Alx Oncology Holdings (ALXO) Operating Expenses (2019 - 2026)
Alx Oncology Holdings (ALXO) posted Operating Expenses of $18.03 million for Q2 2026, down 32.3% from $26.65 million a year earlier and down 4.9% from the prior quarter.
Alx Oncology Holdings (ALXO) Operating Expenses (2019 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Alx Oncology Holdings was $82.55 million, down 32.1% year-over-year; for FY2025, it was $104.02 million, down 27.0% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 18.3% (FY2020 to FY2025).
- In prior years, Alx Oncology Holdings' Operating Expenses was $142.47 million in FY2024 (-16.3%), $170.28 million in FY2023 (+33.6%), $127.44 million in FY2022 (+52.5%) and $83.56 million in FY2021 (+86.3%).
- The Q2 2026 figure stands as the lowest quarterly Operating Expenses since Q2 2021.
- On a year-over-year basis, Operating Expenses has declined in each of the last eight quarters, with an average decline of 31.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 150.5%; the weakest was Q1 2026, with a decline of 40.4%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $18.97 million (Q1 2026), $23.02 million (Q4 2025) and $22.53 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,165.22 Bn | 1,133.81 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 646.28 Bn | 566.14 Bn | 17.30 Bn | 11.12 Bn |
| 3 | AbbVie | 503.17 Bn | 476.28 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 365.23 Bn | 319.60 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 302.66 Bn | 266.65 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 267.39 Bn | 241.08 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 241.61 Bn | 197.01 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 194.67 Bn | 168.86 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 172.91 Bn | 119.55 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Alx Oncology Holdings | 162.77 Mn | -221.20 Mn | - | 18.03 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 18.03 Mn |
| Mar 31, 2026 | 18.97 Mn |
| Dec 31, 2025 | 23.02 Mn |
| Sep 30, 2025 | 22.53 Mn |
| Jun 30, 2025 | 26.65 Mn |
| Mar 31, 2025 | 31.82 Mn |
| Dec 31, 2024 | 30.61 Mn |
| Sep 30, 2024 | 32.57 Mn |
| Jun 30, 2024 | 41.53 Mn |
| Mar 31, 2024 | 37.76 Mn |
| Dec 31, 2023 | 48.02 Mn |
| Sep 30, 2023 | 53.28 Mn |
| Jun 30, 2023 | 36.78 Mn |
| Mar 31, 2023 | 32.20 Mn |
| Dec 31, 2022 | 32.22 Mn |
| Sep 30, 2022 | 36.68 Mn |
| Jun 30, 2022 | 33.79 Mn |
| Mar 31, 2022 | 24.75 Mn |
| Dec 31, 2021 | 28.47 Mn |
| Sep 30, 2021 | 24.58 Mn |
Alx Oncology Holdings 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=ALXO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ALXO", "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=ALXO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();