Cytocast's Simulated Cell is a high-performance computing tool that utilizes an agent-based stochastic simulation algorithm to create virtual cell models. These simulations focus on the interactions of proteins within the cell, allowing for both qualitative and quantitative insights into the complexome of the simulated cell. Cytocast's Simulated Cell is based on a comprehensive cell simulator that integrates bioinformatics databases into a computer model to understand the impact of drug-related perturbations and predict how drugs can modify cellular health on 17 tissue types and cell lines. The main advantage of this technology is its ability to estimate drug effectiveness and side effects during the R&D phase, saving time and money while increasing the likelihood of success in clinical trials. By predicting drug effects and side effects in silico on multiple tissues and cell lines, Cytocast can enable researchers to make informed decisions about drug candidates before starting clinical trials. The process of Cytocast's Simulated Cell involves four main steps: model generation, drug selection, simulation of the model, and reporting. It generates individual cell models from various tissues by integrating molecular data, supports drug testing with pre-defined drugs or custom drug-protein interaction data, and uses a parallelized simulation algorithm to evaluate the effects of each drug on requested tissue types. The resulting reports identify the most affected protein complexes and interactions, as well as the cellular phenotype changes caused by the drug in each tissue type.

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