Forte Biosciences (FBRX) Operating Expenses (2016 - 2026)
Forte Biosciences (FBRX) reported Operating Expenses of $24.6 million for Q2 2026, up 112.5% from $11.58 million a year earlier and up 9.6% from the prior quarter.
Forte Biosciences (FBRX) Operating Expenses (2016 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Forte Biosciences' Operating Expenses came in at $90 million, up 106.0% year-over-year; for FY2025, it was $70.66 million, up 93.0% from FY2024.
- Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 8.8% (FY2020 to FY2025).
- By year, Operating Expenses came in at $36.6 million in FY2024 (+12.7%), $32.49 million in FY2023 (+133.8%), $13.9 million in FY2022 (-35.3%) and $21.49 million in FY2021 (-53.6%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q2 2020.
- Year over year, Operating Expenses has now increased in each of the last four quarters, with growth averaging 74.4% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q4 2025 (growth of 234.3%); the low point was Q3 2022 (a decline of 55.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $22.44 million (Q1 2026), $24.57 million (Q4 2025) and $18.38 million (Q3 2025).
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 | Forte Biosciences | 1.58 Bn | 1.38 Bn | - | 24.60 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 24.60 Mn |
| Mar 31, 2026 | 22.44 Mn |
| Dec 31, 2025 | 24.57 Mn |
| Sep 30, 2025 | 18.38 Mn |
| Jun 30, 2025 | 11.58 Mn |
| Mar 31, 2025 | 16.12 Mn |
| Dec 31, 2024 | 7.35 Mn |
| Sep 30, 2024 | 8.63 Mn |
| Jun 30, 2024 | 12.82 Mn |
| Mar 31, 2024 | 7.80 Mn |
| Dec 31, 2023 | 6.38 Mn |
| Sep 30, 2023 | 10.22 Mn |
| Jun 30, 2023 | 9.03 Mn |
| Mar 31, 2023 | 6.86 Mn |
| Dec 31, 2022 | 4.94 Mn |
| Sep 30, 2022 | 3.42 Mn |
| Jun 30, 2022 | 3.02 Mn |
| Mar 31, 2022 | 2.51 Mn |
| Dec 31, 2021 | 3.30 Mn |
| Sep 30, 2021 | 7.70 Mn |
Forte 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=FBRX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FBRX", "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=FBRX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();