Forte Biosciences (FBRX) Total Liabilities (2016 - 2026)
Forte Biosciences' Total Liabilities came in at $21.95 million for Q2 2026, up 139.4% from $9.17 million a year earlier but down 12.6% from the prior quarter.
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Analysis
Forte Biosciences (FBRX) Total Liabilities (2016 - 2026) Analysis & Trends
At the end of FY2025, Forte Biosciences' Total Liabilities was $21.79 million, up 139.9% from FY2024.
- Total Liabilities has increased in each of the last four years, with a five-year compound annual growth rate of 57.3% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $9.08 million in FY2024 (+147.7%), $3.67 million in FY2023 (+15.3%), $3.18 million in FY2022 (+80.8%) and $1.76 million in FY2021 (-22.2%).
- The five-year range for quarterly Total Liabilities is $1.26 million (Q1 2022) to $25.12 million (Q1 2026).
- Year-over-year, Total Liabilities has increased for nine consecutive quarters, with growth averaging 105.4% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q2 2023 (growth of 316.4%), and the weakest in Q2 2022 (a decline of 49.2%).
- Business Quant data shows FBRX's Total Liabilities at $25.12 million (Q1 2026), $21.79 million (Q4 2025) and $12.99 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Forte Biosciences | 1.58 Bn | 1.38 Bn | - | 21.95 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 21.95 Mn |
| Mar 31, 2026 | 25.12 Mn |
| Dec 31, 2025 | 21.79 Mn |
| Sep 30, 2025 | 12.99 Mn |
| Jun 30, 2025 | 9.17 Mn |
| Mar 31, 2025 | 9.03 Mn |
| Dec 31, 2024 | 9.08 Mn |
| Sep 30, 2024 | 8.58 Mn |
| Jun 30, 2024 | 9.12 Mn |
| Mar 31, 2024 | 3.33 Mn |
| Dec 31, 2023 | 3.67 Mn |
| Sep 30, 2023 | 7.47 Mn |
| Jun 30, 2023 | 6.30 Mn |
| Mar 31, 2023 | 3.76 Mn |
| Dec 31, 2022 | 3.18 Mn |
| Sep 30, 2022 | 2.29 Mn |
| Jun 30, 2022 | 1.51 Mn |
| Mar 31, 2022 | 1.26 Mn |
| Dec 31, 2021 | 1.76 Mn |
| Sep 30, 2021 | 3.74 Mn |
API Access
Forte Biosciences Total Liabilities 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=total-liabilities&ticker=FBRX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=FBRX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();