Atomwise

Atomwise's journey began in 2012, born from the minds of Abraham Heifets, Izhar Wallach, and Alexander Levy, who envisioned a way to dramatically accelerate the painstaking process of drug discovery. They were among the pioneers in applying deep learning, specifically convolutional neural networks (CNNs), to the complex challenge of identifying how small molecules interact with proteins – a critical step in finding new medicines. This innovative approach, embodied in their AtomNet® platform, marked a significant departure from traditional, often serendipitous, drug discovery methods. Instead of relying solely on extensive and costly physical screening of compounds, Atomwise introduced a more rational, structure-based search, leveraging artificial intelligence to predict molecular interactions with unprecedented speed and accuracy.

The early years were focused on refining this groundbreaking technology and demonstrating its potential. Atomwise's AtomNet® platform was engineered to sift through billions of virtual compounds, learning the intricate patterns of molecular recognition much like AI learns to identify objects in images. This capability promised to unlock previously 'undruggable' targets – proteins implicated in diseases that had resisted conventional drug development efforts. The company actively sought collaborations, partnering with academic institutions, research hospitals, and pharmaceutical companies worldwide. These partnerships not only validated the AtomNet® technology across a diverse range of disease targets but also enriched the platform with vast amounts of experimental data, further honing its predictive power. Over time, Atomwise has evolved from primarily being a technology provider to also developing its own pipeline of potential drug candidates, focusing on areas with high unmet medical need. Their commitment to making 'better medicines, faster' continues to drive their expansion and innovation in the field of AI-driven drug discovery, aiming to transform the landscape of pharmaceutical research and development.