The healthcare and pharmaceutical industries are fundamentally broken - it takes 10-15 years to bring a new drug to market after billions of dollars of inefficient investment. Using software, data, AI/ML, and solid engineering principles, alongside a team of knowledgeable PhDs from the field, drug development effectiveness can be dramatically increased, and more human lives can be saved.
Providing efficient and accurate drug insights through AI-enabled virtual simulations of human and animal biology.
We've built a computational platform for AI-enabled simulations of human and animal physiological phenomena. We aim to enable users to conduct hypothesis-driven research across the healthcare field, focusing on high impact areas such as drug development and personal health.
Our computational platform integrates mechanistic models of in vivo functions - such as interactions between xenobiotics, organ functions, and physics-based molecular dynamics - with the big data applicability of self-learning artificial intelligence / machine learning algorithms.
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