IQVIA's $22B top-down 2023 US T2D drug-spend figure and a 29.7M-diagnosed-patient bottom-up build converge, but the per-class revenue split behind that total is a gap this model names rather than fills with invented numbers.
Two sizing methods anchor this model, and they are deliberately not blended into a single unsourced figure. The top-down method starts from IQVIA's reported 2023 US type 2 diabetes drug market spend of approximately $22 billion, a figure that already nets out the full class mix (metformin, SGLT2 inhibitors, DPP-4 inhibitors, GLP-1 receptor agonists, and insulin used in T2D) at the market level. The bottom-up method starts from patient count: an estimated 38.4 million Americans have diabetes, of whom roughly 29.7 million are diagnosed, and applying a treated-patient share against published per-patient pricing across major drug classes produces an independent estimate that lands in a comparable range to the top-down figure.
The broader disease burden puts the $22B drug-spend figure in context rather than inflating it. The American Diabetes Association's 2022 cost-of-diabetes estimate puts total US economic cost, direct medical costs plus reduced productivity, at $412.9 billion, meaning pharmaceutical spend on T2D drugs specifically is a fraction of the disease's total economic footprint. That distinction matters for any sizing exercise: the addressable pharmaceutical market is $22B, not $412.9B, and conflating the two overstates the commercial opportunity by an order of magnitude.
Where this model deliberately stops short is the per-class revenue split within the $22B total. Tirzepatide's 41% share of new GLP-1 starts is a directional signal about where incremental prescribing is going, not a revenue-share figure, since script share and dollar share diverge once list price, rebate depth, and dosing frequency differ across agents. Building a per-class dollar breakdown would require prescription-volume and net-price data this model does not yet have verified; it is flagged here as the specific gap a future update should close, rather than backfilled with an estimate presented as fact.
US type 2 diabetes sizing — top-down drug spend versus bottom-up patient-count build
| Sizing Method | Basis | Estimate / Figure | Source |
|---|---|---|---|
| Top-down (drug spend) | US T2D pharmaceutical market, 2023 | ~$22B | IQVIA |
| Bottom-up (patient count) | Diagnosed patient base × treated share × per-patient pricing | 38.4M prevalence / 29.7M diagnosed | CDC/published diabetes surveillance estimates |
| Disease burden (context, not market size) | Total direct + indirect economic cost, 2022 | $412.9B | American Diabetes Association |
| Class-share directional signal | Share of new GLP-1 starts | Tirzepatide 41% | Published prescribing-trend data |
Sources: IQVIA US pharmaceutical market data, 2023; CDC and published US diabetes prevalence/diagnosis surveillance estimates; American Diabetes Association, Economic Costs of Diabetes in the U.S. in 2022; published GLP-1 new-start prescribing-trend data.
What this model answers
Every section answers a named commercial question your team is asking, scoped to your asset.
Delivers
- IQVIA top-down methodology and the $22B figure's scope
- Bottom-up patient-count-times-pricing build across major T2D drug classes
- The triangulation range where both methods agree, and the confidence band around it
Delivers
- The distinction between total disease economic burden and pharmaceutical market spend
- Why $22B, not $412.9B, is the correct sizing anchor for a drug-focused forecast
- Guidance on where the ADA figure is useful context versus where it would overstate opportunity
Delivers
- The distinction between script-share and dollar-share signals
- What data (prescription volume, net price by class) is needed to close the per-class revenue gap
- This model's explicit flag of that gap as a scoped item for a future update, not an invented figure
Custom model delivered in 72 hours.
Commission This ModelWhat's inside
- Why triangulating top-down and bottom-up methods, not picking one, is the assumption the rest of the model rests on
- Pressure-tested against the $22B IQVIA figure before the bottom-up build is run
- IQVIA's reported $22B 2023 US T2D drug market spend and its class-mix scope
- What the top-down figure includes and excludes
- 38.4M prevalence and 29.7M diagnosed patient base build
- Treated-patient share and per-patient pricing assumptions across major drug classes
- The $412.9B 2022 ADA total economic cost of diabetes
- Why this is disease burden context, not the addressable pharmaceutical market
- Where the top-down and bottom-up methods converge
- Confidence range around the triangulated total
- Tirzepatide's 41% share of new GLP-1 starts as a script-share, not dollar-share, indicator
- The per-class revenue split flagged as a known gap for a future update
- Which assumption moves the triangulated total most: treated-patient share, per-patient pricing, or class mix
- The open sizing questions your team must close before the number is used in planning, including the per-class revenue gap
Included with every brief
How AXLRx builds this model
Prepared by MoatRx analysts.
Every AXLRx market sizing model triangulates at least two independent methods, here top-down drug spend and bottom-up patient-count, before accepting a market total. This is explicitly a sizing model (static market-spend estimate), distinct from a Pricing Strategy or Patient Flow model.
Type 2 diabetes US sizing sources: IQVIA 2023 US pharmaceutical market data, CDC/published diabetes prevalence and diagnosis surveillance estimates, the American Diabetes Association's 2022 cost-of-diabetes report, and published GLP-1 new-start prescribing-trend data.
- IQVIA's $22B 2023 US T2D drug market spend figure verified against published IQVIA market data
- 38.4M prevalence and 29.7M diagnosed patient figures verified against CDC/published US diabetes surveillance estimates
- The $412.9B ADA total economic cost figure verified against the American Diabetes Association's 2022 cost-of-diabetes report
- Tirzepatide's 41% new-GLP-1-start share verified against published prescribing-trend data; flagged explicitly as a script-share signal, not a revenue-share estimate
Frequently asked questions
Commission this model
AXLRx delivers cardiometabolic market sizing models built for forecasting and strategy teams sizing the US type 2 diabetes opportunity. Custom model in 72 hours.
Specify your indication, market, and cohort or class-level definition.
AXLRx analyst confirms triangulation methods and comparator set, including any per-class revenue scope, before building.
Research-verified sizing model in 72 hours with optional analyst readout.