Alkermes (ALKS) Operating Expenses (2010 - 2026)
Alkermes' Operating Expenses came in at $477.66 million for Q2 2026, up 60.5% from $297.68 million a year earlier and up 8.3% from the prior quarter.
Alkermes (ALKS) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Alkermes reported Operating Expenses of $1.55 billion, up 37.1% year-over-year; for FY2025, it came in at $1.22 billion, up 7.5% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 1.2% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $1.14 billion in FY2024 (-9.0%), $1.25 billion in FY2023 (+11.8%), $1.12 billion in FY2022 (+3.9%) and $1.08 billion in FY2021 (-6.5%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q1 2013.
- Year-over-year, Operating Expenses has increased for five consecutive quarters, with growth averaging 15.0% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2023 (growth of 70.7%), and the weakest in Q4 2021 (a decline of 37.2%).
- Business Quant data shows ALKS's Operating Expenses at $441.19 million (Q1 2026), $326.44 million (Q4 2025) and $305.1 million (Q3 2025) in the three quarters before Q2 2026.
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 | Alkermes | 6.73 Bn | 3.86 Bn | 397.90 Mn | 477.66 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 477.66 Mn |
| Mar 31, 2026 | 441.19 Mn |
| Dec 31, 2025 | 326.44 Mn |
| Sep 30, 2025 | 305.10 Mn |
| Jun 30, 2025 | 297.68 Mn |
| Mar 31, 2025 | 292.72 Mn |
| Dec 31, 2024 | 267.30 Mn |
| Sep 30, 2024 | 273.39 Mn |
| Jun 30, 2024 | 289.25 Mn |
| Mar 31, 2024 | 307.06 Mn |
| Dec 31, 2023 | 322.84 Mn |
| Sep 30, 2023 | 291.74 Mn |
| Jun 30, 2023 | 336.13 Mn |
| Mar 31, 2023 | 298.57 Mn |
| Dec 31, 2022 | 189.08 Mn |
| Sep 30, 2022 | 313.00 Mn |
| Jun 30, 2022 | 310.68 Mn |
| Mar 31, 2022 | 305.13 Mn |
| Dec 31, 2021 | 195.05 Mn |
| Sep 30, 2021 | 313.80 Mn |
Alkermes 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=ALKS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ALKS", "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=ALKS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();