Unlock the Future of Biology: AI Virtual Cells

AI-driven whole-cell modeling and prediction
Support for drug discovery, mechanism research, and virtual experiments
Customizable and scalable virtual cell solutions

Request a Demo Learn More

# Virtual Cell # Digital Twin # In Silico Perturbation # Single-cell Omics # Deep Learning # Drug Discovery # Gene Regulatory Networks # Systems Biology # Virtual Cell # Digital Twin # In Silico Perturbation # Single-cell Omics # Deep Learning # Drug Discovery # Gene Regulatory Networks # Systems Biology # Virtual Cell # Digital Twin # In Silico Perturbation # Single-cell Omics # Deep Learning # Drug Discovery # Gene Regulatory Networks # Systems Biology

Definition Applications Architecture Advantages Collaboration Deliverables FAQ Inquiry

What is AI Virtual Cell?

Artificial Intelligence Virtual Cell (AIVC) is a multi-scale, multi-modal, large-scale neural network model capable of simulating the dynamic behavior of molecules, cells, and tissues under different conditions. By establishing a universal representation of biological states, AIVC unifies data across species, modalities, and environments. This framework serves as a powerful reference for revealing core cellular traits, allowing researchers to seamlessly connect diverse datasets and leverage existing knowledge for deeper biological insights.

Why Do We Need Virtual Cells?

Cost & Efficiency: Drastically reduce the high cost and long cycles of traditional in vitro and in vivo experiments.
Infinite Exploration: Perturbation experiments are often limited in wet labs; AI models can explore the "untested space" to predict outcomes of millions of combinations.

Scenarios

Application Scenarios

Deploying AI Virtual Cells to accelerate breakthroughs across critical biological domains.

Drug Discovery & Development

Utilize virtual cells to predict efficacy, toxicity, and resistance mechanisms at the earliest stages of drug discovery.

High-Throughput Virtual Screening
Predicting Perturbation Responses
Personalized Drug Development

Disease Modeling

AIVC models the multi-stage progression of oncology, including tumor growth, invasion, metastasis, and complex dynamic interactions.

Oncology Research
Mechanistic Discovery

Synthetic Biology

AIVC provides influential "blueprints" and "simulators" for the design and construction of these artificial biological systems.

Designing Artificial Cells
Optimizing Cell Therapy

Gene Knockout Prediction

AIVC models are employed to systematically leverage knowledge of cellular responses obtained from known experiments and predict responses in unobserved scenarios.

Genetic Perturbation Modeling
Predictive Analysis

Spatial Reconstruction

By employing a computational framework, we can achieve de novo spatial reconstruction of cellular locations to elucidate how individual cells coordinate multicellular functions.

Spatial Transcriptomics
Cellular Trajectory Modeling

Cell Fate Prediction

Cell fate prediction employs post-knockout cellular characteristics and expression data to build predictive models that infer developmental trajectories or other fate-related information.

Functional Genomics
Genetic Perturbation

Technology

AI Virtual Cell Platform

Powered by large-scale biological foundation models, our platform redefines cellular research through three core engines.

AI Cell Design

The AIVC Design Platform integrates extensive biological knowledge to enable the dynamic analysis of complex cellular processes across multiple scales, temporal dimensions, and data modalities. By establishing a predictive "decoding language," the platform uncovers the fundamental principles governing cellular systems.

Multi-dimensional virtual experimentation—spanning diverse cell types, perturbations, and disease states.
High-precision predictions of cellular behavior while simultaneously illuminating the underlying biological mechanisms.

AI Virtual Knockout

The AI Virtual Knockout engine utilizes deep learning to systematically simulate genome-wide perturbations, predicting the phenotypic consequences of gene deletions without physical screening. By bypassing wet-lab limitations, it efficiently identifies essential genes and synthetic lethal pairs, mapping the landscape of potential therapeutic targets with unprecedented speed.

Genome-wide Screening
Combinatorial Perturbation
Target Identification

AI Cell Laboratory

The AI Cell Laboratory functions as a comprehensive digital twin environment, enabling the simulation of cellular behaviors under diverse chemical and environmental stimuli. It models intricate dose-response dynamics and time-series changes, allowing researchers to optimize experimental conditions and predict drug efficacy before implementation in the physical world.

Drug Response Prediction
Environmental Simulation
Multi-condition Testing

Why Choose Us?

Empowering your research with the next generation of predictive biology.

High Precision

Built on massive multi-omics datasets, our foundation models achieve state-of-the-art accuracy in predicting cell state transitions and perturbation responses, significantly outperforming traditional methods.

Interpretable AI

We move beyond "black box" predictions. Our platform reconstructs Gene Regulatory Networks (GRNs) to explain why a specific outcome occurs, providing actionable mechanistic insights.

High Customizability

Whether for oncology, immunology, or rare diseases, our models can be fine-tuned on your proprietary data or specific tissue types to create a bespoke virtual cell environment.

Workflow

Collaboration Process

From initial concept to validated discovery: a streamlined path to success.

Consultation

We assess your research goals and data availability to define the optimal virtual strategy.

Model Config

Our team fine-tunes the AI Virtual Cell model, integrating your proprietary data.

Simulation

We execute high-throughput virtual experiments to predict phenotypic shifts.

Validation

We deliver actionable reports for wet-lab validation, closing the discovery loop.

Deliverables & Cooperation

Flexible engagement models designed to meet your project's unique requirements.

What We Deliver

Virtual Cell Models: Customized AI models trained on specific datasets.
Prediction Reports: Detailed analysis of perturbation outcomes and state transitions.
Regulator Lists: Ranked lists of key genes and regulatory factors.
Visualization: Interactive charts and network graphs for data exploration.
Data Packages: Full access to raw and processed simulation data.

Cooperation Models

Customized Projects: End-to-end service for specific research questions.
Dedicated FTE Service: A dedicated team of computational experts working exclusively on your projects as an extension of your lab.
Joint R&D: Strategic partnerships with Pharma and Biotech for drug discovery.
Long-term Co-development: Continuous data sharing and model refinement partnerships.

Frequently Asked Questions

Common questions about our AI Virtual Cell technology and engagement models.

Can AI Virtual Cells completely replace wet-lab experiments?

While AI Virtual Cells are incredibly powerful, they are not intended to completely replace physical experiments. Instead, they serve as a high-efficiency filter and accelerator. By simulating millions of conditions in silico, we identify the most promising targets and exclude likely failures. This allows your wet lab to focus resources only on high-probability candidates, drastically reducing the cost and time of the "trial-and-error" phase in drug discovery.

What is the advantage of Virtual Knockout over CRISPR screening?

The primary advantages are scale and speed. Traditional CRISPR screens are limited by library size and cost, especially when testing combinatorial pairs (double or triple knockouts). Our AI Virtual Knockout engine can simulate genome-wide perturbations and complex combinatorial effects in a fraction of the time. It allows you to explore the "untested space" to find synthetic lethality or resistance mechanisms that physical screens might miss due to technical limitations.

Do I need massive datasets to train a custom model?

Not necessarily. Our platform is built upon massive, pre-trained biological Foundation Models that have already learned the fundamental rules of cellular regulation. This allows us to use Transfer Learning. We can fine-tune our models using your relatively small, proprietary datasets (e.g., specific patient-derived cells or rare disease models) to achieve high predictive accuracy without needing the enormous data volume typically required for training from scratch.

Is the AI model a "Black Box," or is it interpretable?

Interpretability is a core feature of our platform. We move beyond simple "black box" predictions. Our architecture is designed to reconstruct the underlying Gene Regulatory Networks (GRNs). This means when the model predicts a drug response or a knockout phenotype, it can also trace the prediction back to specific signaling pathways and regulatory factors, providing you with actionable mechanistic insights into the "why" behind the result.

How do you handle data security and Intellectual Property (IP)?

We treat your data with the highest level of security. All client data is processed in an isolated environment using enterprise-grade encryption. Crucially, we adhere to a strict Model Isolation Policy: any AI model fine-tuned on your proprietary data is dedicated solely to your project and is never merged with our public base models or used for other clients. Your data and the insights derived from it remain your exclusive Intellectual Property.