Relay Therapeutics (RLAY) Operating Expenses (2019 - 2026)
Relay Therapeutics (RLAY) reported Operating Expenses of $91.17 million for Q2 2026, up 17.6% from $77.52 million a year earlier and up 11.7% from the prior quarter.
Relay Therapeutics (RLAY) Operating Expenses (2019 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Relay Therapeutics' Operating Expenses came in at $320.79 million, down 8.7% year-over-year; for FY2025, it came in at $318.09 million, down 16.8% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 18.1% (FY2020 to FY2025).
- By year, Operating Expenses came in at $382.48 million in FY2024 (-4.0%), $398.55 million in FY2023 (+32.6%), $300.66 million in FY2022 (-18.2%) and $367.73 million in FY2021 (+165.6%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q1 2025.
- Year over year, Operating Expenses gained in 1 of the last eight quarters, with an average decline of 9.0%.
- The high point for year-over-year Operating Expenses in five years was Q3 2021 (growth of 68.4%); the low point was Q2 2022 (a decline of 59.8%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $81.59 million (Q1 2026), $67.63 million (Q4 2025) and $80.39 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 | Relay Therapeutics | 3.87 Bn | 3.87 Bn | - | 91.17 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 91.17 Mn |
| Mar 31, 2026 | 81.59 Mn |
| Dec 31, 2025 | 67.63 Mn |
| Sep 30, 2025 | 80.39 Mn |
| Jun 30, 2025 | 77.52 Mn |
| Mar 31, 2025 | 92.55 Mn |
| Dec 31, 2024 | 84.98 Mn |
| Sep 30, 2024 | 96.37 Mn |
| Jun 30, 2024 | 100.76 Mn |
| Mar 31, 2024 | 100.37 Mn |
| Dec 31, 2023 | 92.20 Mn |
| Sep 30, 2023 | 98.78 Mn |
| Jun 30, 2023 | 106.17 Mn |
| Mar 31, 2023 | 101.40 Mn |
| Dec 31, 2022 | 73.10 Mn |
| Sep 30, 2022 | 86.24 Mn |
| Jun 30, 2022 | 78.18 Mn |
| Mar 31, 2022 | 63.14 Mn |
| Dec 31, 2021 | 68.29 Mn |
| Sep 30, 2021 | 61.66 Mn |
Relay Therapeutics 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=RLAY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "RLAY", "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=RLAY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();