DBV Technologies (DBVT) Operating Expenses (2020 - 2026)
DBV Technologies (DBVT) recorded Operating Expenses of $51.3 million in Q2 2026, up 20.4% from $42.6 million a year earlier and up 5.1% from the prior quarter.
DBV Technologies (DBVT) Operating Expenses (2020 - 2026) Analysis & Trends
On a TTM basis, DBV Technologies' Operating Expenses came in at $182.85 million as of Jun 30, 2026, up 45.4% year-over-year; for FY2025, it was $152.69 million, up 26.5% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -2.1% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $120.74 million in FY2024 (+31.0%), $92.16 million in FY2023 (-9.2%), $101.48 million in FY2022 (-2.7%) and $104.32 million in FY2021 (-38.7%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q2 2020.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 35.8% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 123.7% in Q4 2022, against a decline of 57.9% in Q4 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $48.8 million (Q1 2026), $45.7 million (Q4 2025) and $37.05 million (Q3 2025).
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 | DBV Technologies | 5.05 Bn | 4.38 Bn | - | 51.30 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 51.30 Mn |
| Mar 31, 2026 | 48.80 Mn |
| Dec 31, 2025 | 45.70 Mn |
| Sep 30, 2025 | 37.05 Mn |
| Jun 30, 2025 | 42.60 Mn |
| Mar 31, 2025 | 27.40 Mn |
| Dec 31, 2024 | 24.37 Mn |
| Sep 30, 2024 | 31.40 Mn |
| Jun 30, 2024 | 35.00 Mn |
| Mar 31, 2024 | 29.96 Mn |
| Dec 31, 2023 | 20.80 Mn |
| Sep 30, 2023 | 20.64 Mn |
| Jun 30, 2023 | 27.36 Mn |
| Mar 31, 2023 | 23.36 Mn |
| Dec 31, 2022 | 36.71 Mn |
| Sep 30, 2022 | 20.09 Mn |
| Jun 30, 2022 | 25.35 Mn |
| Mar 31, 2022 | 19.32 Mn |
| Dec 31, 2021 | 16.41 Mn |
| Sep 30, 2021 | 25.69 Mn |
DBV Technologies 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=DBVT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DBVT", "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=DBVT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();