INSM vs IRON

Insmed Incorporated vs Disc Medicine, Inc. — Valuation Comparison 2026

INSM

Pharmaceutical Preparations
Insmed Incorporated
Quality
4.0
out of 10
Value Trap
18
SAFE
Price
$106.91
Last close
Models
11/13
Active
VS

IRON

Pharmaceutical Preparations
Disc Medicine, Inc.
Quality
4.2
out of 10
Value Trap
12
SAFE
Price
$69.57
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType INSM Fair ValueINSM Upside IRON Fair ValueIRON Upside
Bayesian DCF Intrinsic $36.40 -66.0% $20.84 -70.0%
Earnings Power Value Intrinsic $64.56 -52.2% $32.12 -53.3%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for INSM vs IRON — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

INSM vs IRON — Which Stock Is More Undervalued?

IRON scores higher with a 4.2/10 quality rating vs INSM's 4.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Insmed Incorporated (INSM) and Disc Medicine, Inc. (IRON) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

INSM currently trades at $106.91 with a QOC of 4.0/10, while IRON trades at $69.57 with a QOC of 4.2/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).