4D Molecular Therapeutics (FDMT) Total Non-Current Liabilities (2019 - 2026)
4D Molecular Therapeutics (FDMT) recorded Total Non-Current Liabilities of $84.57 million in Q2 2026, up 61.4% from $52.41 million a year earlier and up 39.3% from the prior quarter.
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Analysis
4D Molecular Therapeutics (FDMT) Total Non-Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, 4D Molecular Therapeutics reported Total Non-Current Liabilities of $60.69 million, up 22.9% from FY2024.
- Annual Total Non-Current Liabilities has increased for three straight years, with a five-year compound annual growth rate of 15.1% (FY2020 to FY2025).
- Across earlier years, Total Non-Current Liabilities came in at $49.37 million in FY2024 (+55.8%), $31.69 million in FY2023 (+4.6%), $30.3 million in FY2022 (-11.3%) and $34.17 million in FY2021 (+13.5%).
- The Q2 2026 figure is the highest quarterly Total Non-Current Liabilities since Q4 2019.
- On a year-over-year basis, Total Non-Current Liabilities has increased for 12 consecutive quarters, with growth averaging 45.9% over the last eight quarters.
- Peak year-over-year performance for Total Non-Current Liabilities in the last five years was growth of 143.2% in Q2 2022, against a decline of 12.1% in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $60.7 million (Q1 2026), $60.69 million (Q4 2025) and $54.65 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 105.99 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 106.45 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 80.25 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 48.34 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -967.00 Mn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 81.11 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 36.04 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 100.86 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 5.92 Bn |
| 10 | 4D Molecular Therapeutics | 1.02 Bn | -436.78 Mn | - | 84.57 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 84.57 Mn |
| Mar 31, 2026 | 60.70 Mn |
| Dec 31, 2025 | 60.69 Mn |
| Sep 30, 2025 | 54.65 Mn |
| Jun 30, 2025 | 52.41 Mn |
| Mar 31, 2025 | 45.68 Mn |
| Dec 31, 2024 | 49.37 Mn |
| Sep 30, 2024 | 50.68 Mn |
| Jun 30, 2024 | 31.40 Mn |
| Mar 31, 2024 | 28.95 Mn |
| Dec 31, 2023 | 31.69 Mn |
| Sep 30, 2023 | 31.31 Mn |
| Jun 30, 2023 | 27.15 Mn |
| Mar 31, 2023 | 25.20 Mn |
| Dec 31, 2022 | 30.30 Mn |
| Sep 30, 2022 | 28.51 Mn |
| Jun 30, 2022 | 30.20 Mn |
| Mar 31, 2022 | 28.65 Mn |
| Dec 31, 2021 | 34.17 Mn |
| Sep 30, 2021 | 14.60 Mn |
API Access
4D Molecular Therapeutics Total Non-Current 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-non-current-liabilities&ticker=FDMT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "FDMT", "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-non-current-liabilities&ticker=FDMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();