The company behind Ambrego was founded
three years ago in 2018.
Ambrego is actively driving drug research
with its own pipelines and research team.
We have access to a very cost-efficient
computing network to run simulations.
At the core of our optimized pipeline, we perform docking simulations of a drug's API with proteins of the Protein Data Bank archive. We utilize machine learning (AI) models to efficiently find the right proteins to concentrate on. The docking simulation is done without the need to bring the protein or the API into specific conformations, again with help of machine learning models.
With the help of heuristics and AI, our research team analyses the simulation results for safety and adverse reactions. Also, they run additional simulations or do lab tests where needed, based on pre-defined processes. At the end of the process, a detailed report is written and presented to the customer.
Our approach can visualize the reason for adverse reactions, allowing molecules to be optimized for less adverse reactions instead of simply being discarded. Promising molecules which were already discarded because of adverse reactions we can also analyse, to potentially put them back into the process.
We can identify which preclinical studies and human trials will likely fail before they start. Besides reducing the cost risk, this reduces the total amount of morally questionable animal testing and results in less harmed humans in the trials. In some cases we find risks which stay undetected in the trials.