Quantum-Centric Data Driven R&D with focus on Life Science
summary
Capgemini and GSK implement an end-to-end workflow that runs Hamiltonian time evolution on quantum circuits for small molecular fragments to produce quantum-derived fragment embeddings which are fed into existing ML pipelines. The concrete claim: these quantum features change classical outcomes — a GSK clustering that previously split two behaviorally identical molecules now clustered two behaviorally identical molecules together. The prototype targets reactivity of covalent inhibitors, runs on noisy small devices today, is vendor-agnostic, and already spawns follow-up projects in batteries, carbon capture and other chemistry-heavy verticals.
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chapters (13)
- 0:00Introduction
- 1:07Capgemini’s quantum approach
- 2:35Quantum adoption challenges
- 4:23Quantum R&D roots
- 5:50Chemistry focus for quantum
- 6:54Quantum-centric principles
- 8:39Three-part quantum approach
- 10:47Quantum vs classical HPC
- 12:11GSK covalent inhibitors
- 13:56Quantum improving algorithms
- 15:19Future plans and verticals
- 16:24Call for collaboration
- 17:07Q&A
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