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Unleash the Power of Cytocast Digital Twin Platform™

Step into the future of medical technology with Cytocast Digital Twin Platform™. Our cutting-edge platform harnesses the potential of cell simulation to transform how we approach drug discovery and development.

CYTOCAST DIGITAL TWIN Platform™

Cytocast is pioneering the future of drug development and personalized medicine with the CYTOCAST DIGITAL TWIN™ platform, an integrated solution that leverages advanced computational modeling and high-performance computing. At the heart of this platform lies the CYTOCAST DIGITAL TWIN Cell™, one of the most comprehensive and detailed simulated human cell model available today, covering 15 distinct tissue types and cell lines. This innovative technology accelerates drug discovery and development, reduces R&D costs, and enhances clinical trial success rates by enabling precise predictions of drug effects and side effects in silico. 

CYTOCAST DIGITAL TWIN Platform™

The CYTOCAST DIGITAL TWIN Platform™ is more than just a cell simulation system. It is a comprehensive framework that integrates multi-omics data, bioinformatics, and high-performance computing to simulate molecular and cellular dynamics. With the platform, researchers can move beyond traditional trial-and-error methods, making data-driven decisions that transform drug development and patient care. 

Core element: the CYTOCAST DIGITAL TWIN Cell™ 

The CYTOCAST DIGITAL TWIN Cell™ serves as the foundational element of the platform, designed to simulate cellular processes at an unprecedented scale and accuracy. By incorporating data from mass spectrometry,  and protein-protein interaction databases, the CYTOCAST DIGITAL TWIN Cell™ models the intricate molecular complexity of human cells.  

Expanding horizons: the CYTOCAST DIGITAL TWIN Patient™ and the CYTOCAST DIGITAL TWIN POPULATION™ 

The CYTOCAST DIGITAL TWIN Patient™ 

The CYTOCAST DIGITAL TWIN Patient™ is the centerpiece of Cytocast’s platform, excelling in side effect profiling of drugs. Built upon the foundation of the CYTOCAST DIGITAL TWIN Cell™, it simulates the molecular and cellular landscapes of patients with unparalleled precision. 

By integrating protein abundance, protein-protein interaction and several bioinformatics databases, the CYTOCAST DIGITAL TWIN Patient™ enables groundbreaking predictions for drug safety. The process encompasses deep-learning based drug-binding protein predictions, high-performance computational simulations across 15 tissue types, and side effect forecasting by an ML algorithm. This advanced modeling identifies complex interactions and pathways associated with potential side effects, significantly enhancing insights critical for pharmaceutical development and regulatory compliance. 

The CYTOCAST DIGITAL TWIN Population™ 

Looking to the future, the CYTOCAST DIGITAL TWIN Population™ aims to simulate the diversity of human populations by integrating large-scale genomic and demographic data. This capability allows researchers to: 

  • Correlate genetic variations (e.g., SNPs) with drug responses to refine patient stratification for clinical trials. 
  • Improve public health outcomes by modeling population-level responses to therapies. 
  • Support orphan drug development by simulating rare disease scenarios within defined subpopulations. 

CYTOCAST DIGITAL TWIN Platform™

The CYTOCAST DIGITAL TWIN PLATFORM™ operates through a streamlined four-step process: 

1. MODEL GENERATION

1. MODEL GENERATION

Construct detailed cellular models for different tissues using integrated multi-omics data and Cytocast's proprietary database.

2. DRUG SELECTION

2. DRUG SELECTION

Test drug candidates by selecting from a pre-defined library, providing your own molecule, or uploading custom drug-protein interaction data. The system allows the definition of any drug combinations as well.

3. SIMULATION OF THE MODEL

3. SIMULATION OF THE MODEL

Run parallelized simulations of up to 100 million molecules and their interactions across tissues to predict drug effects and side effects.

4. REPORTING

4. REPORTING

Generate actionable reports detailing protein interactions, cellular phenotype changes, and correlations to drug-induced effects.

Interested in a demo?

Contact us today to learn how the CYTOCAST DIGITAL TWIN Platform™ can revolutionize your R&D efforts and bring you closer to breakthroughs in drug safety and efficacy. 

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Impact on Drug Discovery and Development 

Here, you can discover how our technology can be utilized in the domains of drug discovery and development. To gain a deeper insight into the practical implementation of our technology visit our How We Do It page, which features our publications and details about collaborative research projects we have undertaken, or we are currently engaged in. 

The CYTOCAST DIGITAL TWIN Platform™ empowers researchers in academic and pharmaceutical settings to:  

  • Predict drug efficacy and toxicity earlier in the R&D process, reducing costs and time-to-market. 
  • Focus on safety profiling by simulating and understanding potential side effects, helping to mitigate risks during drug development. 
  • Address unmet medical needs through population-level insights, emphasizing side effect prediction and prevention. 

Simulation studies in cell biology are on the rise, and they are now being applied to drug discovery. Our company provides cutting-edge computational technology solutions that harness the power of the advanced Cytocast cell simulator, capable of modeling entire cells and cellular processes. In collaboration with another company, we have already validated our simulation platform through the examination of the effects and side effects of more than 100 drugs.

Cytocast’s key solutions in drug discovery and development:

  1. Early-Stage Drug Candidate Testing: Cell simulation can predict the effects and side effects of new drugs by modeling their interactions with specific cellular targets. This helps identify potential safety concerns early in the development process and guides further research into the drug's efficacy before advancing to clinical trials.
  2. Drug Repurposing: By simulating how a drug interacts with specific proteins, enzymes, or pathways within a cell, we can predict its effectiveness in treating a particular disease or condition. This approach can lead to the identification of drugs suitable for repurposing in treatments for diseases not previously indicated. It can aid in predicting the effects and side effects of existing drugs by modeling their interactions with specific proteins or cellular pathways, assisting in identifying potential drug-drug interactions and foreseeing variations in drug response across different patient populations.
  3. Drug Target Identification: Simulating the behavior of various proteins, genes, or signaling pathways within a cell can uncover new targets for drug development that were previously unknown.
  4. Drug Dosage and Delivery Optimization: Simulations can assist researchers in optimizing the dosage and delivery method of a drug by predicting its absorption, metabolism, and elimination by the body.
  5. Drug Safety Assessment: Simulating the effects of a drug on different cells and tissues can help to predict potential side effects or toxicity, enabling the early identification and resolution of safety concerns in the development process.
  6. Personalized Medicine: By simulating the behavior of cells from individual patients, researchers can devise personalized treatment plans tailored to each patient's unique genetic makeup and disease profile. This enhances the precision of treatment recommendations.
  7. Enhanced Decision-Making with Population Data Insights: Utilizing population data to correlate Single Nucleotide Polymorphisms (SNPs) with specific drug effects and side effects enables more precise drug recommendations for targeted patient populations. SNP data is employed to customize drug recommendations based on individual genetic profiles, thereby enhancing treatment efficacy and minimizing side effects.
  8. Orphan Drug Development: In silico cell simulation can be particularly valuable for predicting drug effects and side effects in the development of orphan drugs, which are designed to treat rare diseases with limited treatment options and small patient populations. This aids in more accurately estimating the potential benefits and risks of such drugs.
  9. Generic Drug Safety Assessment: Cell simulation can ensure that generic drugs are as safe and effective as the original medication

Future perspectives and collaboration 

As simulation studies in cell biology continue to grow, Cytocast is at the forefront of this transformation. By integrating the CYTOCAST DIGITAL TWIN Cell™, CYTOCAST DIGITAL TWIN Patient™ and CYTOCAST DIGITAL TWIN Population™ capabilities, the CYTOCAST DIGITAL TWIN Platform™ offers a unified, scalable approach to advancing precision medicine and global health.