DBV Technologies (DBVT) Total Non-Current Liabilities (2015 - 2026)
DBV Technologies' Total Non-Current Liabilities was $8.5 million in Q2 2026, up 9.3% from $7.78 million a year earlier and up 26.9% from the prior quarter.
DBV Technologies (DBVT) Total Non-Current Liabilities (2015 - 2026) Analysis & Trends
At the end of FY2025, Total Non-Current Liabilities at DBV Technologies came in at $6.9 million, down 3.3% from FY2024.
- Total Non-Current Liabilities shows a five-year compound annual growth rate of -13.2% (FY2020 to FY2025).
- In earlier years, Total Non-Current Liabilities was $7.14 million in FY2024 (+30.7%), $5.46 million in FY2023 (-75.8%), $22.54 million in FY2022 (+40.4%) and $16.05 million in FY2021 (+14.3%).
- The Q2 2026 figure marks the highest quarterly Total Non-Current Liabilities since Q3 2023.
- Compared with a year earlier, Total Non-Current Liabilities was higher in four of the last eight quarters, with an average decline of 2.4%.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q1 2023 (growth of 121.9%); the worst was Q4 2023 (a decline of 75.8%).
- Per Business Quant data, DBVT's Total Non-Current Liabilities in the three quarters before Q2 2026 was $6.7 million (Q1 2026), $6.9 million (Q4 2025) and $8.16 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,138.83 Bn | 1,107.41 Bn | 19.71 Bn | 60.66 Bn |
| 2 | Johnson & Johnson | 618.88 Bn | 537.41 Bn | 17.26 Bn | 105.50 Bn |
| 3 | AbbVie | 502.93 Bn | 476.04 Bn | 12.70 Bn | 106.45 Bn |
| 4 | Merck | 369.61 Bn | 323.99 Bn | 12.21 Bn | 80.25 Bn |
| 5 | Novartis Ag | 298.70 Bn | 262.69 Bn | 11.24 Bn | 48.34 Bn |
| 6 | Astrazeneca | 261.35 Bn | 235.03 Bn | 12.86 Bn | 33.91 Bn |
| 7 | Amgen | 237.59 Bn | 192.99 Bn | 7.24 Bn | 78.66 Bn |
| 8 | Gilead Sciences | 191.60 Bn | 165.79 Bn | 6.22 Bn | 35.10 Bn |
| 9 | Pfizer | 170.23 Bn | 116.88 Bn | 10.94 Bn | 97.04 Bn |
| 10 | DBV Technologies | 835.42 Mn | 167.29 Mn | - | 8.50 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 8.50 Mn |
| Mar 31, 2026 | 6.70 Mn |
| Dec 31, 2025 | 6.90 Mn |
| Sep 30, 2025 | 8.16 Mn |
| Jun 30, 2025 | 7.78 Mn |
| Mar 31, 2025 | 7.31 Mn |
| Dec 31, 2024 | 7.14 Mn |
| Sep 30, 2024 | 8.11 Mn |
| Jun 30, 2024 | 7.71 Mn |
| Mar 31, 2024 | 7.76 Mn |
| Dec 31, 2023 | 5.46 Mn |
| Sep 30, 2023 | 14.35 Mn |
| Jun 30, 2023 | 19.91 Mn |
| Mar 31, 2023 | 21.06 Mn |
| Dec 31, 2022 | 22.54 Mn |
| Sep 30, 2022 | 7.67 Mn |
| Jun 30, 2022 | 10.13 Mn |
| Mar 31, 2022 | 9.49 Mn |
| Dec 31, 2021 | 16.05 Mn |
| Sep 30, 2021 | 20.22 Mn |
DBV Technologies Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=DBVT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "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=total-non-current-liabilities&ticker=DBVT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();