Editas Medicine (EDIT) Operating Expenses (2015 - 2025)
Editas Medicine (EDIT) recorded Operating Expenses of $32.09 million in Q3 2025, down 51.2% from $65.73 million a year earlier and down 41.8% from the prior quarter.
Editas Medicine (EDIT) Operating Expenses (2015 - 2025) Analysis & Trends
On a TTM basis, Editas Medicine's Operating Expenses came in at $245.23 million as of Sep 30, 2025, down 15.5% year-over-year; for FY2024, it came in at $283.47 million, up 14.6% from FY2023.
- Annual Operating Expenses has increased for three straight years, with a five-year compound annual growth rate of 11.9% (FY2019 to FY2024).
- Across earlier years, Operating Expenses came in at $247.3 million in FY2023 (+0.7%), $245.66 million in FY2022 (+12.3%), $218.69 million in FY2021 (-3.1%) and $225.57 million in FY2020 (+39.7%).
- The Q3 2025 figure is the lowest quarterly Operating Expenses since Q3 2018.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 5.0%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 54.1% in Q2 2024, against a decline of 51.2% in Q3 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $55.12 million (Q2 2025), $80.82 million (Q1 2025) and $77.2 million (Q4 2024).
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 | Editas Medicine | 234.09 Mn | -477.66 Mn | - | - |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2025 | 32.09 Mn |
| Jun 30, 2025 | 55.12 Mn |
| Mar 31, 2025 | 80.82 Mn |
| Dec 31, 2024 | 77.20 Mn |
| Sep 30, 2024 | 65.73 Mn |
| Jun 30, 2024 | 72.42 Mn |
| Mar 31, 2024 | 68.13 Mn |
| Dec 31, 2023 | 84.01 Mn |
| Sep 30, 2023 | 55.50 Mn |
| Jun 30, 2023 | 46.98 Mn |
| Mar 31, 2023 | 60.81 Mn |
| Dec 31, 2022 | 69.98 Mn |
| Sep 30, 2022 | 57.56 Mn |
| Jun 30, 2022 | 60.60 Mn |
| Mar 31, 2022 | 57.52 Mn |
| Dec 31, 2021 | 54.08 Mn |
| Sep 30, 2021 | 45.45 Mn |
| Jun 30, 2021 | 55.78 Mn |
| Mar 31, 2021 | 63.38 Mn |
| Dec 31, 2020 | 77.29 Mn |
Editas Medicine 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=EDIT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EDIT", "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=EDIT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();