Disc Medicine (IRON) Operating Expenses (2020 - 2026)
Disc Medicine's Operating Expenses was $65.08 million in Q2 2026, up 6.0% from $61.41 million a year earlier but down 6.4% from the prior quarter.
Disc Medicine (IRON) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Disc Medicine's Operating Expenses was $269.27 million through Jun 30, 2026, up 59.6% year-over-year; for FY2025, it was $236.02 million, up 81.9% from FY2024.
- Operating Expenses has now increased for four consecutive years, with a five-year compound annual growth rate of 47.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $129.72 million in FY2024 (+42.4%), $91.13 million in FY2023 (+91.9%), $47.48 million in FY2022 (+53.5%) and $30.93 million in FY2021 (-9.1%).
- Quarterly Operating Expenses has moved between -$20.33 million (Q4 2021) and $69.52 million (Q1 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for 14 straight quarters, with growth averaging 61.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2023 (growth of 152.3%); the worst was Q3 2022 (a decline of 43.2%).
- Per Business Quant data, IRON's Operating Expenses in the three quarters before Q2 2026 was $69.52 million (Q1 2026), $66.97 million (Q4 2025) and $67.7 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 645.01 Bn | 563.54 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 465.23 Bn | 438.39 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 368.40 Bn | 322.83 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 278.02 Bn | 233.89 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 254.57 Bn | 228.13 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 229.02 Bn | 184.42 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 187.74 Bn | 161.85 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.45 Bn | 105.45 Bn | 2.84 Bn | 2.09 Bn |
| 10 | Disc Medicine | 2.53 Bn | 2.53 Bn | - | 65.08 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 65.08 Mn |
| Mar 31, 2026 | 69.52 Mn |
| Dec 31, 2025 | 66.97 Mn |
| Sep 30, 2025 | 67.70 Mn |
| Jun 30, 2025 | 61.41 Mn |
| Mar 31, 2025 | 39.95 Mn |
| Dec 31, 2024 | 34.55 Mn |
| Sep 30, 2024 | 32.86 Mn |
| Jun 30, 2024 | 30.85 Mn |
| Mar 31, 2024 | 31.46 Mn |
| Dec 31, 2023 | 29.71 Mn |
| Sep 30, 2023 | 18.96 Mn |
| Jun 30, 2023 | 17.33 Mn |
| Mar 31, 2023 | 25.13 Mn |
| Dec 31, 2022 | 15.02 Mn |
| Sep 30, 2022 | 10.48 Mn |
| Jun 30, 2022 | 12.02 Mn |
| Mar 31, 2022 | 9.96 Mn |
| Dec 31, 2021 | -20.33 Mn |
| Sep 30, 2021 | 18.45 Mn |
Disc Medicine Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=IRON&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IRON", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=IRON&period=max&api_key=YOUR_API_KEY");
const data = await res.json();