IBM Expands AI-Driven Materials Discovery Capabilities, Signs New Industry Collaborations, Sandmeyer Award 2022
IBM RoboRXN, a cloud-based AI-automated lab, designed to enable a new era of fast-track molecular discovery, now supports proprietary datasets and green chemistry combined with Chemspeed’s automated synthesis solutions.
Launched in 2018, RXN for Chemistry – the AI behind RoboRXN – has been used by more than 29,000 users and accumulated over five million reaction predictions in efforts to streamline the scientific process around discovery and creation of new materials.
While RoboRXN leverages cutting-edge cloud and AI capabilities to improve material discovery, it is essential this process be secure for organizations working with proprietary data. Additionally, there is a growing need to improve sustainability throughout manufacturing processes, including the chemical reactions that convert raw materials into finished products.
To address these challenges, IBM offers two new capabilities in RoboRXN:
- Security and customization: new cloud capabilities allow users to train RXN directly with sensitive datasets for more secure experimentation and customization of prediction models using proprietary knowledge.
- Greener chemical processes: new AI model scan now assist chemists in the rapid prediction and identification of more environmentally-friendly enzymes. Enzymes are highly complex bio molecules needed to convert materials into products such as paper, cosmetics, pharmaceuticals and flavors.
IBM is also announcing new collaborations with Atinary, Arctoris, Chemspeed Technologies AG, Syngenta, and Thieme Chemistry to continue RoboRXN’s impact in accelerating the synthesis and testing of new materials across many industries.
Sandmeyer Award 2022
RXN for Chemistry Project Team from IBM Research Zurich, namely
Alain Vaucher, Daniel Probst, Philippe Schwaller, Theophile Gaudin, Teodoro Laino, Matteo Manica, Alessandra Toniato, Federico Zipoli, Antonio Cardinale, Alessandro Castrogiovanni, Heiko Wolf, Aleksandros Sobczyk, Joppe Geluykens
for their important scientific breakthrough in the digitalization of synthetic organic chemistry that helps to improve digital workflows with state-of-the-art machine learning technologies.