CRIWeighted
68
Ultra-rarePopulation
82
DiagnosticInfra
74
ReferralLeakage
68
AwarenessPhysician
63
AttritionPatient
59
Scoring Engine
Patient Demand · Signal Gauges
82
Ultra-rare
Population
74
Diagnostic
Infra
68
Referral
Leakage
71
Late Dx
Dependency
63
Awareness
Physician
59
Attrition
Patient
Signal Radar
Patient Demand Profile vs. Cohort Median
Risk— this therapyBase— cohort median (55)
Benchmarked against the cohort median (55) of CGT launches sharing modality & indication. This therapy runs +11 vs. cohort across 10 Patient Demand signals — 8 elevated, 2 below cohort. Largest gap: Ultra-rare patient population (+27). Strongest area: Competing treatment paradigms (-8).
Patient Demand Trajectory
Identified Patients vs Attrition Pressure · 36 mo
Identified Attrition
Signal Intensity
Patient Demand · 10 Signals
Ultra-rare patient population
82
Weak diagnostic infrastructure
74
Referral leakage
68
Late-stage diagnosis dependency
71
Low physician awareness
63
High patient attrition
59
Competing treatment paradigms
47
Eligibility restriction burden
66
Low epidemiological density
78
Patient travel burden
54
LowHigh
Failure Similarity Engine
Patient Demand failures most similar to yours:
Zynteglo
Ultra-rare · β-thal · Demand shortfall
72%
Skysona
Late dx · CALD · Referral collapse
65%
Mustang MB-207
Low density · SCID · Attrition-driven exit
58%
Glybera
Ultra-rare · LPLD · Zero uptake
51%
Why: ultra-rare epidemiology, weak diagnostic infrastructure, and high referral leakage — patterns shared with prior CGT launches that failed to convert addressable patients into treated patients.