EyePoint (EYPT) Total Non-Current Liabilities (2014 - 2026)
EyePoint (EYPT) recorded Total Non-Current Liabilities of $61.76 million in Q2 2026, up 12.3% from $54.99 million a year earlier and up 7.0% from the prior quarter.
EyePoint (EYPT) Total Non-Current Liabilities (2014 - 2026) Analysis & Trends
At the end of FY2025, EyePoint reported Total Non-Current Liabilities of $57.8 million, down 29.3% from FY2024.
- Annual Total Non-Current Liabilities has a five-year compound annual growth rate of -4.0% (FY2020 to FY2025).
- Across earlier years, Total Non-Current Liabilities came in at $81.76 million in FY2024 (-8.0%), $88.86 million in FY2023 (+6.6%), $83.39 million in FY2022 (+8.8%) and $76.64 million in FY2021 (+8.2%).
- The Q2 2026 figure is the highest quarterly Total Non-Current Liabilities since Q1 2025.
- On a year-over-year basis, Total Non-Current Liabilities rose in 1 of the last eight quarters, with an average decline of 19.0%.
- Peak year-over-year performance for Total Non-Current Liabilities in the last five years was growth of 45.3% in Q2 2023, against a decline of 42.3% in Q2 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $57.69 million (Q1 2026), $57.8 million (Q4 2025) and $51.4 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,261.99 Bn | 1,235.61 Bn | 20.46 Bn | 60.81 Bn |
| 2 | Johnson & Johnson | 678.93 Bn | 598.79 Bn | 17.30 Bn | 102.65 Bn |
| 3 | AbbVie | 518.29 Bn | 486.30 Bn | 13.12 Bn | 117.60 Bn |
| 4 | Merck | 365.98 Bn | 328.92 Bn | 13.19 Bn | 79.95 Bn |
| 5 | Novartis Ag | 316.85 Bn | 290.09 Bn | - | - |
| 6 | Astrazeneca | 293.40 Bn | 267.29 Bn | 13.26 Bn | -36.84 Bn |
| 7 | Amgen | 251.78 Bn | 203.43 Bn | 7.58 Bn | 76.12 Bn |
| 8 | Gilead Sciences | 210.61 Bn | 185.71 Bn | 6.73 Bn | 36.05 Bn |
| 9 | Pfizer | 166.87 Bn | 114.23 Bn | 12.56 Bn | 96.04 Bn |
| 10 | EyePoint | 31.41 Mn | -881.72 Mn | 507,000.00 | 61.76 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 61.76 Mn |
| Mar 31, 2026 | 57.69 Mn |
| Dec 31, 2025 | 57.80 Mn |
| Sep 30, 2025 | 51.40 Mn |
| Jun 30, 2025 | 54.99 Mn |
| Mar 31, 2025 | 63.99 Mn |
| Dec 31, 2024 | 81.76 Mn |
| Sep 30, 2024 | 81.95 Mn |
| Jun 30, 2024 | 95.34 Mn |
| Mar 31, 2024 | 78.71 Mn |
| Dec 31, 2023 | 88.86 Mn |
| Sep 30, 2023 | 101.42 Mn |
| Jun 30, 2023 | 118.39 Mn |
| Mar 31, 2023 | 75.60 Mn |
| Dec 31, 2022 | 83.39 Mn |
| Sep 30, 2022 | 83.54 Mn |
| Jun 30, 2022 | 81.47 Mn |
| Mar 31, 2022 | 77.08 Mn |
| Dec 31, 2021 | 76.64 Mn |
| Sep 30, 2021 | 73.14 Mn |
EyePoint 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=EYPT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "EYPT", "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=EYPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();