Exicure (XCUR) Operating Expenses (2016 - 2026)
Exicure (XCUR) recorded Operating Expenses of $1.05 million in Q2 2026, down 58.0% from $2.51 million a year earlier and down 35.7% from the prior quarter.
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Analysis
Exicure (XCUR) Operating Expenses (2016 - 2026) Analysis & Trends
On a TTM basis, Exicure's Operating Expenses came in at $7.34 million as of Jun 30, 2026, down 24.7% year-over-year; for FY2025, it came in at $4.23 million, down 66.8% from FY2024.
- Annual Operating Expenses has declined for four straight years, with a five-year compound annual growth rate of -36.8% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $12.73 million in FY2024 (-15.1%), $15 million in FY2023 (-51.1%), $30.66 million in FY2022 (-50.6%) and $62.07 million in FY2021 (+47.6%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q1 2025.
- On a year-over-year basis, Operating Expenses rose in two of the last six quarters, with growth averaging 58.7%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 406.6% in Q4 2024, against a decline of 79.6% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $1.64 million (Q1 2026), $2.26 million (Q4 2025) and $2.39 million (Q3 2025).
Peer Set
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 | Exicure | 7.27 Mn | 7.27 Mn | - | 1.05 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.05 Mn |
| Mar 31, 2026 | 1.64 Mn |
| Dec 31, 2025 | 2.26 Mn |
| Sep 30, 2025 | 2.39 Mn |
| Jun 30, 2025 | 2.51 Mn |
| Mar 31, 2025 | -2.92 Mn |
| Dec 31, 2024 | 7.59 Mn |
| Sep 30, 2024 | 2.57 Mn |
| Jun 30, 2024 | 1.24 Mn |
| Mar 31, 2024 | 1.34 Mn |
| Dec 31, 2023 | 1.50 Mn |
| Sep 30, 2023 | 3.32 Mn |
| Jun 30, 2023 | 5.64 Mn |
| Mar 31, 2023 | 4.54 Mn |
| Dec 31, 2022 | 3.18 Mn |
| Sep 30, 2022 | 7.22 Mn |
| Jun 30, 2022 | 9.95 Mn |
| Mar 31, 2022 | 10.30 Mn |
| Dec 31, 2021 | 15.57 Mn |
| Sep 30, 2021 | 19.40 Mn |
API Access
Exicure 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=XCUR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "XCUR", "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=XCUR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();