Foghorn Therapeutics (FHTX) Total Liabilities (2019 - 2026)
Foghorn Therapeutics (FHTX) posted Total Liabilities of $284.43 million for Q2 2026, down 6.1% from $302.9 million a year earlier and down 4.7% from the prior quarter.
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Analysis
Foghorn Therapeutics (FHTX) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Foghorn Therapeutics' Total Liabilities came in at $306.6 million, down 7.0% from FY2024.
- Annual Total Liabilities has declined for four consecutive years, though with a five-year compound annual growth rate of 22.9% (FY2020 to FY2025).
- In prior years, Foghorn Therapeutics' Total Liabilities was $329.51 million in FY2024 (-9.3%), $363.11 million in FY2023 (-10.3%), $404.77 million in FY2022 (-4.3%) and $422.9 million in FY2021 (+286.5%).
- The Q2 2026 figure stands as the lowest quarterly Total Liabilities since Q3 2021.
- On a year-over-year basis, Total Liabilities has declined in each of the last 15 quarters, with an average decline of 8.9% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q1 2022, with growth of 297.2%; the weakest was Q3 2021, with a decline of 61.9%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $298.58 million (Q1 2026), $306.6 million (Q4 2025) and $294.62 million (Q3 2025).
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 | Foghorn Therapeutics | 206.67 Mn | -119.28 Mn | - | 284.43 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 284.43 Mn |
| Mar 31, 2026 | 298.58 Mn |
| Dec 31, 2025 | 306.60 Mn |
| Sep 30, 2025 | 294.62 Mn |
| Jun 30, 2025 | 302.90 Mn |
| Mar 31, 2025 | 320.34 Mn |
| Dec 31, 2024 | 329.51 Mn |
| Sep 30, 2024 | 336.66 Mn |
| Jun 30, 2024 | 342.91 Mn |
| Mar 31, 2024 | 352.49 Mn |
| Dec 31, 2023 | 363.11 Mn |
| Sep 30, 2023 | 370.81 Mn |
| Jun 30, 2023 | 388.93 Mn |
| Mar 31, 2023 | 397.47 Mn |
| Dec 31, 2022 | 404.77 Mn |
| Sep 30, 2022 | 409.61 Mn |
| Jun 30, 2022 | 409.27 Mn |
| Mar 31, 2022 | 415.90 Mn |
| Dec 31, 2021 | 422.90 Mn |
| Sep 30, 2021 | 105.09 Mn |
API Access
Foghorn Therapeutics 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=FHTX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "FHTX", "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=FHTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();