Resources

Dr. Stephen Buchwald Joins Atinary’s Advisory Board

Atinary welcomes Dr. Stephen Buchwald, pioneering chemist behind Buchwald–Hartwig reaction, to advance AI-driven molecular discovery and innovation.

Atinary and Chemspeed teaming up for Self-Driving Labs

Atinary and Chemspeed are teaming up to accelerate R&D with AI and automation. Their no-code AI and automation platforms are now fully integrated, enabling self-driving labs with closed-loop optimization. Live demos launch in Basel (Q3 2025) and Boston (Q4 2025), showcasing faster, smarter experimentation.

Harnessing AI to Accelerate Breakthroughs in Metal-Based Antibiotic Discovery

Atinary and Dr. Angelo Frei’s lab at the University of York secure funding to revolutionize metalloantibiotic discovery, leveraging AI and high-throughput screening to combat antimicrobial resistance.

Upcoming Webinar: DMTA Innovation at Takeda

Join our webinar to explore how Takeda is accelerating chemical R&D with AI, automation, and HTE—paving the way for self-driving labs.

Atinary adds artificial chemical intelligence expert to its Scientific Advisory Board

Atinary welcomes Professor Philippe Schwaller to its Scientific Advisory Board to advance AI-driven molecular discovery and Self-Driving Labs™ technology.

Advancing T Cell Engineering with AI and Self-Driving Lab technology

Atinary collaborates with the lab of Prof. Rogelio Hernández-López at Stanford University to advance T cell engineering using AI, optimizing synthetic circuits for safer, more effective cell therapies.

New machine learning research article from Atinary

Atinary announces their latest research on Multi-fidelity Optimization (MFBO), a machine learning technique that optimizes several information sources with different fidelities.

New publication for Atinary and IBM Research

?? Our latest article, a collaboration between Atinary & IBM Research, was published in the May 2024 issue of Chemical Science from the Royal Society of Chemistry!

New publication for Atinary in Chimia

?? Our latest article describes a framework and lay out the key technologies to accelerate R&D and optimize experiment planning.