We have an international network of academic and industrial partners, collaborating research laboratories, and customers that trust our technology. We constantly seek mission-aligned partners to advance our discovery platform.
Our discovery platform couples enzyme kinetics with branches of deep reinforcement learning overlaid onto first principles of physics and biology to address problems and unmet needs in the real-time simulation of genome-scale metabolic networks.
By leveraging artificial intelligence and digital twin prototyping, we develop digital replicas of human cells and offer a cloud platform to conduct computational simulations for predicting the effect of new drugs on cellular metabolism.
Here we show our predictive analysis on a model system of human erythrocyte (red blood cell) metabolism.
Our proprietary algorithms are rooted in biochemistry and are incorporated in a suite of powerful computational tools based on artificial intelligence that ensure full compliance with non-equilibrium thermodynamics across the entire modeling pipeline.
Kinetic models are the ultimate tools for simulating biochemistry because they can predict exact quantities for any variable in the system, thereby making the implementation of single-cell or multicellular digital twin possible.
We strive to provide in silico solutions for drug discovery for both industry and academia. Find out how your R&D gets value from day one. Our AI-powered cloud-computing platform is cost-effective and always up-to-date.
Gain insights into metabolic pathway optimization, target identification/validation, biomarker determination, and more for Drug Discovery, Synthetic Biology, Precision Medicine, as well as Basic and Translational Research.