Arctoris was featured in a BioPharma Trend case study exploring how the Ulysses® platform combines closed-loop robotics and machine learning to industrialise drug discovery, generating datasets with up to 100 times more data points per assay than industry standard, and compressing Design-Make-Test-Analyse cycles from weeks to days.
The case study delves into how Ulysses® conducts fully automated wet lab experiments across biochemistry, biophysics, and molecular and cellular biology, producing ultra-rapid, large-scale and fully annotated datasets. These feed into automated analytical pipelines that train machine learning models for small molecule optimisation, enabling more effective leaps in molecular design and faster progression from hit to candidate.
Arctoris’ growing portfolio of external partnerships is also highlighted, with biotech, pharma and AI drug discovery companies across the US, Europe and Asia-Pacific leveraging Ulysses® to accelerate programmes across target validation, hit identification, hit-to-lead progression and lead optimisation. Spotlighted in particular is the collaboration with Evariste Technologies, a London-based AI drug discovery company. Combining Arctoris’ wet lab data generation capabilities with Evariste’s machine learning-enabled molecular design, the two organisations progressed from target selection to several qualified lead series in non-small cell lung cancer within just six months, a compelling demonstration of what becomes possible when automation and AI work in concert.
