Allogene Therapeutics (ALLO) Operating Expenses (2018 - 2026)
Allogene Therapeutics (ALLO) recorded Operating Expenses of $51.56 million in Q2 2026, down 9.3% from $56.82 million a year earlier but up 11.9% from the prior quarter.
Allogene Therapeutics (ALLO) Operating Expenses (2018 - 2026) Analysis & Trends
On a TTM basis, Allogene Therapeutics' Operating Expenses came in at $184.96 million as of Jun 30, 2026, down 27.3% year-over-year; for FY2025, it came in at $209.32 million, down 23.4% from FY2024.
- Annual Operating Expenses has declined for three straight years, with a five-year compound annual growth rate of -4.1% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $273.22 million in FY2024 (-16.7%), $327.83 million in FY2023 (-2.3%), $335.69 million in FY2022 (+14.1%) and $294.28 million in FY2021 (+14.0%).
- Quarterly Operating Expenses has ranged from $42.4 million in Q4 2025 to $99.12 million in Q1 2023 over the past five years.
- On a year-over-year basis, Operating Expenses has declined for seven consecutive quarters, with an average decline of 18.5% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 30.4% in Q4 2022, against a decline of 37.4% in Q3 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $46.09 million (Q1 2026), $42.4 million (Q4 2025) and $44.9 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 | Allogene Therapeutics | 562.91 Mn | 562.91 Mn | - | 51.56 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 51.56 Mn |
| Mar 31, 2026 | 46.09 Mn |
| Dec 31, 2025 | 42.40 Mn |
| Sep 30, 2025 | 44.90 Mn |
| Jun 30, 2025 | 56.82 Mn |
| Mar 31, 2025 | 65.19 Mn |
| Dec 31, 2024 | 60.49 Mn |
| Sep 30, 2024 | 71.77 Mn |
| Jun 30, 2024 | 71.43 Mn |
| Mar 31, 2024 | 69.53 Mn |
| Dec 31, 2023 | 85.13 Mn |
| Sep 30, 2023 | 63.02 Mn |
| Jun 30, 2023 | 80.56 Mn |
| Mar 31, 2023 | 99.12 Mn |
| Dec 31, 2022 | 96.42 Mn |
| Sep 30, 2022 | 82.54 Mn |
| Jun 30, 2022 | 76.68 Mn |
| Mar 31, 2022 | 80.05 Mn |
| Dec 31, 2021 | 73.94 Mn |
| Sep 30, 2021 | 77.72 Mn |
Allogene 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=ALLO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ALLO", "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=ALLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();