Alnylam Pharmaceuticals (ALNY) Change in Accured Expenses (2009 - 2026)
Alnylam Pharmaceuticals (ALNY) reported Change in Accured Expenses of $61.62 million for Q2 2026, down 61.1% from $158.23 million a year earlier.
Alnylam Pharmaceuticals (ALNY) Change in Accured Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Alnylam Pharmaceuticals' Change in Accured Expenses came in at -$39.84 million; for FY2025, it came in at $75.07 million, down 17.6% from FY2024.
- Change in Accured Expenses has a five-year compound annual growth rate of -12.2% (FY2020 to FY2025).
- By year, Change in Accured Expenses came in at $91.09 million in FY2024 (+12.7%), $80.84 million in FY2023 (-57.8%), $191.77 million in FY2022 (+117.3%) and $88.24 million in FY2021 (-38.6%).
- Five-year quarterly Change in Accured Expenses spans a low of -$176.03 million in Q1 2026 and a high of $249.43 million in Q3 2025.
- Year over year, Change in Accured Expenses gained in two of the last four quarters, with growth averaging 55.0%.
- The high point for year-over-year Change in Accured Expenses in five years was Q3 2025 (growth of 198.4%); the low point was Q2 2026 (a decline of 61.1%).
- Per Business Quant data, the three quarters before Q2 2026 came in at -$176.03 million (Q1 2026), -$174.85 million (Q4 2025) and $249.43 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 653.54 Bn | 572.07 Bn | 17.26 Bn | 2.96 Bn |
| 2 | AbbVie | 467.01 Bn | 440.17 Bn | 12.70 Bn | 1.20 Bn |
| 3 | Merck | 367.16 Bn | 321.59 Bn | 12.21 Bn | - |
| 4 | Novartis Ag | 277.56 Bn | 233.43 Bn | 11.24 Bn | -251.00 Mn |
| 5 | Astrazeneca | 258.23 Bn | 231.79 Bn | 12.86 Bn | - |
| 6 | Amgen | 224.14 Bn | 179.54 Bn | 7.24 Bn | 901.00 Mn |
| 7 | Gilead Sciences | 187.30 Bn | 161.42 Bn | 6.22 Bn | 338.00 Mn |
| 8 | Pfizer | 163.47 Bn | 110.41 Bn | 10.94 Bn | - |
| 9 | Vertex Pharmaceuticals | 133.31 Bn | 105.31 Bn | 2.84 Bn | 222.50 Mn |
| 10 | Alnylam Pharmaceuticals | 34.23 Bn | 22.28 Bn | 992.69 Mn | 61.62 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 61.62 Mn |
| Mar 31, 2026 | -176.03 Mn |
| Dec 31, 2025 | -174.85 Mn |
| Sep 30, 2025 | 249.43 Mn |
| Jun 30, 2025 | 158.23 Mn |
| Mar 31, 2025 | -157.74 Mn |
| Dec 31, 2024 | -62.11 Mn |
| Sep 30, 2024 | 83.60 Mn |
| Jun 30, 2024 | 74.47 Mn |
| Mar 31, 2024 | -4.87 Mn |
| Dec 31, 2023 | -38.67 Mn |
| Sep 30, 2023 | 118.74 Mn |
| Jun 30, 2023 | 82.74 Mn |
| Mar 31, 2023 | -81.98 Mn |
| Dec 31, 2022 | 102.62 Mn |
| Sep 30, 2022 | 69.75 Mn |
| Jun 30, 2022 | 68.14 Mn |
| Mar 31, 2022 | -48.74 Mn |
| Dec 31, 2021 | 39.50 Mn |
| Sep 30, 2021 | 46.36 Mn |
Alnylam Pharmaceuticals Change in Accured 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=change-in-accured-expenses&ticker=ALNY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "ALNY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=ALNY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();