Artificial Intelligence Driven Autonomous Lab by IBM & Chemspeed

Diverse collections of well-defined glycans are needed to investigate the molecular mechanisms by which these biomolecules mediate biological and disease processes. Several automation approaches have been introduced to accelerate the enzymatic synthesis of complex glycans. These methodologies have, however, provided only relatively simple oligosaccharides due to limitations of glycosyl transferase selectivity.

The design and discovery of porous materials have become a central theme in materials science, driven by their applications in gas storage, separation, carbon capture, and catalysis. Rapid advances in synthetic chemistry, particularly in metal–organic frameworks, porous organic cages, and conjugated microporous polymers, have enabled the generation of increasingly large and diverse material libraries.

Pharmaceuticals increasing complexity requires longer synthesis with unique processes for each step, increasing the number of experiments to develop robust sustainable processes. The time to develop these processes is getting shorter, and automation can support the growing need to efficiently perform more experiments.