IBM Research and Arctoris are investigating the application of AI and automation to accelerate closed loop molecule discovery.
IBM Research has developed RXN for Chemistry, an online platform leveraging Natural Language Processing (NLP) architectures to automate synthetic chemistry. Representing chemical reactions via SMILES (Simplified Molecular Input Line Entry System), the system is designed to perform reaction predictions using its AI. Optimised synthetic routes are then used as input for RoboRXN, an automated platform for molecule synthesis.
Arctoris’ Ulysses, is an automated platform for drug discovery research. The platform leverages robotic experiment execution and digital data capture technologies across cell and molecular biology and biochemistry/biophysics.
The two platforms are being combined in a research collaboration that will see new small molecule inhibitors for undisclosed targets being designed, made, tested, and analysed (DMTA) in an autonomous, closed loop approach. IBM Research will design and synthesise novel chemical matter to be profiled and evaluated by Arctoris, with the resulting data informing the subsequent iteration of the DMTA cycle.
Thomas Fleming, Arctoris Co-Founder & COO, said: “The future of drug discovery is computational, with AI and robotics paving the way for better treatments to reach patients sooner. We are excited about partnering with IBM Research on a world-first closed loop drug discovery project bringing together two leaders in the field of AI and robotics-powered drug discovery.
Dr Teodoro Laino, Distinguished Scientist at IBM Research Europe – Zurich, said: “This collaboration is a great example of the enablement that AI, Cloud and Automation can have in the space of material design. The integration between the two complementary technologies reveals how it is more and more important in R&D to turn great research into great viable products.”