Onconetix (ONCO) Operating Expenses (2021 - 2026)
Onconetix (ONCO) reported Operating Expenses of $2.74 million for Q2 2026, up 36.4% from $2.01 million a year earlier but down 73.2% from the prior quarter.
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Analysis
Onconetix (ONCO) Operating Expenses (2021 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Onconetix's Operating Expenses came in at $16.83 million, down 64.3% year-over-year; for FY2025, it came in at $18.49 million, down 67.9% from FY2024.
- Operating Expenses has a four-year compound annual growth rate of 52.5% (FY2021 to FY2025).
- By year, Operating Expenses came in at $57.54 million in FY2024 (+64.8%), $34.91 million in FY2023 (+158.9%), $13.48 million in FY2022 (+294.5%) and $3.42 million in FY2021.
- Five-year quarterly Operating Expenses spans a low of $1.1 million in Q3 2021 and a high of $29.81 million in Q4 2024.
- Year over year, Operating Expenses gained in three of the last eight quarters, with an average decline of 20.3%.
- The high point for year-over-year Operating Expenses in five years was Q4 2023 (growth of 544.5%); the low point was Q4 2025 (a decline of 94.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $10.22 million (Q1 2026), $1.53 million (Q4 2025) and $2.34 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Onconetix | 1.75 Mn | -13.97 Mn | 4,303.00 | 2.74 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.74 Mn |
| Mar 31, 2026 | 10.22 Mn |
| Dec 31, 2025 | 1.53 Mn |
| Sep 30, 2025 | 2.34 Mn |
| Jun 30, 2025 | 2.01 Mn |
| Mar 31, 2025 | 12.62 Mn |
| Dec 31, 2024 | 29.81 Mn |
| Sep 30, 2024 | 2.75 Mn |
| Jun 30, 2024 | 13.72 Mn |
| Mar 31, 2024 | 11.27 Mn |
| Dec 31, 2023 | 20.92 Mn |
| Sep 30, 2023 | 4.49 Mn |
| Jun 30, 2023 | 6.65 Mn |
| Mar 31, 2023 | 2.85 Mn |
| Dec 31, 2022 | 3.25 Mn |
| Sep 30, 2022 | 3.87 Mn |
| Jun 30, 2022 | 4.29 Mn |
| Mar 31, 2022 | 2.07 Mn |
| Dec 31, 2021 | 1.20 Mn |
| Sep 30, 2021 | 1.10 Mn |
API Access
Onconetix 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=ONCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ONCO", "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=ONCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();