US SMA prevalence runs 8,000-10,000 patients, and newborn screening has rebuilt the funnel's entry point around a 300-infant-a-year pre-symptomatic pool.
US SMA prevalence is estimated at 8,000-10,000 patients, with incidence near 1 in 10,000 live births (Prior TW, Genet Med 2010, PMID 20057317). The type distribution splits severity into four groups defined by SMN2 copy number: Type 1 accounts for roughly 60 percent of diagnoses, Type 2 for 27 percent, Type 3 for 13 percent, and Type 4 for under 5 percent. That skew toward the most severe phenotype is exactly what a patient flow model has to capture before treatment-eligible sizing means anything, since Type 1's historically fatal natural history, median survival of about 13.6 months untreated, makes early identification the single largest lever on outcome.
Universal newborn screening has rebuilt the funnel's entry point. SMA was added to the federal Recommended Uniform Screening Panel in 2018, and all 50 states have screened since 2023, identifying roughly 300 infants a year before symptoms emerge. This pre-symptomatic population is where onasemnogene abeparvovec achieves near-normal motor development, and it is now the primary route into gene-therapy eligibility rather than symptomatic Type 1 diagnosis. On the treatment side, our model anchors sizing against the observed 500-700 US children who received Zolgensma between 2019 and 2023, a bottom-up validation check against the top-down prevalence-and-type-split estimate, so your team can defend the funnel from both directions in the first forecast review.
US spinal muscular atrophy funnel — from prevalence to the Zolgensma on-therapy anchor
| Funnel Stage | Population | Source |
|---|---|---|
| US SMA prevalence (all types) | 8,000-10,000 | Prior TW, Genet Med 2010 (PMID 20057317) |
| Type 1 share of diagnoses (most severe) | ~60% | SMN2 copy-number type distribution |
| Newborn-screening-identified pre-symptomatic infants | ~300/yr | RUSP 2018; all 50 states screening since 2023 |
| On-therapy anchor: Zolgensma-treated US children, 2019-2023 | 500-700 | Strauss KA et al., Mol Ther 2023; Cure SMA gene therapy registry |
Sources: Prior TW, Genetics in Medicine 2010 (PMID 20057317); federal Recommended Uniform Screening Panel (RUSP) and CureSMA newborn-screening tracking; Strauss KA et al., Molecular Therapy 2023; Cure SMA gene therapy registry.
What this model answers
Every section answers a named commercial question your team is asking, scoped to your asset.
Delivers
- Prevalence-based top-down sizing (8,000-10,000 patients)
- NBS-identified pre-symptomatic infants (~300/yr, all 50 states since 2023)
- why pre-symptomatic identification is now the primary gene-therapy entry route rather than symptomatic Type 1 diagnosis
Delivers
- Type 1/2/3/4 share of diagnoses (60%/27%/13%/<5%)
- SMN2 copy number as the severity and eligibility driver
- how age and weight criteria gate gene-therapy eligibility within each type
Delivers
- 8-sheet structure (Strategic Context, Inputs, Model, Projections, Sensitivity, References, Market Context, QC)
- the observed on-therapy cohort as a bottom-up check against top-down prevalence sizing
- source citation per conversion step
Custom model delivered in 72 hours.
Commission This ModelWhat's inside
- Why pre-symptomatic identification, not symptomatic diagnosis, sets the modern addressable population
- Pressure-tested against the newborn-screening coverage trend before the rest of the model is built out
- 8,000-10,000 US SMA patients; incidence ~1 in 10,000 live births
- Demographic distribution across the Type 1-4 spectrum
- Type distribution by SMN2 copy number (60%/27%/13%/<5%)
- Newborn-screening identification pathway and the RUSP timeline
- ~300/yr NBS-identified infants since all-50-state screening in 2023
- Pre-symptomatic vs symptomatic segmentation and its commercial implications
- Age and weight criteria gating gene-therapy eligibility
- Three-mechanism eligibility across the treated population
- Which assumptions move the eligible pool most
- Scenario ranges across the top-down and bottom-up estimates
- Patient volume by horizon under conservative, base, and aggressive scenarios
- Revenue translation inputs
- The open questions your forecasting team must close before the model is finalised
- Structured for an internal forecast-review session
Included with every brief
How AXLRx builds this model
Prepared by MoatRx analysts.
Every AXLRx patient flow model is built on a five-layer funnel: population and disease burden (E1), diagnosis and specialist capture (E2), subtype and severity eligibility (E3), market access (E4), then Year 1-3-5 projections across three scenarios. For an ultra-rare, birth-cohort-anchored disease like SMA, the funnel starts from prevalence and incidence rather than a large diagnosed population, and newborn screening functions as the E2 capture mechanism rather than a specialist referral pathway.
US SMA sources: Prior TW, Genetics in Medicine 2010, for prevalence and genetics; the federal Recommended Uniform Screening Panel and CureSMA for newborn-screening coverage; and Strauss KA et al., Molecular Therapy 2023, together with the Cure SMA gene therapy registry, for the observed Zolgensma-treated cohort used as this model's bottom-up validation anchor.
- US SMA prevalence and incidence verified against Prior TW, Genet Med 2010 (PMID 20057317)
- Type 1-4 severity distribution verified against the published SMN2 copy-number-to-phenotype correlation
- Newborn-screening coverage (RUSP 2018; all 50 states by 2023) and annual pre-symptomatic identification volume verified against CureSMA and the federal RUSP
- 500-700-patient Zolgensma on-therapy cohort verified against Strauss KA et al., Mol Ther 2023, and the Cure SMA gene therapy registry
Frequently asked questions
Commission this model
AXLRx delivers rare disease patient flow models built for forecasting and launch teams sizing the US spinal muscular atrophy opportunity. Custom model in 72 hours.
Specify your indication, market, and cohort definition.
AXLRx analyst confirms funnel scope and comparator set before building.
Research-verified patient flow model in 72 hours with optional analyst readout.