Belgian drugmaker UCB is working with AI startup Cradle to design new antibody drugs more efficiently, and the collaboration could eventually expand to other programs across UCB's pipeline.
AI drug design · UCB × Cradle
UCB teams up with Cradle to speed up early antibody design
The Brussels drugmaker is using Cradle's AI tools to narrow the field of candidate antibodies before lab testing. The collaboration could later extend to other programs across UCB's pipeline.
Where AI is applied: the early stage
Researchers typically test large numbers of candidate molecules before choosing the most promising ones for further study.
Step 1
Candidate molecules
A large pool of possible antibodies
→
Step 2 · AI
Computational narrowing
Models help shrink the search space
→
Step 3
Laboratory screening
Fewer candidates to test in the lab
→
Step 4
Most promising picks
Advance to further study
The case for the approach
Computational models can narrow the search space.
Fewer candidates may need laboratory screening.
Potential reductions in time and cost of screening.
The caution from observers
AI-designed molecules must pass the same preclinical and clinical testing.
Early computational promise does not guarantee approval.
What is still unknown
Key terms and results have not yet been disclosed.
Financial terms
Not disclosed
Program timelines
No detailed schedule for specific programs
Technical workflow
Which Cradle models will be used is not detailed
Key questions: whether the work yields candidates that enter clinical development, and whether the collaboration expands as suggested.
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