BioCardia (BCDA) Operating Expenses (2010 - 2026)
BioCardia's Operating Expenses was $1.62 million in Q2 2026, down 20.9% from $2.05 million a year earlier and down 28.4% from the prior quarter.
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Analysis
BioCardia (BCDA) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, BioCardia's Operating Expenses was $7.39 million through Jun 30, 2026, down 16.5% year-over-year; for FY2025, it came in at $8.28 million, up 2.7% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of -12.0% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $8.06 million in FY2024 (-33.5%), $12.12 million in FY2023 (-8.5%), $13.25 million in FY2022 (-2.9%) and $13.65 million in FY2021 (-12.9%).
- Quarterly Operating Expenses has moved between $1.49 million (Q3 2025) and $3.57 million (Q1 2023) over five years.
- Compared with a year earlier, Operating Expenses has declined for four straight quarters, with an average decline of 6.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2025 (growth of 24.2%); the worst was Q2 2024 (a decline of 52.7%).
- Per Business Quant data, BCDA's Operating Expenses in the three quarters before Q2 2026 was $2.27 million (Q1 2026), $2.01 million (Q4 2025) and $1.49 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 | BioCardia | 12.46 Mn | -407,934.31 | - | 1.62 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.62 Mn |
| Mar 31, 2026 | 2.27 Mn |
| Dec 31, 2025 | 2.01 Mn |
| Sep 30, 2025 | 1.49 Mn |
| Jun 30, 2025 | 2.05 Mn |
| Mar 31, 2025 | 2.73 Mn |
| Dec 31, 2024 | 2.32 Mn |
| Sep 30, 2024 | 1.76 Mn |
| Jun 30, 2024 | 1.65 Mn |
| Mar 31, 2024 | 2.33 Mn |
| Dec 31, 2023 | 2.10 Mn |
| Sep 30, 2023 | 2.96 Mn |
| Jun 30, 2023 | 3.50 Mn |
| Mar 31, 2023 | 3.57 Mn |
| Dec 31, 2022 | 3.12 Mn |
| Sep 30, 2022 | 3.27 Mn |
| Jun 30, 2022 | 3.47 Mn |
| Mar 31, 2022 | 3.39 Mn |
| Dec 31, 2021 | 3.54 Mn |
| Sep 30, 2021 | 3.53 Mn |
API Access
BioCardia 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=BCDA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BCDA", "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=BCDA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();