Coherus Oncology (CHRS) Operating Expenses (2013 - 2026)
Coherus Oncology (CHRS) recorded Operating Expenses of $46.64 million in Q2 2026, down 16.3% from $55.74 million a year earlier and down 3.8% from the prior quarter.
Coherus Oncology (CHRS) Operating Expenses (2013 - 2026) Analysis & Trends
On a TTM basis, Coherus Oncology's Operating Expenses came in at $209.63 million as of Jun 30, 2026, down 2.4% year-over-year; for FY2025, it was $223.31 million, down 1.2% from FY2024.
- Annual Operating Expenses has declined for four straight years, with a five-year compound annual growth rate of -6.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $226.04 million in FY2024 (-50.9%), $460.44 million in FY2023 (-1.6%), $467.92 million in FY2022 (-20.7%) and $590.41 million in FY2021 (+84.8%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q2 2018.
- On a year-over-year basis, Operating Expenses rose in three of the last eight quarters, with an average decline of 17.4%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 65.7% in Q4 2023, against a decline of 66.9% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $48.46 million (Q1 2026), $58.63 million (Q4 2025) and $55.9 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,221.54 Bn | 1,195.15 Bn | 20.46 Bn | 7.68 Bn |
| 2 | Johnson & Johnson | 650.21 Bn | 570.07 Bn | 17.30 Bn | 11.12 Bn |
| 3 | AbbVie | 508.24 Bn | 476.24 Bn | 13.12 Bn | 11.14 Bn |
| 4 | Merck | 360.07 Bn | 323.01 Bn | 13.19 Bn | 7.61 Bn |
| 5 | Novartis Ag | 312.26 Bn | 285.49 Bn | - | - |
| 6 | Astrazeneca | 285.31 Bn | 259.20 Bn | 13.26 Bn | 9.00 Bn |
| 7 | Amgen | 247.74 Bn | 199.39 Bn | 7.58 Bn | 6.66 Bn |
| 8 | Gilead Sciences | 207.12 Bn | 182.22 Bn | 6.73 Bn | 4.84 Bn |
| 9 | Pfizer | 166.13 Bn | 113.48 Bn | 12.56 Bn | 7.09 Bn |
| 10 | Coherus Oncology | 116.17 Mn | -519.97 Mn | 10.07 Mn | 46.64 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.64 Mn |
| Mar 31, 2026 | 48.46 Mn |
| Dec 31, 2025 | 58.63 Mn |
| Sep 30, 2025 | 55.90 Mn |
| Jun 30, 2025 | 55.74 Mn |
| Mar 31, 2025 | 53.03 Mn |
| Dec 31, 2024 | 53.12 Mn |
| Sep 30, 2024 | 52.91 Mn |
| Jun 30, 2024 | 49.92 Mn |
| Mar 31, 2024 | 70.10 Mn |
| Dec 31, 2023 | 160.43 Mn |
| Sep 30, 2023 | 106.57 Mn |
| Jun 30, 2023 | 93.26 Mn |
| Mar 31, 2023 | 100.18 Mn |
| Dec 31, 2022 | 96.85 Mn |
| Sep 30, 2022 | 125.87 Mn |
| Jun 30, 2022 | 104.16 Mn |
| Mar 31, 2022 | 141.04 Mn |
| Dec 31, 2021 | 112.92 Mn |
| Sep 30, 2021 | 115.29 Mn |
Coherus Oncology 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=CHRS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CHRS", "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=CHRS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();