Assembly Biosciences (ASMB) Change in Accured Expenses (2010 - 2026)
Assembly Biosciences' Change in Accured Expenses came in at $678,000 for Q2 2026, down 38.6% from $1.11 million a year earlier.
Assembly Biosciences (ASMB) Change in Accured Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Assembly Biosciences reported Change in Accured Expenses of -$65,000; for FY2025, it came in at $887,000, down 20.7% from FY2024.
- Change in Accured Expenses carries a five-year compound annual growth rate of -25.4% (FY2020 to FY2025).
- Going back by year, Change in Accured Expenses was $1.12 million in FY2024, -$1.57 million in FY2023, $458,000 in FY2022 and -$5.07 million in FY2021.
- The five-year range for quarterly Change in Accured Expenses is -$5.09 million (Q1 2026) to $2.32 million (Q3 2025).
- Year-over-year, Change in Accured Expenses increased in two of the last five quarters, with growth averaging 7.9%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q2 2022 (growth of 236.8%), and the weakest in Q4 2021 (a decline of 69.8%).
- Business Quant data shows ASMB's Change in Accured Expenses at -$5.09 million (Q1 2026), $2.02 million (Q4 2025) and $2.32 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,076.25 Bn | 1,044.84 Bn | 19.71 Bn | - |
| 2 | Johnson & Johnson | 617.18 Bn | 535.70 Bn | 17.26 Bn | 2.96 Bn |
| 3 | AbbVie | 464.58 Bn | 437.73 Bn | 12.70 Bn | 1.20 Bn |
| 4 | Merck | 356.04 Bn | 310.47 Bn | 12.21 Bn | - |
| 5 | Novartis Ag | 269.07 Bn | 224.94 Bn | 11.24 Bn | -251.00 Mn |
| 6 | Astrazeneca | 243.21 Bn | 216.77 Bn | 12.86 Bn | - |
| 7 | Amgen | 217.88 Bn | 173.28 Bn | 7.24 Bn | 901.00 Mn |
| 8 | Gilead Sciences | 179.62 Bn | 153.74 Bn | 6.22 Bn | 338.00 Mn |
| 9 | Pfizer | 158.45 Bn | 105.40 Bn | 10.94 Bn | - |
| 10 | Assembly Biosciences | 447.43 Mn | -580.20 Mn | - | 678,000.00 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 678,000.00 |
| Mar 31, 2026 | -5.09 Mn |
| Dec 31, 2025 | 2.02 Mn |
| Sep 30, 2025 | 2.32 Mn |
| Jun 30, 2025 | 1.11 Mn |
| Mar 31, 2025 | -4.56 Mn |
| Dec 31, 2024 | 2.10 Mn |
| Sep 30, 2024 | 1.18 Mn |
| Jun 30, 2024 | 1.54 Mn |
| Mar 31, 2024 | -3.69 Mn |
| Dec 31, 2023 | 1.86 Mn |
| Sep 30, 2023 | -302,000.00 |
| Jun 30, 2023 | 1.03 Mn |
| Mar 31, 2023 | -4.16 Mn |
| Dec 31, 2022 | 1.64 Mn |
| Sep 30, 2022 | 950,000.00 |
| Jun 30, 2022 | 2.23 Mn |
| Mar 31, 2022 | -4.37 Mn |
| Dec 31, 2021 | 1.42 Mn |
| Sep 30, 2021 | 1.16 Mn |
Assembly Biosciences 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=ASMB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "ASMB", "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=ASMB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();