Arvinas (ARVN) Research & Development (2017 - 2026)
Arvinas' Research & Development was $52.6 million in Q2 2026, down 23.3% from $68.6 million a year earlier and down 12.8% from the prior quarter.
Arvinas (ARVN) Research & Development (2017 - 2026) Analysis & Trends
On a trailing twelve-month basis, Arvinas' Research & Development was $238.7 million through Jun 30, 2026, down 27.6% year-over-year; for FY2025, it was $285.2 million, down 18.1% from FY2024.
- Research & Development shows a five-year compound annual growth rate of 21.3% (FY2020 to FY2025).
- In earlier years, Research & Development was $348.2 million in FY2024 (-8.3%), $379.7 million in FY2023 (+20.5%), $315 million in FY2022 (+74.6%) and $180.4 million in FY2021 (+66.4%).
- The Q2 2026 figure marks the lowest quarterly Research & Development since Q3 2021.
- Compared with a year earlier, Research & Development has declined for five straight quarters, with an average decline of 17.4% over the last eight quarters.
- The best year-over-year quarter for Research & Development over five years was Q3 2022 (growth of 90.9%); the worst was Q1 2026 (a decline of 33.6%).
- Per Business Quant data, ARVN's Research & Development in the three quarters before Q2 2026 was $60.3 million (Q1 2026), $61.1 million (Q4 2025) and $64.7 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 3.65 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 2.34 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 9.74 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -2.85 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -4.05 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 1.87 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 1.76 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 2.81 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 993.80 Mn |
| 10 | Arvinas | 490.40 Mn | -2.17 Bn | - | 52.60 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 52.60 Mn |
| Mar 31, 2026 | 60.30 Mn |
| Dec 31, 2025 | 61.10 Mn |
| Sep 30, 2025 | 64.70 Mn |
| Jun 30, 2025 | 68.60 Mn |
| Mar 31, 2025 | 90.80 Mn |
| Dec 31, 2024 | 83.30 Mn |
| Sep 30, 2024 | 86.90 Mn |
| Jun 30, 2024 | 93.70 Mn |
| Mar 31, 2024 | 84.30 Mn |
| Dec 31, 2023 | 95.20 Mn |
| Sep 30, 2023 | 85.90 Mn |
| Jun 30, 2023 | 103.40 Mn |
| Mar 31, 2023 | 95.30 Mn |
| Dec 31, 2022 | 98.30 Mn |
| Sep 30, 2022 | 77.50 Mn |
| Jun 30, 2022 | 75.30 Mn |
| Mar 31, 2022 | 64.00 Mn |
| Dec 31, 2021 | 61.90 Mn |
| Sep 30, 2021 | 40.60 Mn |
Arvinas 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=ARVN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "ticker": "ARVN", "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=ARVN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();