Aligos Therapeutics (ALGS) Operating Expenses (2019 - 2026)
Aligos Therapeutics (ALGS) recorded Operating Expenses of $29.67 million in Q2 2026, up 51.9% from $19.53 million a year earlier but down 0.3% from the prior quarter.
Aligos Therapeutics (ALGS) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, Aligos Therapeutics' Operating Expenses came in at $110.51 million as of Jun 30, 2026, up 35.3% year-over-year; for FY2025, it came in at $90.17 million, down 3.1% from FY2024.
- Annual Operating Expenses has declined for four straight years, with a five-year compound annual growth rate of -1.6% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $93.1 million in FY2024 (-10.2%), $103.66 million in FY2023 (-7.0%), $111.49 million in FY2022 (-16.0%) and $132.68 million in FY2021 (+35.6%).
- Quarterly Operating Expenses has ranged from $19.53 million in Q2 2025 to $38.32 million in Q4 2021 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for four consecutive quarters, with growth averaging 8.7% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 60.5% in Q3 2021, against a decline of 33.4% in Q3 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $29.76 million (Q1 2026), $21.98 million (Q4 2025) and $29.1 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,132.46 Bn | 1,101.04 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 614.45 Bn | 532.98 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 503.76 Bn | 476.87 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 367.67 Bn | 322.05 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 298.09 Bn | 262.08 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.81 Bn | 235.50 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 236.49 Bn | 191.89 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 191.25 Bn | 165.45 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 170.18 Bn | 116.83 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Aligos Therapeutics | 54.60 Mn | -273.80 Mn | - | 29.67 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 29.67 Mn |
| Mar 31, 2026 | 29.76 Mn |
| Dec 31, 2025 | 21.98 Mn |
| Sep 30, 2025 | 29.10 Mn |
| Jun 30, 2025 | 19.53 Mn |
| Mar 31, 2025 | 19.55 Mn |
| Dec 31, 2024 | 21.19 Mn |
| Sep 30, 2024 | 21.40 Mn |
| Jun 30, 2024 | 27.48 Mn |
| Mar 31, 2024 | 23.03 Mn |
| Dec 31, 2023 | 28.68 Mn |
| Sep 30, 2023 | 22.31 Mn |
| Jun 30, 2023 | 26.03 Mn |
| Mar 31, 2023 | 26.64 Mn |
| Dec 31, 2022 | 26.22 Mn |
| Sep 30, 2022 | 23.05 Mn |
| Jun 30, 2022 | 24.09 Mn |
| Mar 31, 2022 | 38.13 Mn |
| Dec 31, 2021 | 38.32 Mn |
| Sep 30, 2021 | 34.61 Mn |
Aligos 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=ALGS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ALGS", "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=ALGS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();