics, lipid bilayers using MD (GROMACS)

Micro scale icon

Micro Scale (Å-nm)

Molecular binding, ligand-receptor docking, binding affinity using AutoDock Vina

Key Features

01

Bidirectional Scale Bridging

Seamless data conversion in BOTH directions - supports docking-first (standard screening) AND MD-first (membrane targeting) workflows with built-in validation

Bidirectional workflow comparison: Standard screening vs Membrane targeting
02

Docker-Based Architecture

Pre-configured containers for OpenFOAM, GROMACS, and AutoDock Vina ensure reproducibility across environments

03

Interactive Visualization

3D visualization of simulation results with real-time monitoring and progress tracking

04

Workflow Library

Pre-built workflows for common drug delivery scenarios to accelerate your research

Example Use Cases

🎯 Targeted Drug Delivery

HER2-targeted nanoparticle drug delivery illustration

Simulate liposome transport in blood vessels, nanoparticle accumulation in tumors, and predict ligand-receptor binding affinity

Example: Doxorubicin-loaded nanoparticles targeting HER2+ breast cancer

💉 Vaccine Delivery

mRNA lipid nanoparticle vaccine delivery mechanism

Model mRNA-lipid nanoparticle distribution, cell membrane penetration, and endosomal escape mechanisms

Example: mRNA vaccine formulation optimization

🧠 Brain Drug Delivery

Nanoparticle crossing the blood-brain barrier

Model nanoparticle transport across the blood-brain barrier using receptor-mediated transcytosis and endothelial cell interactions

Example: Transferrin-functionalized nanoparticles for brain tumor treatment

Development Roadmap

Phase 1: Proof of Concept

Current - Month 6
  • Bidirectional workflow architecture ✓
  • Intelligent workflow router ✓
  • Scale bridge implementations ✓
  • Docker containerization (in progress)
  • Python API wrappers (in progress)
  • Example: HER2-targeted liposome

Phase 2: MVP Development

Months 7-12
  • Web-based interface
  • Cloud job execution
  • All three scales integrated
  • Visualization dashboard
  • Beta testing with 10+ users

Phase 3: AI Integration

Months 13-18
  • AI parameter recommendations
  • Natural language interface
  • Automated result interpretation
  • Interactive learning modules