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.
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 Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,136.92 Bn | 1,105.50 Bn | 19.71 Bn | 108.40 Bn |
| 2 | Johnson & Johnson | 617.57 Bn | 536.10 Bn | 17.26 Bn | 116.09 Bn |
| 3 | AbbVie | 501.37 Bn | 474.48 Bn | 12.70 Bn | 141.05 Bn |
| 4 | Merck | 367.96 Bn | 322.33 Bn | 12.21 Bn | 87.82 Bn |
| 5 | Novartis Ag | 297.98 Bn | 261.97 Bn | 11.24 Bn | 80.09 Bn |
| 6 | Astrazeneca | 261.45 Bn | 235.14 Bn | 12.86 Bn | 65.46 Bn |
| 7 | Amgen | 236.30 Bn | 191.70 Bn | 7.24 Bn | 83.95 Bn |
| 8 | Gilead Sciences | 190.27 Bn | 164.46 Bn | 6.22 Bn | 37.53 Bn |
| 9 | Pfizer | 169.65 Bn | 116.29 Bn | 10.94 Bn | 115.64 Bn |
| 10 | Foghorn Therapeutics | 145.14 Mn | -180.81 Mn | - | 284.43 Mn |
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 |
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_KEY
import 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();