AbCellera Biologics (ABCL) Operating Expenses (2020 - 2026)
AbCellera Biologics (ABCL) reported Operating Expenses of $66.83 million for Q2 2026, up 0.2% from $66.67 million a year earlier and up 1.5% from the prior quarter.
AbCellera Biologics (ABCL) Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, AbCellera Biologics' Operating Expenses came in at $291.33 million, down 6.5% year-over-year; for FY2025, it was $292.23 million, down 14.9% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 30.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $343.6 million in FY2024 (+24.8%), $275.23 million in FY2023 (+2.3%), $268.91 million in FY2022 (+57.5%) and $170.79 million in FY2021 (+121.4%).
- Five-year quarterly Operating Expenses spans a low of $33.6 million in Q3 2021 and a high of $100.78 million in Q2 2024.
- Year over year, Operating Expenses gained in four of the last eight quarters, with growth averaging 1.7%.
- The high point for year-over-year Operating Expenses in five years was Q3 2021 (growth of 201.9%); the low point was Q2 2025 (a decline of 33.8%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $65.83 million (Q1 2026), $73.44 million (Q4 2025) and $85.23 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 653.54 Bn | 572.07 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 467.01 Bn | 440.17 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.16 Bn | 321.59 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 277.56 Bn | 233.43 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 258.23 Bn | 231.79 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 224.14 Bn | 179.54 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 187.30 Bn | 161.42 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.47 Bn | 110.41 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.31 Bn | 105.31 Bn | 2.84 Bn | 2.09 Bn |
| 10 | AbCellera Biologics | 3.89 Bn | 3.89 Bn | - | 66.83 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 66.83 Mn |
| Mar 31, 2026 | 65.83 Mn |
| Dec 31, 2025 | 73.44 Mn |
| Sep 30, 2025 | 85.23 Mn |
| Jun 30, 2025 | 66.67 Mn |
| Mar 31, 2025 | 66.90 Mn |
| Dec 31, 2024 | 77.81 Mn |
| Sep 30, 2024 | 100.17 Mn |
| Jun 30, 2024 | 100.78 Mn |
| Mar 31, 2024 | 64.85 Mn |
| Dec 31, 2023 | 75.23 Mn |
| Sep 30, 2023 | 61.49 Mn |
| Jun 30, 2023 | 61.45 Mn |
| Mar 31, 2023 | 77.07 Mn |
| Dec 31, 2022 | 59.32 Mn |
| Sep 30, 2022 | 63.65 Mn |
| Jun 30, 2022 | 54.31 Mn |
| Mar 31, 2022 | 91.63 Mn |
| Dec 31, 2021 | 57.78 Mn |
| Sep 30, 2021 | 33.60 Mn |
AbCellera Biologics 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=ABCL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ABCL", "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=ABCL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();