Rapid Science with Machine Learning

In silico trials use computational models to simulate human physiology, disease progression, and drug effects in virtual populations.

Our advanced and proven  

PK/PD models simulate the relationship between drug concentration (PK) and its therapeutic effect (PD) in virtual systems. 

AI and machine learning (ML) models predict our trial outcomes by analyzing large datasets from prior trials, real-world evidence, or preclinical studies.

We can simulate bioequivalence studies to compare generic and reference drugs using computational models.

We use simulations to design and optimize adaptive clinical trials, adjusting parameters like dose or sample size based on interim results.