Assembly Biosciences (ASMB) Operating Expenses (2010 - 2026)
Assembly Biosciences' Operating Expenses came in at $19.72 million for Q2 2026, down 4.8% from $20.72 million a year earlier but up 0.7% from the prior quarter.
Assembly Biosciences (ASMB) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Assembly Biosciences reported Operating Expenses of $83.64 million, up 9.0% year-over-year; for FY2025, it was $84.42 million, up 14.2% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of -10.1% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $73.94 million in FY2024 (+3.0%), $71.81 million in FY2023 (-23.7%), $94.11 million in FY2022 (-32.3%) and $138.94 million in FY2021 (-3.4%).
- The five-year range for quarterly Operating Expenses is $15.05 million (Q3 2023) to $62.89 million (Q4 2021).
- Year-over-year, Operating Expenses increased in five of the last eight quarters, with growth averaging 8.7%.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2021 (growth of 54.6%), and the weakest in Q4 2022 (a decline of 63.5%).
- Business Quant data shows ASMB's Operating Expenses at $19.58 million (Q1 2026), $22.67 million (Q4 2025) and $21.67 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 | Assembly Biosciences | 468.67 Mn | -558.96 Mn | - | 19.72 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 19.72 Mn |
| Mar 31, 2026 | 19.58 Mn |
| Dec 31, 2025 | 22.67 Mn |
| Sep 30, 2025 | 21.67 Mn |
| Jun 30, 2025 | 20.72 Mn |
| Mar 31, 2025 | 19.36 Mn |
| Dec 31, 2024 | 18.89 Mn |
| Sep 30, 2024 | 17.80 Mn |
| Jun 30, 2024 | 20.74 Mn |
| Mar 31, 2024 | 16.51 Mn |
| Dec 31, 2023 | 19.71 Mn |
| Sep 30, 2023 | 15.05 Mn |
| Jun 30, 2023 | 17.49 Mn |
| Mar 31, 2023 | 19.56 Mn |
| Dec 31, 2022 | 22.98 Mn |
| Sep 30, 2022 | 23.40 Mn |
| Jun 30, 2022 | 24.57 Mn |
| Mar 31, 2022 | 23.16 Mn |
| Dec 31, 2021 | 62.89 Mn |
| Sep 30, 2021 | 25.13 Mn |
Assembly Biosciences 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=ASMB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-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=operating-expenses&ticker=ASMB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();