Treat the patient not the statistics

Drug development is a lengthy, costly, and complex process, and the heterogeneity of patient population further increases the uncertainty of a particular drug or drug combination to succeed.

Cytocast revolutionizes the drug discovery pipeline through predictive and personalized computer simulations of large-scale biological processes.
Our software utilizes various types of molecular information, called multi-omics data, collected from diseased and healthy cells.

The tool integrates personalized data with the existing knowledge on how molecules interact to perform their functions forming structures called macromolecular complexes, which ultimately perform the major functions in a cell.

Looking at cellular behavior from a large-scale point of view, we can identify global variations between healthy cells and those affected by a disease, which are typically impossible to observe by looking at a single component of a cell.

Our simulation tool allows us to categorize the key changes in macromolecular complexes that might cause the observed behavior of diseased cells and through this it can give suggestions on how this malfunctioning state can be repaired.

This will help in identifying the best drugs to be used.

Once a possible drug or molecular target is identified, Cytocast can simulate the behavior of the biological systems with various doses of a drug to test the efficacy of the suggested treatment.

For instance, we successfully predicted that Metformin, a diabetes drug, can affect the way DNA is packed, which has a profound effect on many other biological functions.

The table below outlines how Cytocast can impact the full drug discovery and development pipeline.

DRUG TESTING Years 2-4 weeks
CLINICAL TRIALS Several years and often resulting in unsuccessful product Months: Testing multiple drugs and selecting the best for clinical trial.


  1. Biological datasets collected from patients are used as input

  2. Cytocast simulates the behaviour of biological systems based on the input data and predicts targets for novel therapies

  3. The effect of drugs is simulated on the same biological systems to predict the OUTCOME of the therapy