Aggregate procurement spend across molecule, origin, and supplier dimensions. Surface concentration, leverage, and category-management opportunities.
The PharmaDB warehouse tracks $25.9B in declared API trade across 1,817 active exporters and 1,693 distinct molecules in the trailing 24 months. Hetero Labs leads with $1.7B across 162 molecules; Cadila, MSN, Cipla, and Dr Reddy's all clear $700M. Read this as the supply-side spend cube — the inventory a buyer benchmarks their own sourcing against.
| # | Exporter | Origin | Cumulative trade | Molecules | Share |
|---|---|---|---|---|---|
| 1 | Hetero Labs | IN · Hyderabad | 162 molecules | $1.74B | VAI |
| 2 | Cadila | IN · Ahmedabad | 153 molecules | $1.13B | NAI |
| 3 | MSN Life Sciences | IN · Hyderabad | 129 molecules | $972M | NAI |
| 4 | Cipla | IN · Mumbai | 118 molecules | $786M | VAI |
| 5 | Dr Reddy's Laboratories | IN · Hyderabad | 100 molecules | $750M | VAI |
The molecules you actively source. Pull from your internal ERP or define manually. PharmaDB matches molecules to its catalog.
Spend aggregated across molecule × origin × supplier dimensions. Concentration metrics computed per axis.
Citation-anchored brief with the top suppliers, the molecules where you have leverage, and the categories flagged for negotiation.
Spend cube across molecule × origin × supplier. Slice by any axis or any combination. The full inventory of your procurement.
Molecules with concentrated spend but fragmented supplier base are flagged. These are the categories where consolidation drives leverage.
Suppliers holding over 30% of category spend, origins holding over 60% of a molecule's supply — surfaced as risk markers.
Built from trade aggregates. Internal ERP optional — when supplied, cross-validated against the warehouse for completeness.
A real chat thread in PharmaDB. Type a question, the AI agent runs the tools, the answer lands as a saveable note.
pharmagraph_query Top ten exporters · trailing 24 months · molecule count per exporter shows category-breadth, not depth.
The spend cube is the category-management foundation. PharmaDB aggregates procurement spend across molecule × origin × supplier, computes concentration and leverage metrics, and surfaces the categories where consolidation or diversification drives value. The view is company_trade_exports_by_molecule; the join is to global_companies and the molecule catalog.
Three primary dimensions: molecule, origin country, supplier. Spend is aggregated from customs export records (when ERP is not supplied) or cross-validated against ERP transactions (when supplied). The cube refreshes on the same cadence as the underlying tables.
No. PharmaDB can build the cube from trade aggregates alone, using your supplier list as the entity filter. ERP upload improves completeness — internal small-volume transactions not in customs become visible — but is optional.
Spend concentration on a molecule (your spend divided by the molecule's global supplier base size) versus supplier fragmentation (your top supplier's share). Categories where you spend a lot but no single supplier dominates are flagged as leverage opportunities.
Two thresholds: a supplier holding over 30% of category spend triggers a supplier concentration flag. An origin country holding over 60% of a molecule's supply triggers a geographic concentration flag. Both flags surface inline with the affected molecules.
Trade aggregates refresh weekly. The cube recomputes on every refresh. ERP-supplied transactions are matched to the cube at upload; the catalog row carries the refresh timestamp.
Yes. The same methodology applies to API, FDF, and intermediates procurement. FDF lanes add pack-size normalisation to the spend calculation; the cube remains the same shape.
Bring the molecule, the lane, or the supplier you're sourcing this week. The AI agent runs it on PharmaDB in 30 minutes. You keep the brief.