Immunome (IMNM) Operating Expenses (2019 - 2026)
Immunome (IMNM) recorded Operating Expenses of $78.14 million in Q2 2026, up 54.7% from $50.49 million a year earlier and up 31.7% from the prior quarter.
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Analysis
Immunome (IMNM) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, Immunome's Operating Expenses came in at $270.47 million as of Jun 30, 2026, up 14.0% year-over-year; for FY2025, it came in at $231.05 million, down 26.6% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 79.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $314.84 million in FY2024 (+154.8%), $123.55 million in FY2023 (+234.8%), $36.9 million in FY2022 (+46.4%) and $25.2 million in FY2021 (+105.6%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q4 2024.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 71.3%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 551.8% in Q3 2024, against a decline of 64.3% in Q1 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $59.33 million (Q1 2026), $72.86 million (Q4 2025) and $60.14 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 2.09 Bn |
| 10 | Immunome | 2.46 Bn | 429.67 Mn | - | 78.14 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 78.14 Mn |
| Mar 31, 2026 | 59.33 Mn |
| Dec 31, 2025 | 72.86 Mn |
| Sep 30, 2025 | 60.14 Mn |
| Jun 30, 2025 | 50.49 Mn |
| Mar 31, 2025 | 47.56 Mn |
| Dec 31, 2024 | 85.71 Mn |
| Sep 30, 2024 | 53.43 Mn |
| Jun 30, 2024 | 42.37 Mn |
| Mar 31, 2024 | 133.33 Mn |
| Dec 31, 2023 | 98.48 Mn |
| Sep 30, 2023 | 8.20 Mn |
| Jun 30, 2023 | 10.04 Mn |
| Mar 31, 2023 | 6.84 Mn |
| Dec 31, 2022 | 7.79 Mn |
| Sep 30, 2022 | 8.53 Mn |
| Jun 30, 2022 | 8.93 Mn |
| Mar 31, 2022 | 11.65 Mn |
| Dec 31, 2021 | 7.84 Mn |
| Sep 30, 2021 | 7.72 Mn |
API Access
Immunome 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=IMNM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IMNM", "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=IMNM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();