Pauling gives you CRO-class computational capabilities in-house -- run docking, MD, and ADMET yourself in minutes, iterate in real time, keep all your data. A CRO engagement means sending specs, waiting weeks, paying $50K--$500K+ per project, and losing visibility into the workflow.
| Category | Pauling | CRO |
|---|---|---|
| Turnaround time | Minutes to hours (run jobs yourself) | Weeks to months (scoping, contracting, execution, reporting) |
| Cost per project | Pay-per-compute; screen 10M compounds for a fraction of CRO fees | $50K--$500K+ per engagement depending on scope |
| Iteration speed | Real-time -- adjust parameters and rerun instantly | Each iteration requires a new SOW or change order |
| Data ownership | All data stays in your account (private catalogs, owner_id) | Results delivered at project end; raw data retention varies |
| Workflow transparency | Full visibility -- jobs dashboard tracks every parameter and output | Black box; you see the final report, not the methodology details |
| Scale | 10M+ compounds on auto-scaling cloud infrastructure | Limited by CRO capacity and your budget per engagement |
| Customization | Configure docking parameters, MD settings, ADMET filters directly | Specify requirements upfront; mid-project changes are costly |
| In-house expertise building | Your team learns comp chem by running real calculations | Knowledge stays with the CRO |
| Reproducibility | Every job logged with full inputs, parameters, outputs | Reproducibility depends on CRO documentation quality |
| Domain expertise | AI-guided workflows; physics-based tools (UniDock, GROMACS, P2Rank) | Experienced computational chemists with domain judgment |
| Proprietary methods | Open, validated engines (Vina scoring, GROMACS force fields) | Some CROs offer proprietary scoring functions or ML models |
| Confidentiality | Private cloud infrastructure; your data is isolated | Governed by CDA/NDA; shared infrastructure risk |