DBV Technologies (DBVT) Research & Development (2020 - 2026)
DBV Technologies' Research & Development came in at $31.2 million for Q2 2026, down 7.4% from $33.7 million a year earlier and down 6.6% from the prior quarter.
DBV Technologies (DBVT) Research & Development (2020 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, DBV Technologies reported Research & Development of $126.11 million, up 29.0% year-over-year; for FY2025, it came in at $116.68 million, up 30.6% from FY2024.
- Research & Development carries a five-year compound annual growth rate of 2.8% (FY2020 to FY2025).
- Going back by year, Research & Development was $89.34 million in FY2024 (+48.4%), $60.22 million in FY2023 (-20.3%), $75.54 million in FY2022 (+7.4%) and $70.34 million in FY2021 (-30.8%).
- The five-year range for quarterly Research & Development is $11.67 million (Q4 2021) to $33.7 million (Q2 2025).
- Year-over-year, Research & Development increased in seven of the last eight quarters, with growth averaging 37.0%.
- The fastest year-over-year change in Research & Development over five years came in Q4 2022 (growth of 153.7%), and the weakest in Q4 2023 (a decline of 56.9%).
- Business Quant data shows DBVT's Research & Development at $33.4 million (Q1 2026), $32.89 million (Q4 2025) and $28.62 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,136.97 Bn | 1,105.55 Bn | 19.71 Bn | 3.82 Bn |
| 2 | Johnson & Johnson | 619.72 Bn | 538.25 Bn | 17.26 Bn | 3.65 Bn |
| 3 | AbbVie | 503.40 Bn | 476.52 Bn | 12.70 Bn | 2.34 Bn |
| 4 | Merck | 370.15 Bn | 324.53 Bn | 12.21 Bn | 9.74 Bn |
| 5 | Novartis Ag | 298.64 Bn | 262.63 Bn | 11.24 Bn | 2.85 Bn |
| 6 | Astrazeneca | 261.07 Bn | 234.76 Bn | 12.86 Bn | 4.05 Bn |
| 7 | Amgen | 237.00 Bn | 192.40 Bn | 7.24 Bn | 1.87 Bn |
| 8 | Gilead Sciences | 191.24 Bn | 165.43 Bn | 6.22 Bn | 1.76 Bn |
| 9 | Pfizer | 170.31 Bn | 116.96 Bn | 10.94 Bn | 2.81 Bn |
| 10 | DBV Technologies | 836.72 Mn | 168.59 Mn | - | 31.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 31.20 Mn |
| Mar 31, 2026 | 33.40 Mn |
| Dec 31, 2025 | 32.89 Mn |
| Sep 30, 2025 | 28.62 Mn |
| Jun 30, 2025 | 33.70 Mn |
| Mar 31, 2025 | 21.50 Mn |
| Dec 31, 2024 | 18.90 Mn |
| Sep 30, 2024 | 23.66 Mn |
| Jun 30, 2024 | 25.37 Mn |
| Mar 31, 2024 | 21.40 Mn |
| Dec 31, 2023 | 12.78 Mn |
| Sep 30, 2023 | 13.80 Mn |
| Jun 30, 2023 | 17.62 Mn |
| Mar 31, 2023 | 16.04 Mn |
| Dec 31, 2022 | 29.61 Mn |
| Sep 30, 2022 | 15.10 Mn |
| Jun 30, 2022 | 18.61 Mn |
| Mar 31, 2022 | 12.22 Mn |
| Dec 31, 2021 | 11.67 Mn |
| Sep 30, 2021 | 16.32 Mn |
DBV Technologies Research & Development 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=research-and-development&ticker=DBVT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "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=research-and-development&ticker=DBVT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();