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 | Eli Lilly | 1,230.11 Bn | 1,198.70 Bn | 19.71 Bn | 60.66 Bn |
| 2 | Johnson & Johnson | 644.39 Bn | 564.25 Bn | 17.30 Bn | 102.65 Bn |
| 3 | AbbVie | 503.52 Bn | 476.68 Bn | 12.70 Bn | 106.45 Bn |
| 4 | Merck | 363.29 Bn | 317.72 Bn | 12.21 Bn | 80.25 Bn |
| 5 | Novartis Ag | 298.23 Bn | 262.62 Bn | 11.24 Bn | 48.34 Bn |
| 6 | Astrazeneca | 267.53 Bn | 241.29 Bn | 12.86 Bn | 33.91 Bn |
| 7 | Amgen | 241.80 Bn | 197.20 Bn | 7.24 Bn | 78.66 Bn |
| 8 | Gilead Sciences | 195.07 Bn | 169.19 Bn | 6.22 Bn | 35.10 Bn |
| 9 | Pfizer | 173.33 Bn | 120.28 Bn | 10.94 Bn | 97.04 Bn |
| 10 | 4D Molecular Therapeutics | 832.72 Mn | -627.22 Mn | - | 84.47 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 84.47 Mn |
| Mar 31, 2026 | 60.58 Mn |
| Dec 31, 2025 | 60.55 Mn |
| Sep 30, 2025 | 54.51 Mn |
| Jun 30, 2025 | 52.25 Mn |
| Mar 31, 2025 | 45.51 Mn |
| Dec 31, 2024 | 49.18 Mn |
| Sep 30, 2024 | 50.49 Mn |
| Jun 30, 2024 | 31.18 Mn |
| Mar 31, 2024 | 28.72 Mn |
| Dec 31, 2023 | 31.45 Mn |
| Sep 30, 2023 | 31.29 Mn |
| Jun 30, 2023 | 27.12 Mn |
| Mar 31, 2023 | 25.17 Mn |
| Dec 31, 2022 | 30.28 Mn |
| Sep 30, 2022 | 28.48 Mn |
| Jun 30, 2022 | 30.19 Mn |
| Mar 31, 2022 | 28.63 Mn |
| Dec 31, 2021 | 34.05 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();