T3QUBO-EPharmaceuticals & Healthcare
Protein–ligand docking / binding affinity
Molecular docking as optimization — heavily encoding-taxed; classical + ML strong.
Sector
Drug discovery
Likely buyer
Pharma R&D
Hardware gate
Classical + ML strong
Taxonomy
cost-prohibitive × accelerating
No live demo yet — docking embeds poorly; classical + ML competitive. The paradigm-honest position: this use case is demonstrated with crossover analysis, not theater.
GTM talk track
Say classical/ML.
OGSM — product operating frame
Objective
Watching brief.
Goals
- Monitor
Strategies
- Monitor
Measures
- N/A
OBR — outcome-based roadmap
| Horizon | Outcome we create | Buyer behavior change | Result we measure |
|---|---|---|---|
| Now | Educate | Prospect runs the emulated demo on their own instance data | Booked QPU-time evaluation or paid pilot |
| Next | Revisit | Prospect co-designs a scoped benchmark against their incumbent solver | Documented crossover curve; expansion to production instances |
| Later | Reassess | Prospect standardizes on the workflow or buys an on-prem system | Recurring QPU consumption / system sale; reference case |
Fit notes (honesty gate)
Heavily encoding-taxed.
Ready to run this on real hardware?
Emulation-verified today — the same program runs on a Pasqal QPU unchanged.